From 74c2fbd082619c248f554d03470c972673ba0157 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Wed, 27 Jun 2018 13:39:20 +0530 Subject: [PATCH 01/17] added cfp crawler --- cfp_crawler/logs.log | 2947 +++++++++++++++++++++ cfp_crawler/proposal/__init__.py | 0 cfp_crawler/proposal/__init__.pyc | Bin 0 -> 137 bytes cfp_crawler/proposal/items.py | 14 + cfp_crawler/proposal/middlewares.py | 103 + cfp_crawler/proposal/pipelines.py | 11 + cfp_crawler/proposal/settings.py | 90 + cfp_crawler/proposal/settings.pyc | Bin 0 -> 319 bytes cfp_crawler/proposal/spiders/__init__.py | 4 + cfp_crawler/proposal/spiders/__init__.pyc | Bin 0 -> 145 bytes cfp_crawler/proposal/spiders/crawler.py | 66 + cfp_crawler/proposal/spiders/crawler.pyc | Bin 0 -> 3431 bytes cfp_crawler/proposal/spiders/logs.log | 0 cfp_crawler/proposal/spiders/test.json | 18 + cfp_crawler/proposals.json | 2833 ++++++++++++++++++++ cfp_crawler/scrapy.cfg | 11 + 16 files changed, 6097 insertions(+) create mode 100644 cfp_crawler/logs.log create mode 100644 cfp_crawler/proposal/__init__.py create mode 100644 cfp_crawler/proposal/__init__.pyc create mode 100644 cfp_crawler/proposal/items.py create mode 100644 cfp_crawler/proposal/middlewares.py create mode 100644 cfp_crawler/proposal/pipelines.py create mode 100644 cfp_crawler/proposal/settings.py create mode 100644 cfp_crawler/proposal/settings.pyc create mode 100644 cfp_crawler/proposal/spiders/__init__.py create mode 100644 cfp_crawler/proposal/spiders/__init__.pyc create mode 100644 cfp_crawler/proposal/spiders/crawler.py create mode 100644 cfp_crawler/proposal/spiders/crawler.pyc create mode 100644 cfp_crawler/proposal/spiders/logs.log create mode 100644 cfp_crawler/proposal/spiders/test.json create mode 100644 cfp_crawler/proposals.json create mode 100644 cfp_crawler/scrapy.cfg diff --git a/cfp_crawler/logs.log b/cfp_crawler/logs.log new file mode 100644 index 0000000..106a3f5 --- /dev/null +++ b/cfp_crawler/logs.log @@ -0,0 +1,2947 @@ +2018-06-27 12:25:46 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:25:46 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:25:46 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:25:46 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:25:46 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:25:46 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:25:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:25:47 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:25:49 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:25:49 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:25:49 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:25:49 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 6, 55, 49, 588705), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52924416, + 'memusage/startup': 52924416, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 6, 55, 46, 910135)} +2018-06-27 12:25:49 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:27:09 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:27:09 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:27:09 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:27:09 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:27:09 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:27:09 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:27:10 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:27:10 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:27:11 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:27:12 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:27:12 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:27:12 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 6, 57, 12, 425249), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52613120, + 'memusage/startup': 52613120, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 6, 57, 9, 832012)} +2018-06-27 12:27:12 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:29:19 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:29:19 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:29:19 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:29:19 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:29:19 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:29:19 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:29:19 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:29:19 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:29:21 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:29:21 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:29:21 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) +Traceback (most recent call last): + File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks + current.result = callback(current.result, *args, **kw) + File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 34, in parseProposal + proposal[index] = some_dic +NameError: global name 'proposal' is not defined +2018-06-27 12:29:21 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:29:21 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 6, 59, 21, 772162), + 'log_count/DEBUG': 5, + 'log_count/ERROR': 1, + 'log_count/INFO': 7, + 'memusage/max': 52531200, + 'memusage/startup': 52531200, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'spider_exceptions/NameError': 1, + 'start_time': datetime.datetime(2018, 6, 27, 6, 59, 19, 112984)} +2018-06-27 12:29:21 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:29:40 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:29:40 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:29:40 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:29:40 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:29:40 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:29:40 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:29:40 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:29:41 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:29:42 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:29:42 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:29:42 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) +Traceback (most recent call last): + File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks + current.result = callback(current.result, *args, **kw) + File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 34, in parseProposal + proposals[index] = some_dic +NameError: global name 'proposals' is not defined +2018-06-27 12:29:42 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:29:42 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 6, 59, 42, 909398), + 'log_count/DEBUG': 5, + 'log_count/ERROR': 1, + 'log_count/INFO': 7, + 'memusage/max': 52936704, + 'memusage/startup': 52936704, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'spider_exceptions/NameError': 1, + 'start_time': datetime.datetime(2018, 6, 27, 6, 59, 40, 371316)} +2018-06-27 12:29:42 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:29:56 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:29:56 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:29:56 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:29:56 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:29:56 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:29:56 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:29:57 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:29:57 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:29:59 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:29:59 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:29:59 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:29:59 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 6, 59, 59, 471957), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52756480, + 'memusage/startup': 52756480, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 6, 59, 56, 844075)} +2018-06-27 12:29:59 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:31:00 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:31:00 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:31:00 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:31:00 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:31:00 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:31:00 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:31:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:31:01 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:31:03 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:31:03 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:31:03 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:31:03 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 1, 3, 782442), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52920320, + 'memusage/startup': 52920320, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 1, 0, 897261)} +2018-06-27 12:31:03 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:32:43 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:32:43 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:32:43 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:32:43 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:32:43 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:32:43 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:32:43 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:32:43 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:32:45 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:32:45 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:45 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: 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[scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: 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[scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: 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[scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:32:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: 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datetime.datetime(2018, 6, 27, 7, 2, 52, 969550), + 'log_count/DEBUG': 196, + 'log_count/INFO': 7, + 'memusage/max': 52461568, + 'memusage/startup': 52461568, + 'request_depth_max': 1, + 'response_received_count': 194, + 'scheduler/dequeued': 194, + 'scheduler/dequeued/memory': 194, + 'scheduler/enqueued': 194, + 'scheduler/enqueued/memory': 194, + 'start_time': datetime.datetime(2018, 6, 27, 7, 2, 43, 144637)} +2018-06-27 12:32:52 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:33:45 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:33:45 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:33:45 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:33:45 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:33:45 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 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(default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:34:51 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:34:51 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:34:51 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 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(finished) +2018-06-27 12:35:17 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:35:17 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:35:17 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:35:17 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:35:17 [scrapy.middleware] INFO: Enabled downloader middlewares: 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https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:35:27 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:35:27 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 65947, + 'downloader/request_count': 195, + 'downloader/request_method_count/GET': 195, + 'downloader/response_bytes': 1066390, + 'downloader/response_count': 195, + 'downloader/response_status_count/200': 194, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 5, 27, 905766), + 'log_count/DEBUG': 196, + 'log_count/INFO': 7, + 'memusage/max': 53112832, + 'memusage/startup': 53112832, + 'request_depth_max': 1, + 'response_received_count': 194, + 'scheduler/dequeued': 194, + 'scheduler/dequeued/memory': 194, + 'scheduler/enqueued': 194, + 'scheduler/enqueued/memory': 194, + 'start_time': datetime.datetime(2018, 6, 27, 7, 5, 17, 943679)} +2018-06-27 12:35:27 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:39:23 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:39:23 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:39:23 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:39:23 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:39:23 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:39:23 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:39:23 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:39:23 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:39:25 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:39:25 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:39:25 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:39:25 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 9, 25, 917780), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 53276672, + 'memusage/startup': 53276672, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 9, 23, 163264)} +2018-06-27 12:39:25 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:39:58 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:39:58 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:39:58 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:39:58 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:39:58 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:39:58 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:39:59 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:39:59 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:40:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:40:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:40:01 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:40:01 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 10, 1, 705240), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 53010432, + 'memusage/startup': 53010432, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 9, 58, 989745)} +2018-06-27 12:40:01 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:40:37 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:40:37 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:40:37 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:40:37 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:40:37 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:40:37 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:40:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:40:37 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:40:39 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:40:39 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:40:39 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:40:39 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 10, 39, 785433), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52920320, + 'memusage/startup': 52920320, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 10, 37, 132524)} +2018-06-27 12:40:39 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:41:49 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:41:49 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:41:49 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:41:49 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:41:49 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:41:49 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:41:50 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:41:50 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:41:52 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:41:52 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:41:52 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:41:52 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32130, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 11, 52, 626632), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52723712, + 'memusage/startup': 52723712, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 11, 49, 919731)} +2018-06-27 12:41:52 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:42:37 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:42:37 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:42:37 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:42:37 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:42:37 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:42:37 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:42:38 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:42:38 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:42:40 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:42:40 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:42:40 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) +Traceback (most recent call last): + File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks + current.result = callback(current.result, *args, **kw) + File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 39, in parseProposal + heading = col.xpath(".//tbody/td[@class='text-muted text-right']/small/text()").extract()[0] +IndexError: list index out of range +2018-06-27 12:42:40 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:42:40 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32131, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 12, 40, 576442), + 'log_count/DEBUG': 5, + 'log_count/ERROR': 1, + 'log_count/INFO': 7, + 'memusage/max': 53067776, + 'memusage/startup': 53067776, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'spider_exceptions/IndexError': 1, + 'start_time': datetime.datetime(2018, 6, 27, 7, 12, 37, 989769)} +2018-06-27 12:42:40 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:42:53 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:42:53 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:42:53 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:42:53 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:42:53 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:42:53 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:42:54 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:42:54 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:42:55 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:42:56 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:42:56 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:42:56 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32131, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 12, 56, 291246), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52514816, + 'memusage/startup': 52514816, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 12, 53, 970524)} +2018-06-27 12:42:56 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:43:30 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:43:30 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:43:30 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:43:30 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:43:31 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:43:31 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:43:31 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:43:31 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:43:31 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:43:31 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:43:31 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:43:31 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:43:33 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:43:33 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:43:33 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:43:33 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32131, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 13, 33, 519041), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52486144, + 'memusage/startup': 52486144, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 13, 31, 41207)} +2018-06-27 12:43:33 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:44:10 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:44:10 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:44:10 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:44:10 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:44:10 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:44:10 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:44:11 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:44:11 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:44:12 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:44:13 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:44:13 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:44:13 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32129, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 14, 13, 259668), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52674560, + 'memusage/startup': 52674560, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 14, 10, 957543)} +2018-06-27 12:44:13 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:44:35 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:44:35 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:44:35 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:44:35 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:44:35 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:44:35 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:44:35 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:44:35 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:44:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:44:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:44:37 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) +Traceback (most recent call last): + File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks + current.result = callback(current.result, *args, **kw) + File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 40, in parseProposal + heading = col.xpath(".//tr/td/small/text()").extract() +AttributeError: 'unicode' object has no attribute 'xpath' +2018-06-27 12:44:37 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:44:37 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32129, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 14, 37, 663396), + 'log_count/DEBUG': 5, + 'log_count/ERROR': 1, + 'log_count/INFO': 7, + 'memusage/max': 53157888, + 'memusage/startup': 53157888, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'spider_exceptions/AttributeError': 1, + 'start_time': datetime.datetime(2018, 6, 27, 7, 14, 35, 465093)} +2018-06-27 12:44:37 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:44:51 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:44:51 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:44:51 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:44:51 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:44:51 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:44:51 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:44:51 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:44:51 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:44:53 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:44:53 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:44:53 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:44:53 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32129, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 14, 53, 898515), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52920320, + 'memusage/startup': 52920320, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 14, 51, 342070)} +2018-06-27 12:44:53 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:45:56 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:45:56 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:45:56 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:45:56 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:45:56 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:45:56 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:45:56 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:45:57 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:45:58 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:45:58 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:45:58 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:45:58 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32129, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 15, 58, 910613), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 53002240, + 'memusage/startup': 53002240, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 15, 56, 622123)} +2018-06-27 12:45:58 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:51:26 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:51:26 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:51:26 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:51:26 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:51:26 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:51:26 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:51:26 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:51:26 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:51:28 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:51:28 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:51:29 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:51:29 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 21, 29, 82414), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52928512, + 'memusage/startup': 52928512, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 21, 26, 272238)} +2018-06-27 12:51:29 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:52:12 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:52:12 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:52:12 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:52:12 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:52:12 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:52:12 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:52:12 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:52:13 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:52:14 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:52:14 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:52:14 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:52:14 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 22, 14, 975094), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 53293056, + 'memusage/startup': 53293056, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 22, 12, 613721)} +2018-06-27 12:52:14 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:53:13 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:53:13 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:53:13 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:53:13 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:53:13 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:53:13 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:53:14 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:53:14 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:53:16 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:53:16 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:53:16 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:53:16 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 23, 16, 507293), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52613120, + 'memusage/startup': 52613120, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 23, 13, 861019)} +2018-06-27 12:53:16 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:53:54 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:53:54 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:53:54 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:53:54 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:53:54 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:53:54 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:53:55 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:53:55 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:53:57 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:53:57 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:53:57 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) +Traceback (most recent call last): + File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks + current.result = callback(current.result, *args, **kw) + File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 43, in parseProposal + print(last_updated) +NameError: global name 'last_updated' is not defined +2018-06-27 12:53:57 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:53:57 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 23, 57, 573534), + 'log_count/DEBUG': 5, + 'log_count/ERROR': 1, + 'log_count/INFO': 7, + 'memusage/max': 52543488, + 'memusage/startup': 52543488, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'spider_exceptions/NameError': 1, + 'start_time': datetime.datetime(2018, 6, 27, 7, 23, 54, 982346)} +2018-06-27 12:53:57 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:54:14 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:54:14 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:54:14 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:54:15 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:54:15 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:54:15 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:54:15 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:54:15 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:54:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:54:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:54:17 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:54:17 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 24, 17, 709732), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 53067776, + 'memusage/startup': 53067776, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 24, 15, 58725)} +2018-06-27 12:54:17 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:55:18 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:55:18 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:55:18 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:55:18 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:55:18 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:55:18 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:55:18 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:55:19 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:55:20 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:55:20 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:55:21 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:55:21 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 25, 21, 2368), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52969472, + 'memusage/startup': 52969472, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 25, 18, 636989)} +2018-06-27 12:55:21 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:56:16 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:56:16 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:56:16 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:56:16 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:56:16 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:56:16 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:56:16 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:56:17 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:56:18 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:56:18 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:56:18 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:56:18 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 26, 18, 940953), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52805632, + 'memusage/startup': 52805632, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 26, 16, 512313)} +2018-06-27 12:56:18 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:56:33 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:56:33 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:56:33 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:56:34 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:56:34 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:56:34 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:56:34 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:56:34 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:56:35 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:56:36 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:56:36 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:56:36 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32123, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 26, 36, 423425), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52862976, + 'memusage/startup': 52862976, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 26, 34, 66003)} +2018-06-27 12:56:36 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:58:59 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:58:59 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:58:59 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:58:59 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:58:59 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:58:59 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:59:00 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:59:00 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:59:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:59:02 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:59:02 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:59:02 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32122, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 29, 2, 301957), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 53014528, + 'memusage/startup': 53014528, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 28, 59, 410614)} +2018-06-27 12:59:02 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 12:59:15 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 12:59:15 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 12:59:15 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 12:59:15 [scrapy.core.engine] INFO: Spider opened +2018-06-27 12:59:15 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 12:59:15 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 12:59:15 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:59:15 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 12:59:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 12:59:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 12:59:17 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 12:59:17 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32122, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 29, 17, 978718), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52961280, + 'memusage/startup': 52961280, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 29, 15, 266848)} +2018-06-27 12:59:17 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 13:00:35 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 13:00:35 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 13:00:35 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 13:00:35 [scrapy.core.engine] INFO: Spider opened +2018-06-27 13:00:35 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 13:00:35 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 13:00:36 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 13:00:36 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 13:00:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 13:00:38 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:00:38 [scrapy.core.engine] INFO: Closing spider (finished) +2018-06-27 13:00:38 [scrapy.statscollectors] INFO: Dumping Scrapy stats: +{'downloader/request_bytes': 1008, + 'downloader/request_count': 4, + 'downloader/request_method_count/GET': 4, + 'downloader/response_bytes': 32122, + 'downloader/response_count': 4, + 'downloader/response_status_count/200': 3, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 30, 38, 251195), + 'log_count/DEBUG': 5, + 'log_count/INFO': 7, + 'memusage/max': 52572160, + 'memusage/startup': 52572160, + 'request_depth_max': 1, + 'response_received_count': 3, + 'scheduler/dequeued': 3, + 'scheduler/dequeued/memory': 3, + 'scheduler/enqueued': 3, + 'scheduler/enqueued/memory': 3, + 'start_time': datetime.datetime(2018, 6, 27, 7, 30, 35, 928535)} +2018-06-27 13:00:38 [scrapy.core.engine] INFO: Spider closed (finished) +2018-06-27 13:03:03 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) +2018-06-27 13:03:03 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful +2018-06-27 13:03:03 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} +2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled extensions: +['scrapy.extensions.memusage.MemoryUsage', + 'scrapy.extensions.logstats.LogStats', + 'scrapy.extensions.telnet.TelnetConsole', + 'scrapy.extensions.corestats.CoreStats'] +2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled downloader middlewares: +['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', + 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', + 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', + 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', + 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', + 'scrapy.downloadermiddlewares.retry.RetryMiddleware', + 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', + 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', + 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', + 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', + 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', + 'scrapy.downloadermiddlewares.stats.DownloaderStats'] +2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled spider middlewares: +['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', + 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', + 'scrapy.spidermiddlewares.referer.RefererMiddleware', + 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', + 'scrapy.spidermiddlewares.depth.DepthMiddleware'] +2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled item pipelines: +[] +2018-06-27 13:03:03 [scrapy.core.engine] INFO: Spider opened +2018-06-27 13:03:03 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) +2018-06-27 13:03:03 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 +2018-06-27 13:03:03 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 13:03:03 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from +2018-06-27 13:03:05 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) +2018-06-27 13:03:07 [scrapy.core.engine] DEBUG: Crawled (200) (referer: 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+{'downloader/request_bytes': 65947, + 'downloader/request_count': 195, + 'downloader/request_method_count/GET': 195, + 'downloader/response_bytes': 1066382, + 'downloader/response_count': 195, + 'downloader/response_status_count/200': 194, + 'downloader/response_status_count/301': 1, + 'finish_reason': 'finished', + 'finish_time': datetime.datetime(2018, 6, 27, 7, 33, 13, 434925), + 'log_count/DEBUG': 196, + 'log_count/INFO': 7, + 'memusage/max': 52928512, + 'memusage/startup': 52928512, + 'request_depth_max': 1, + 'response_received_count': 194, + 'scheduler/dequeued': 194, + 'scheduler/dequeued/memory': 194, + 'scheduler/enqueued': 194, + 'scheduler/enqueued/memory': 194, + 'start_time': datetime.datetime(2018, 6, 27, 7, 33, 3, 265461)} +2018-06-27 13:03:13 [scrapy.core.engine] INFO: Spider closed (finished) diff --git a/cfp_crawler/proposal/__init__.py b/cfp_crawler/proposal/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/cfp_crawler/proposal/__init__.pyc b/cfp_crawler/proposal/__init__.pyc new file mode 100644 index 0000000000000000000000000000000000000000..e45b03f325e797e1f989e0ba2eb0019aeb3b3bc5 GIT binary patch literal 137 zcmZSn%*!>2{aI8p0~9a^fU5vQ}y#Q%TkLo z^j%VmvrF;|^b3me3-XH-a}bR9_{_Y_lK6PNg31yOpf;P_{FKt1R6CI2#X!se0IxG0 Awg3PC literal 0 HcmV?d00001 diff --git a/cfp_crawler/proposal/items.py b/cfp_crawler/proposal/items.py new file mode 100644 index 0000000..b22f028 --- /dev/null +++ b/cfp_crawler/proposal/items.py @@ -0,0 +1,14 @@ +# -*- coding: utf-8 -*- + +# Define here the models for your scraped items +# +# See documentation in: +# https://doc.scrapy.org/en/latest/topics/items.html + +import scrapy + + +class ProposalItem(scrapy.Item): + # define the fields for your item here like: + # name = scrapy.Field() + pass diff --git a/cfp_crawler/proposal/middlewares.py b/cfp_crawler/proposal/middlewares.py new file mode 100644 index 0000000..23a5248 --- /dev/null +++ b/cfp_crawler/proposal/middlewares.py @@ -0,0 +1,103 @@ +# -*- coding: utf-8 -*- + +# Define here the models for your spider middleware +# +# See documentation in: +# https://doc.scrapy.org/en/latest/topics/spider-middleware.html + +from scrapy import signals + + +class ProposalSpiderMiddleware(object): + # Not all methods need to be defined. If a method is not defined, + # scrapy acts as if the spider middleware does not modify the + # passed objects. + + @classmethod + def from_crawler(cls, crawler): + # This method is used by Scrapy to create your spiders. + s = cls() + crawler.signals.connect(s.spider_opened, signal=signals.spider_opened) + return s + + def process_spider_input(self, response, spider): + # Called for each response that goes through the spider + # middleware and into the spider. + + # Should return None or raise an exception. + return None + + def process_spider_output(self, response, result, spider): + # Called with the results returned from the Spider, after + # it has processed the response. + + # Must return an iterable of Request, dict or Item objects. + for i in result: + yield i + + def process_spider_exception(self, response, exception, spider): + # Called when a spider or process_spider_input() method + # (from other spider middleware) raises an exception. + + # Should return either None or an iterable of Response, dict + # or Item objects. + pass + + def process_start_requests(self, start_requests, spider): + # Called with the start requests of the spider, and works + # similarly to the process_spider_output() method, except + # that it doesn’t have a response associated. + + # Must return only requests (not items). + for r in start_requests: + yield r + + def spider_opened(self, spider): + spider.logger.info('Spider opened: %s' % spider.name) + + +class ProposalDownloaderMiddleware(object): + # Not all methods need to be defined. If a method is not defined, + # scrapy acts as if the downloader middleware does not modify the + # passed objects. + + @classmethod + def from_crawler(cls, crawler): + # This method is used by Scrapy to create your spiders. + s = cls() + crawler.signals.connect(s.spider_opened, signal=signals.spider_opened) + return s + + def process_request(self, request, spider): + # Called for each request that goes through the downloader + # middleware. + + # Must either: + # - return None: continue processing this request + # - or return a Response object + # - or return a Request object + # - or raise IgnoreRequest: process_exception() methods of + # installed downloader middleware will be called + return None + + def process_response(self, request, response, spider): + # Called with the response returned from the downloader. + + # Must either; + # - return a Response object + # - return a Request object + # - or raise IgnoreRequest + return response + + def process_exception(self, request, exception, spider): + # Called when a download handler or a process_request() + # (from other downloader middleware) raises an exception. + + # Must either: + # - return None: continue processing this exception + # - return a Response object: stops process_exception() chain + # - return a Request object: stops process_exception() chain + pass + + def spider_opened(self, spider): + spider.logger.info('Spider opened: %s' % spider.name) diff --git a/cfp_crawler/proposal/pipelines.py b/cfp_crawler/proposal/pipelines.py new file mode 100644 index 0000000..7391e9e --- /dev/null +++ b/cfp_crawler/proposal/pipelines.py @@ -0,0 +1,11 @@ +# -*- coding: utf-8 -*- + +# Define your item pipelines here +# +# Don't forget to add your pipeline to the ITEM_PIPELINES setting +# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html + + +class ProposalPipeline(object): + def process_item(self, item, spider): + return item diff --git a/cfp_crawler/proposal/settings.py b/cfp_crawler/proposal/settings.py new file mode 100644 index 0000000..707c930 --- /dev/null +++ b/cfp_crawler/proposal/settings.py @@ -0,0 +1,90 @@ +# -*- coding: utf-8 -*- + +# Scrapy settings for proposal project +# +# For simplicity, this file contains only settings considered important or +# commonly used. You can find more settings consulting the documentation: +# +# https://doc.scrapy.org/en/latest/topics/settings.html +# https://doc.scrapy.org/en/latest/topics/downloader-middleware.html +# https://doc.scrapy.org/en/latest/topics/spider-middleware.html + +BOT_NAME = 'proposal' + +SPIDER_MODULES = ['proposal.spiders'] +NEWSPIDER_MODULE = 'proposal.spiders' +LOG_FILE = "logs.log" + +# Crawl responsibly by identifying yourself (and your website) on the user-agent +#USER_AGENT = 'proposal (+http://www.yourdomain.com)' + +# Obey robots.txt rules +ROBOTSTXT_OBEY = True + +# Configure maximum concurrent requests performed by Scrapy (default: 16) +#CONCURRENT_REQUESTS = 32 + +# Configure a delay for requests for the same website (default: 0) +# See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay +# See also autothrottle settings and docs +#DOWNLOAD_DELAY = 3 +# The download delay setting will honor only one of: +#CONCURRENT_REQUESTS_PER_DOMAIN = 16 +#CONCURRENT_REQUESTS_PER_IP = 16 + +# Disable cookies (enabled by default) +#COOKIES_ENABLED = False + +# Disable Telnet Console (enabled by default) +#TELNETCONSOLE_ENABLED = False + +# Override the default request headers: +#DEFAULT_REQUEST_HEADERS = { +# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', +# 'Accept-Language': 'en', +#} + +# Enable or disable spider middlewares +# See https://doc.scrapy.org/en/latest/topics/spider-middleware.html +#SPIDER_MIDDLEWARES = { +# 'proposal.middlewares.ProposalSpiderMiddleware': 543, +#} + +# Enable or disable downloader middlewares +# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html +#DOWNLOADER_MIDDLEWARES = { +# 'proposal.middlewares.ProposalDownloaderMiddleware': 543, +#} + +# Enable or disable extensions +# See https://doc.scrapy.org/en/latest/topics/extensions.html +#EXTENSIONS = { +# 'scrapy.extensions.telnet.TelnetConsole': None, +#} + +# Configure item pipelines +# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html +#ITEM_PIPELINES = { +# 'proposal.pipelines.ProposalPipeline': 300, +#} + +# Enable and configure the AutoThrottle extension (disabled by default) +# See https://doc.scrapy.org/en/latest/topics/autothrottle.html +#AUTOTHROTTLE_ENABLED = True +# The initial download delay +#AUTOTHROTTLE_START_DELAY = 5 +# The maximum download delay to be set in case of high latencies +#AUTOTHROTTLE_MAX_DELAY = 60 +# The average number of requests Scrapy should be sending in parallel to +# each remote server +#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 +# Enable showing throttling stats for every response received: +#AUTOTHROTTLE_DEBUG = False + +# Enable and configure HTTP caching (disabled by default) +# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings +#HTTPCACHE_ENABLED = True +#HTTPCACHE_EXPIRATION_SECS = 0 +#HTTPCACHE_DIR = 'httpcache' +#HTTPCACHE_IGNORE_HTTP_CODES = [] +#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage' diff --git a/cfp_crawler/proposal/settings.pyc b/cfp_crawler/proposal/settings.pyc new file mode 100644 index 0000000000000000000000000000000000000000..7d11cf3c4edbd873e088e61d31d5c70bbc5afe1d GIT binary patch literal 319 zcmY*UO-sW-5S>lx(u#_ILddCso{MP7DupyFO~iIR1aX%(n0A-UR`BArKiEIuBv@Jp z_U(MWHxvF`o`3I0ukY|@jQ%@%ctfB86d{8Z1I1cL1)u{^A($ShGteRAQI9%(pTITN zS$wPU`Xm^ltF&nl+m702{aI8p0~9aiw9rCZRFNWhKmkpl6{(8l*psXiukCnd zn^f9;3U5gK5}x>LyaV4k_HG*J0}@FxlkuFHbNS9~8h^}petUTPSw!_u1OFdk*e@}~ z_*0Y;ZB5pSwv_C9yx;d|%Oe#x$Pn!{Xa}?@`kCmM=*O)ozP;IPf>ZJrem1%aOE=Bz zlie&#t((Vsy$laiQ*IVXY|2xLe8DF(OyFLLg*5Qog%%BpA$*DwkeXy#1SKH*7@N}+ zH(80T8H!u7Xj42biw?yzvX~_^M{%3i$KW2diLZqk}RjS!JY$VxQ@iNM@ zwY=Q57qHQDuCSl^{wcya5Q;J{atrg;_H3RxHu^B)na30c8)>g%azIVd5VP2I2`2GJ z13IZEDkh-E4%x8hG5gU@;eT}V);)hBz|CMk3e$8ujP|?C+O;rQ=v}-N3$!^H80#Ff z8I-AGXB1&+P2~%|Vokc!#eb5?eu|af%lpR9k{8DI{Kv-byS$i4Jy}?Bne}U!fRAJQ ztqV&Rl$B(`&U(yWMf{I7Xk!Qna4ZcK?Ma})5kTXZXaqDo8a3!>orWGgetw@uQ{+5G zhVhxA;S^nh!}+7hZcl(B{NJQcj+OUB@!F%i;Bau2o(hhP%Z7a)v+wtAKYJ9Vp|uaM zjiFp!b%{&Owda25KkAic2ONpCK+03!xKOao2K{YQcA1@kc~pe1Cs3OsSB8<(Y@lYk z=17+i7sS7-!$J~5GX&zk(%2%;tP$wO>I7+$?OPF$WHC6i4!n0(j?x@C3mCS8iPS~a zQuFFYiL4f<_-LArA{w?33(sgYL&F&nKYg0Ps9i@yO`bU+58GTCMjaZW1fU#r=t}i5 zoF>rXSz38;@C!YyHJcOBvvjmY!&wN`G@7H~oCuvi;rfcr5M7bay_PJ3UzJ7bDWViR z@d7*UL-CSrnBf z1WW<4nKKBCUa_2ce-m1_@TeqD-@bc6i{mGj&skRp?H)o*_C=s>c%Znx61SJ0f%6FHCshP^z=^fGU; 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The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! My talk is going to be about highlighting the flexibility and power python gives in this case. I'm going to share my experience of building a tool for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/).", + "Prerequisites" : "Basic knowledge of Python, Django, Javascript and querying RDBMS is required.", + "Content URLs" : "Slides will be uploaded soon Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv/", + "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia. Other than coding, I love reading, writing and trying out new things.", + "Speaker Links": ["Blog: https://medium.com/@meghasharma4910", "Github: https://github.com/MeghaSharma21","Outreachy project: https://github.com/MeghaSharma21/WikiCV", "Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018"], + "Section" :"Web development", + "Type" : "Talks", + "Target Audience" :"Beginner", + "Last Updated" : "27 Jun, 2018" + + } + +} \ No newline at end of file diff --git a/cfp_crawler/proposals.json b/cfp_crawler/proposals.json new file mode 100644 index 0000000..4760e24 --- /dev/null +++ b/cfp_crawler/proposals.json @@ -0,0 +1,2833 @@ +{ + "1": { + "Content URLs": "Would be uploaded soo", + "Description": "My talk would be starting from the very grounds of machine learning . What is it and how is it connected with our biological brain. I will be introducing some biological concepts and infrastructure of our brain to explain to them how our natural ability of thinking and deduction work, because at last the whole field of artificial intelligence is just an attempt to mimic our brain. Isn't it?\nThis will be through a series of fun QnA . Then we will see the mathematics core which enables us to lay down the logic and basics of the brain as formulas . \n- Then we will start with the classic linear regression . Will study the basic idea behind it and also see what kind of problems we should apply it.\n- Next will be the logistic regression , a classification algorithm. Learn the difference between these two and how logistic regression could be implemented and study the beautiful mathematics behind it. \n- Then we will go for a clustering algorithm, that is, Knn . Study the simple dynamics and application of this algorithm\n- Then a glimpse over the structure and mathematics of neural network . As this talk is for the novice I would keep the mathematics to the minimum and would no go deep into \"deep\" learning.\nWe will wrap up seeing some of my projects in action so that the audience could feel the power of AI", + "Last Updated": "27 Jun, 2018", + "Section": "Data science", + "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", + "Speaker Links": "udayupreti.m", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "uday1201", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/evolution-and-basics-of-machine-learning~bWzxa/", + "title": "Evolution and basics of Machine Learning" + }, + "2": { + "Content URLs": "http://www.thedurkweb.com/automated-anonymous-interactions-with-websites-using-python-and-tor", + "Description": "Need to get some repetitive task done on your web browser? Want to automatically fill boring forms? Or maybe you want to crawl pages that annoyingly check whether you are a browser or a robot. Or maybe you want to repeatedly bias an online poll in your favour (as long as you don't harm anyone). Circumvent all of that with Selenium, the browser automation tool. And if want you want to protect your IP while doing it then just fire up tor-selenium browser, which gives you the power of tor and browser automation. In this talk: I'll show you how to set up the browser. How to access the website through code. How to design your script to navigate through the pages and button clicks. How to effectively do your activity, like filling up text fields etc. And then a demo of it working completely.", + "Last Updated": "27 Jun, 2018", + "Section": "Developer tools and Automation", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Ved Mathai (~ved47)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automate-anything-on-the-web-using-python-bindings-for-tor-selenium-and-hide-your-ip-while-doing-it~eVyXd/", + "title": "Automate anything on the Web using Python bindings for Tor-Selenium and hide your IP while doing it." + }, + "3": { + "Content URLs": "in progres", + "Description": "Data classes have been introduced in Python 3.7 (Refer to PEP 557 -- Data Classes). This talk is to introduce data classes to the audience. Talk about why data classes and how they are different from other alternatives like named tuples, et", + "Last Updated": "27 Jun, 2018", + "Prerequisites": "Knowlede of Object Oriented Programming with Pytho", + "Section": "Core python and Standard library", + "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.\nI have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delhi I have done a talk \"How import works in Python\" at Pycon 2017 Delh", + "Speaker Links": "github link - https://github.com/sdonapar\nlinkedin profile - https://www.linkedin.com/in/sasidonaparthi\ntwitter handle - @sdonapa", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Sasidhar Donaparthi (~sasidhar)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/what-you-need-to-know-about-data-classes-in-python-37~dRrEd/", + "title": "What you need to know about data classes in Python 3.7" + }, + "4": { + "Content URLs": "Tutorial Series https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-2 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-3 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-4 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-5 Github Repo (Most starred repo for a Python implementation of YOLO v3, at 589 stars at the time of speaking) https://github.com/ayooshkathuria/pytorch-yolo-v", + "Description": "The workshop will walk the audience on how to implement a state of the art object detector (YOLO: You only look once) from scratch using the PyTorch deep learning framework. The main The aim is not to merely show the audience how to implement the detector that can work on videos, but give them a deep insight about the problems that rear their heads only when one is implementing a deep architecture. Some of these issues include, Rapid Prototyping with PyTorch : Which PyTorch classes and abstractions to use to quickly code up neural network. How to implement a layer if it doesn't already ship with PyTorch. Our detector has 3 such layers! How to deal with complex architectures efficiently : What if your network has more than a 100 layers? Our detector certainly has 106 ! Do we write 106 lines of code for each layer? What if we want to run our detector over a folder containing 100000 images that we can't fit into our RAM at once. Best PyTorch practices to get around problems like these will be discussed. Speeding up Python code with Vectorisation : Python can be a slow language, but PyTorch does provide a lot of functions that are merely wrappers for super fast C code under the hood. Vectorisation and broadcasting will be covered in great detail. Using vectorised code instead of loops to do iterative tasks can give speed ups as much as 100x. Our detector can not work in real time without these optimisations. Managing GPU resources : How to write device-agnostic code, parallelize GPU/CPU ops, practices to reduce redundant GPU memory usage, and how to time GPU code. We will review the entire code base, and spend much time on justifying design decisions. A lot of non-critical code will be provided as it is to the audience, while they are expected to code along when it comes to the critical parts. These parts would be discussed in greater detail. Important PyTorch features might also be demonstrated using toy examples outside the detector code base, which the audience is also expected to code along. A docker image as well as Jupyter notebook will be provided to the audience. Google Colab may also be considered with notebooks provided. Most of the tutorials online demonstrate how to write code that is more proof-of-concept rather than being performant. When it comes to learning to code complex architectures, especially when we are transitioning from beginner to intermediate stage, most of us have to rely on the laborious process of reading open source code. The idea of this workshop is to help audience move along this journey", + "Last Updated": "27 Jun, 2018", + "Prerequisites": " Knowledge of Python Basic understanding of convolutional neural networks, image classification and preferably, but not necessarily object detection (Will spend 15 min or so giving an overview of YOLO algorithm) Basic understanding of PyTorch (the level that can be reached by taking the official 60 min tutorial)", + "Section": "Data science", + "Speaker Info": "I'm currently an research intern at a DRDO Lab where I work on video semantics, detecting violence as well as unusual activity in surveillance footage. My other interests include weakl supervised, unsupervised learning and generative modelling using GANS. I've recently graduated college, and while at college, I founded AI Circle, SMVDU, a club dedicated to helping students get started with machine learning through lectures and hands-on sessions, many of which were conducted by me. I am very passionate about sharing what I've learned, and write articles regularly at Paperspace and Medium", + "Speaker Links": "Paperspace blog: https://blog.paperspace.com/author/ayoosh/ Medium : https://medium.com/@ayoosh Github : https://github.com/ayooshkathuri", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Ayoosh Kathuria (~ayoosh)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-implement-a-yolo-object-detector-from-scratch-using-pytorch-and-opencv~aQq9a/", + "title": "How to implement a YOLO object detector from scratch using PyTorch and OpenCV" + }, + "5": { + "Content URLs": "Slides will be uploaded soon. Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv", + "Description": "There lies a huge gap between a website made as a hobby/college project and that made for professional purposes. The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! My talk is going to be about highlighting the flexibility and power python gives in this case.\nI'm going to share my experience of building a tool for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/). The tool summarizes the contributions of the Wikipedia editors and presents it in a CV-like format. The biggest challenge here was dealing with millions of edits and doing all the related computations within seconds. Without any kind of optimizations, the page took 3 hours to load. Through my talk, I want to bring out the journey from 3 hours to 3 seconds on the table! Broad outline of my talk is as follows: Deciding upon the web framework : In this, Django, Flask and Pyramid will be compared. Reducing the response time : When one is dealing with a dataset as huge as that of Wikipedia's, response time becomes of paramount importance. Optimizations like implementing a cache layer , using cron jobs , sessions etc will be discussed. Also, design choices will be compared - like cache layer using database vs sessions in python. Database Optimizations : In this I'll be covering how database choice and query optimizations can affect the performance when dealing with large datasets. In this, ORM will be discussed in detail. Component based approach with plain javascript : When one component of your website slows down the rendering of the whole page, what should one do? This is going to be another aspect that I'm going to touch upon - dividing page into pagelets without using any javascript framework. Let code speak of professionalism : Lastly, I'll be discussing about the good coding techniques and practices that should be used. (Like making dependency graph of modules for better modularity.) Hope you will find this talk interesting. :)", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "Basic knowledge of Python, Django, Javascript and querying RDBMS is required", + "Section": "Web development", + "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia.\nOther than coding, I love reading, writing and trying out new things", + "Speaker Links": " Blog: https://medium.com/@meghasharma4910 Github: https://github.com/MeghaSharma21 Outreachy project: https://github.com/MeghaSharma21/WikiCV Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Megha Sharma (~megha480)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/optimizations-in-web-development-journey-from-a-college-project-to-a-product-using-django~dPp4d/", + "title": "Optimizations in Web Development: Journey from a college project to a product using Django" + }, + "6": { + "Content URLs": "Will be updated soon", + "Description": "In this talk, I will provide a concise understanding of Threading and Global Interpreter Lock(GIL) in Python. In the modern era of hybrid cores and processors, there is an in demand need for concurrent and parallel programming paradigms. Python, since its inception has amazing support for single threaded applications. The extensive use of Python in booming fields like Machine Learning has paved the way to constantly improve multi-threaded applications in Python. I will speak from ground level covering very crucial aspects of Threading and Locks which will pave the way for community to develop better Python applications. Program outcomes: How threading can improve performance, its pros and cons. What works best in which environment between threads and processes. Why GIL matters the most in Python How to leverage the power of open source source code to understand the crux of language. Contents to be covered: 1. Threading for noobs: Terminologies: Process, threads, multithreading, multiprocessing, types of threads, locks, mutex, CPU and I/O bound processes. Multithreading in Python: Threading module (with example) Comparative analysis of Sequential vs Multithreaded execution in Python (with example) 2. Understanding the global interpreter lock (GIL): What and why of GIL Impact of GIL on CPU and I/O Bound Processes In-depth understanding of GIL using cpython interpreter source code Reference counting Ticks via context switching 3. Infamous concepts: Cooperative vs Preemptive multitasking Parallelism vs Concurrency Thread Safety in Python 4. Removing the GIL: Famous GIL removal patch Guido on GIL, Larry Hastings Gilectomy 5. Questions Agenda: 0 - 6 minutes : section 1, Threading for noobs 6 - 15 minutes : section 2, Understanding GIL 15 - 25 minutes : section 3, Infamous concepts 25 - 28 minutes : section 4, Removing the GIL 28 - 30 minutes : section 5, Questions ", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Basics of Python: Class, objects, list, libraries", + "Section": "Core python and Standard library", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself from scratch. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-multithreading-by-deciphering-the-cpython-interpreter-source-code~aOora/", + "title": "Understanding multithreading by deciphering the cpython interpreter source code" + }, + "7": { + "Content URLs": "https://gautam-ankit.github.io/HomeAR", + "Description": "In this project, we are going to create a home finder in which we are going to give an individual marker/bar code to each and every home and going to create a web-app which will tell about the home on starring the camera on the marker/bar code. This idea will help out to find some place way better than the Google maps because one can generate its own marker for his/her home and can edit the details of there home, through which one can recognize the home. For management of this data we are going to use several concept of Big data also. But this is the best way possible to implement and link augmented reality with python", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "HTML and CSS and basic Javascript,\nbasic python ,\nsome programming concepts", + "Section": "Core python and Standard library", + "Speaker Info": "As a Microsoft student partner, I gave several presentations for Hour of code. And as a Mozilla campus club caption, I gave several presentations for Virtual reality and Augmented reality using Aframe web framework", + "Speaker Links": "https://www.linkedin.com/in/ankit-gautam-9b0524108", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Ankit Gautam (~Gautam-ankit)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/home-finder-using-python-and-augmented-reality~dNnvd/", + "title": "Home finder using Python and Augmented Reality" + }, + "8": { + "Content URLs": "So, Slides can be seen here: https://slides.com/tanayagrawal/efficient-hyperparameter-optimization#/ Full content is available here: https://github.com/tanayag/pycon_18_hyperopt You can also have a look at my article: https://blog.goodaudience.com/on-using-hyperopt-advanced-machine-learning-a2dde2ccece7 In the Repo iris.csv is the dataset that we'll work on. docker folder contains the scripts to setup Environment \"Introduction to Hyperopt.ipynb\" is iPython Notebook which contains the implementation which we'll work on during workshop and understand the concept \"link_to_slides.txt\" contains the link to our presentation", + "Description": "Hands on Experience with Advanced Hyper-parameter Optimization Techniques, using Hyperopt We'll go step by step, starting with the Hyper-parameter optimization with SkLearn's Grid Search, we'll compare it with the more effective Hyper-Parameter Optimization TPE Algorithm implemented in Hyperopt.\nWe'll also go through on how to parallelize the evaluations using MongoDB making the optimization even more effective. A Docker Image will be provided, so that participants won't have to waste time in setting up the environment. The Workflow of the Workshop would be: We will start with a slide presentation so that participants get some insight on what they are going to do. After that we'll shift on to a Juypter Notebook(pre-installed in the docker environment, so you can just focus on the implementation part), here they will implement the code, and see the best algorithms of hyperparameter optimization working. After that we'll show a working demo of a problem that we were working on and solved using Hyperopt during our Summer Intern at MateLabs. After attending this workshop you will be able to apply Hyper-parameter optimization using better algorithms which decides the hyper-parameters based on information. In short much much efficient model training", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "Basic Python Coding and a little familiarity with Machine Learning/Data Science", + "Section": "Data science", + "Speaker Info": "Tanay Agrawal Working on Machine Learning/Deep Learning and also an Open Source Enthusiast. Currently in Final Year of his Engineering. He is working as Deep Learning Intern at Matelabs. He along with team at MateLabs is creating Meta Algorithms, so that user even with minimum or no knowledge of Machine Learning would be able to use it. Also he is a contributor at SymPy. He has previously worked on state of the art Classification and Object detection Models as well. He has previously conducted Python workshop at SFD-SMVDU and also he conduct the session of AI Circle at his College regularly. Anubhav Kesari Currently at fInal year of engineering from IIIT Guwahati. Two worked on the same problem and solved it using Hyperopt. Anubhav is the summer intern at MateLabs as well. He has worked at Cadence Design Systems in summer of 2017 as Software Development Intern. He has also been working on development of blockchain based distributed neural networks at MateLab", + "Speaker Links": "Tanay Agrawal https://github.com/tanayag https://angel.co/tanay_agrawal Anubhav Kesari https://github.com/kesarianubhav https://www.linkedin.com/in/anubhav-kesari-588a03131", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "tanay_agrawal", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-ml-learn-how-to-improve-accuracy-by-optimizing-hyper-parameters-using-hyperopt~aMmGa/", + "title": "Advanced ML: Learn how to Improve Accuracy by optimizing Hyper-Parameters using Hyperopt" + }, + "9": { + "Content URLs": "Will be uploaded soon", + "Description": "Python - Turing Complete and easy at the same time. Given its simplicity, one may be tempted to use it to solve a problem of any magnitude. But as the codebase scales, so does the difficulty in managing it. And as the applicability scales up, so does the difficulty in maintaining performance. In this workshop, we will walk through how these problems crop up in the first place, and how to tackle them. This workshop will NOT cover scalability from the perspective of distributing data loading and computation across multiple compute units (horizontal scalability). We will focus more on how to write code from the very start that is both efficient in performance and makes a larger codebase manageable. The topics we will go through are: 1.Performance - How should one write \"fast\" code Finding the bottleneck - Profiling Compiling Python to C - JIT vs AOT / Cython vs Numba vs Pythran vs PyPy - How they differ and choosing which one is for you Concurrency - To parallelize or not to parallelize, to sync or not to sync Choosing the right data structures Hacks and bits that can get us the extra performance 2.Design Principles - How should one write \"good\" code, because we have all written code that we have difficulty in understanding ourselves in no time Logging - Keeping track of what happened when and where Type Checking - The why and the how Unit Tests and beyond", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Cython, numba, and pythran installed. All of them are available on pip/conda Working knowledge of Python", + "Section": "Others", + "Speaker Info": "I am a final year student at IIT Madras. I currently lead the CV and AI team at Detect Technologies and have headed the CVI group at CFI, IIT Madras in the past. I love learning new things about how and why things work, and love sharing that knowledge", + "Speaker Links": " Personal Website Github Linkedin StackOverflow", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-not-break-your-head-or-computer-writing-python-at-scale~dLlrd/", + "title": "How to not break your head (or computer) writing python at scale" + }, + "10": { + "Content URLs": "https://en.wikipedia.org/wiki/Decentralized_autonomous_organization\nhttps://blockchaindevs.github.io/MeetupDA", + "Description": "Open Source Communities and their management. How things work currently A case study of different open source organizations: Advantages and disadvantages of current systems. The issues with Open Source organizations are nothing new, what are the possible solutions available? DAO and automation of majority of the tasks of a \"Open by default organizations\" What part of the organization can be automated, what can't. Important Aspects that usually breed trust among members::\n - Transparency\n - Consistency & Automation\n - Inclusion & support Our Proposal We will be posting codebase and complete websites and mobile apps that offer these solutions: Automated and transparent membership procedure. Transparent Public Elections on Blockchain for a board with automated publication of votes and results. Automate votes based on proposals Automated Procedure to apply for grants: with voting members and results being put up on Blockchain Automated meetings with MOM being recorded and put up on blockchain. Testing Proposal from the ground up: Start Small and test if these methods work locally in meetup groups \n- Automation of Tasks around meetups:\n...\nWe will keep updating here as and when we have deployed solutions on blockchain Tools used for these automation: Blockchain Dapps using : Solidity & Vyper\nPython: Kivy Framework for mobile apps and Web3.js & other such frameworks. Repos:\n They will be made online shortly, currently the experimentation is going on the following repos: https://blockchaindevs.github.io/MeetupDAO please excuse for the alpha quality of the software as they are just experiments as of now. This is a open source initiative based on the needs we feel we have seen arise in open source communities around us. Ultimate Goal Use this proposal as a catalyst and create small Organizations in local communities testing this theory. If things work in local communities, create a National Level Organization for managing the tasks around PyCon India This is just one of the hopefully multiple proposed solutions for moving on post PSSI", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "A willing ness to contribute, ability to learn. \nOpen Mind to experiment even if it leads to failure", + "Section": "Developer tools and Automation", + "Speaker Info": "http://github.com/akshaurora Akkshay is huge open source enthusiast, he has helped bootstrap different communities around Kivy, PyDelhi, ILUGD, BlockchainDevs , HyperLedger Delhi/NCR & chaired conferences like PyDelhiConf, Pycon-India, Global Blockchain Conference. He has been involved and working on blockchain based projects from 2011 onwards, he is one of the core developers of Kivy python framework & Electrum bitcoin wallet that has been built on top of it", + "Speaker Links": "http://github.com/akshauror", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Akshay Arora (~akshayaurora)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-open-source-communities-on-blockchain-a-transparent-way-to-manage-organizations~aKkxa/", + "title": "Automating Open Source communities on Blockchain: A transparent way to manage Organizations" + }, + "11": { + "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research \nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", + "Description": "We survey progress in recent years toward developing a theory of deep learning. Works have started addressing issues such as: (a) the effect of architecture choices on the optimization landscape, training speed, and expressiveness (b) quantifying the true \"capacity\" of the net, as a step towards understanding why nets with hugely more parameters than training examples nevertheless do not overfit (c) understanding inherent power and limitations of deep generative models, especially (various flavors of) generative adversarial nets (GANs) (d) understanding properties of simple RNN-style language models and some of their solutions (word embeddings and sentence embeddings", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", + "Section": "Others", + "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", + "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban http://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban \nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Parthi", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/toward-theoretical-understanding-of-deep-learning~dJjgd/", + "title": "Toward Theoretical Understanding of Deep Learning" + }, + "12": { + "Content URLs": "http://www.calmdownkarm.com/2018/clustering (Blog Post)\nhttps://github.com/CalmDownKarm/360classificatio", + "Description": "Quick walkthrough of how word2vec combined with more traditional clustering mechanisms can be used for topic modelling and document classificatio", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "Some familiarity with clustering (Kmeans) is helpful, but not required", + "Section": "Data science", + "Speaker Info": "Recently graduated from BML Munjal University, Developer at Gramener", + "Speaker Links": "calmdownkarm.co", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Karmanya Aggarwal (~CalmDownKarm)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/document-clustering-with-word2vec-and-hierarchial-clusters~dG7Jd/", + "title": "Document Clustering with Word2vec and Hierarchial Clusters" + }, + "13": { + "Content URLs": "TB", + "Description": "\"Data is the new Oil!\" But, what is the benefit of this oil if you cannot refine (analyse) and sell/use (derive value) it. Big Data has pushed the frontier of analytical processing to gather more actionable insights in the past decade from having separate analytical servers to performing analytics close to the Data Lake/Cloud. A new paradigm of FOG computing has recently emerged which enables analyzing data at the Edge (close to the data capture device). This talk will focus on Edge Analytics enabled by Python & Raspberry Pi. Why attend this session? This session will provide a first hand look into the paradigm of FOG computing and Edge analytics. Model deployment is a critical part of the analytics life-cycle and this talk will provide insights and best practices to ensure seamless and robust model deployment. Also, the audience will get a flavor of python in embedded devices through the live and interactive demonstration using Raspberry Pi. Content The talk will cover the following sections: Evolution of analytics (Dedicated Machines -> Cloud -> Edge) The need of Edge analytics Analytics Life-cycle (ALC): Introduction, Importance of Model Deployment, Adapting ALC for Edge Analytics Model Exchange Formats (PFA, ONNX) for Deployment: Introduction & Need for Democratizing model development process Edge Device Introduction - Raspberry Pi Introduction to Portable Format for Analytics (PFA) Model Deployment on Edge Device (Raspberry Pi) using open source PFA engine implemented in Python Hands-on Application Use Cases - Deployment of Clustering, Regression, Decision Tree, Neural Network/ Deep Learning Models", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Python 2.7.x titus python package (pip install titus)", + "Section": "Embedded python", + "Speaker Info": "A die hard Pythonista, Ankit is a full time open source contributor and a former Google Summer of Code 2013 scholar under Python Software Foundation. Currently, he is developing the open source Portable Format for Analytics (PFA) implementation - Titus on Python 3. Ankit has 4 years of industrial experience in machine learning, quantitative modelling, data analytics and visualization. Over the years, he has developed an expertise in handling the entire data analytics pipeline comprising \u2013 ingestion, exploration, transformation, modeling and deployment. He is a polyglot programmer with an extensive knowledge of algorithms, statistics and parallel programming. He has shipped multiple releases of DB Lytix, a comprehensive library of over 800 mathematical and statistical functions used widely in data mining, machine learning and analytics applications, including \u201cbig data analytics\u201d. An IIT Kanpur alumnus, Ankit is also an active researcher with publications in international journal and conferences. He is actively working in the domain of IoT Analytics and has recently presented his work: \"Discovering Knowledge from Smart Meter Data using Competitive Learning Methods\" in the Data Science Congress 2018. \u201cIn-database Analytics in the Age of Smart Meters\u201d in the 5th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, 2017. \u201cSmart Meter Data Analytics using Orange\u201d in Scipy India 2017, Mumbai. Ankit is an active contributor to the Indian Python Community and has conducted the following workshops in PyCon India and Scipy India: Scientific Computing using Orange in SciPy India 2017, Mumbai. Making Machine Learning Fruitful and Fun using Orange in PyCon India 2017, New Delhi.", + "Speaker Links": "LinkedIn Youtube channel Githu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Ankit Mahato (~ankit60)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fog-analytics-using-raspberry-pi-and-python~eE7gb/", + "title": "Fog Analytics using Raspberry Pi and Python" + }, + "14": { + "Content URLs": "Open weather map https://openweathermap.org/ Twitter API https://developer.twitter.com/en/docs.htm", + "Description": "This talk focuses on demonstrating the power of Python's Statistical and Data Science Libraries. I have been working on a project to classify average human sentiments as positive or negative. Classification is completely based on the prediction made by the ML models, which incorporates the weather of the location. I will try to prove that weather is \"one of the factor\" contributing to the moods/emotions of humans and ultimately affects the decision making ability. I have achieved the accuracy of 60%, which is good enough, with the existing and publically available data. The accuracy will certainly grow along with the data", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Basic knowledge of Python Basic understanding of Statistics", + "Section": "Data science", + "Speaker Info": "I am a Python enthusiast, always a keen explorer of the power of python. I have been passionate about Python since my early college days, and then I went on developing many Web Apps, APIs based on Django and Flask, later on, my journey with Python turned towards exploring the magic of Data Science. It has been quite an interesting time spent exploring this field, and I must say that the depth cannot be determined. The more you experience, the more moments of awe occur", + "Speaker Links": " https://omkar-dsd.github.io/ https://towardsdatascience.com/a-simple-word-sense-disambiguation-application-3ca645c56357 https://medium.com/@omkar_dsd/when-killing-humans-becomes-the-right-choice-e3964419e78c https://stackoverflow.com/users/5130528/omkar-deshpande https://www.github.com/omkar-dsd", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Omkar Deshpande (~omkar08)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/analyzing-the-impact-of-weather-on-human-sentiments~bD7Ka/", + "title": "Analyzing the impact of weather on human sentiments" + }, + "15": { + "Content URLs": "TB", + "Description": "This tutorial is meant to familiarize participants with Tensorflow, generally as a tensor library and particularly as a tool for doing day-to-day machine learning tasks. The ultimate goal of the tutorial is to be able to make participants comfortable enough with it so that they can use tensorflow as a scalable substitute for other ML libraries like sklearn. Why Learn Tensorflow? For the same reason that you should learn NumPy. Tensorflow is to Keras (and many other deep learning libraries) what NumPy is to sklearn (and many other machine learning libraries). It is the underlying data model of many deep learning applications. There are always nooks and crannies in any deep learning application that high level wrapper libraries cannot reach. The tutorial is aimed at making these accessible and debuggable with tensorflow. What will I learn? The focus of the tutorial would be on loss functions - ensuring their fundamental correctness with respect to the machine learning problem at hand, ensuring their differentiability and convergence are critical to solving a deep learning problem. There are many ready-made loss functions in tensorflow, and using these as building blocks, we will see how to make arbitrarily complex loss functions. FAQs: Q. Will I need a GPU? A. No. The beauty of tensorflow is that it can seamlessly deploy code to GPUs, without you needing a GPU to develop that code. Q. What is the format of the tutorial? A. Being a tutorial, this session is meant to be highly interactive in nature. It will be a sequence of units where concepts are first explained and then the audience will have to solve exercises in a Jupyter notebook. Q. I don't know anything about neural networks or deep learning. Should I attend this tutorial? A. Absolutely. The focus is on tensors, which are the domain of tensorflow, and not on network layers, which are domain of keras", + "Last Updated": "25 Jun, 2018", + "Prerequisites": " Basic knowledge of Python data structures and NumPy arrays Basic knowledge of linear algebra Elementary vector calculus", + "Section": "Data science", + "Speaker Info": "Jaidev is a data scientist based in New Delhi, India. He specializes in building data-driven products and the tooling around them for a living. His research interests are in signal processing and computational harmonic analysis. He is obsessed with applications of machine learning in personal productivity and recommendation systems. He blogs about these here ", + "Speaker Links": "Twitter GitHub Blo", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Jaidev Deshpande (~jaidev)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tensorflow-101~dB7Ye/", + "title": "Tensorflow 101" + }, + "16": { + "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research\nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", + "Description": "The Python ecosystem is growing and may become the dominant platform for machine learning. The primary rationale for adopting Python for machine learning is because it is a general purpose programming language that we can use both for R&D and in production. In this talk I will discuss 1. Python and its rising use for machine learning, 2. SciPy and the functionality it provides with NumPy, Matplotlib and Pandas.\n3. scikit-learn for machine learning algorithms, TensorFlow and Keras for Deep learning and PyTorch for Natural Language Processing, 4. How to setup your Python ecosystem for machine learning and what versions to use. At the end I will also give case studies on using this Python ecosystem for biomedical applications", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", + "Section": "Data science", + "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", + "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban\nhttp://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban\nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Parthi", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mastering-machine-learning-with-python~azNya/", + "title": "Mastering Machine Learning with Python" + }, + "17": { + "Content URLs": "Will be updated soo", + "Description": "The ELK stack consists of Elasticsearch, Logstash, and Kibana. Although they've all been built to work exceptionally well together, each one is a separate project that is driven by the open-source vendor Elastic\u2014which itself began as an enterprise search platform vendor. It has now become a full-service analytics software company, mainly because of the success of the ELK stack. The session will cover basics of ELK stack for a kickstart", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Passion to Lear", + "Section": "Others", + "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International University", + "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chhavnish Mittal (~chhavnish)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-wih-elk-stack~axNBd/", + "title": "Getting Started wih ELK Stack" + }, + "18": { + "Content URLs": "will update soo", + "Description": "Get to Know Tkinter , pyqt5 and pyqtgraph and how to create a data visualization and control interface for your geeky arduino project in no time. Tkinter is a is the standard Python interface to the Tk GUI toolkit pyqt5 is Python bindings for the Qt cross platform UI and application toolkit pyqtgraph is Scientific Graphics and GUI Library for Python I will show you how to send the commands to Arduino using Python GUI and how parse and create a real-time graphs from Arduino dat", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "You should know how to write mighty Hello World program in Python and Arduin", + "Section": "Embedded python", + "Speaker Info": "I'm just a Tinkerer. Been playing with Python , Arduino and Raspberry Pi from few year", + "Speaker Links": "Blog - My Tinkering with Arduino GitHub linkden simple dem", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Kunchala Anil (~anilkunchalaece)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-python-gui-for-arduino-project~dw88e/", + "title": "Building Python GUI for Arduino Project" + }, + "19": { + "Content URLs": "TB", + "Description": "The focus is more on teaching core concepts to programmers rather than using libraries. More than one neural network will be implemented. An Easy way to learn Machine Learning An interactive way to learn ML. With ML being a leading platform in the market, the workshop introduces to one of the most important fields of Machine Learning that is Deep Neural Networks. Only basic introduction to Mathematics required. Why Python? Python for Machine Learning Machine Learning What is Machine Learning? Why learn Machine Learning? Types of Machine Learning Regression and Classification Supervised and Unsupervised Neural Networks Deep Neural Networks Feed forward Neural Networks Convolutional Neural Networks CNN Recurrent Neural Networks Layers in Neural Networks Neuron Models Perceptron Sigmoid Neuron Binary Threshold Rectifier Stochastic Binary Cost Functions (A Loss or Objective function) Gradient Descent Gradient Boosting Backpropagation Stochastic Gradient Descent Implementing the classic MNIST dataset problem A Neural Network for handwritten digit recognition Classification using individual pixels Image Classification A simple implementation using deeper networks TensorFlow Expanding the Neural Network using Google's Library for Machine Learning Might change to Caffe - nVIDIA's library for Machine Learning Deep Learning A brief introduction to Deep Learning practices Auto Encoders Other areas of Deep Learning (A qualitative study) ", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "User Prerequisites Core Python - lists, dict, string including functions and classes NumPy, SciPy - not necessary but preferred Elementary Calculus - Differentiation and Integration (Understanding qualitatively is enough) Linear Algebra System Requirements 32/64-bit Windows/Linux architecture with at least 2GB RAM Python3 compiler with NumPy, SciPy and TensorFlow library PDF reader Other Requirements but not necessarily needed Anaconda3 (or support for ipynb files, Jupyter preferred) A graphic card", + "Section": "Core python and Standard library", + "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", + "Speaker Links": "GitHub Instagram Emai", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Aniket Chowdhury (~aniket43)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-advent-of-deep-neural-networks-neural-network-implementation-without-ml-libraries-and-extending-them-with-tensorflow~av75b/", + "title": "The Advent of Deep Neural Networks. Neural Network implementation without ML libraries and extending them with Tensorflow." + }, + "20": { + "Content URLs": "Session Content: Introduction to main units of Deep learning Feature engineering techniques for audio data DeepSpeech Architecture Live demo of DeepSpeech Project Common Voice initiative (why and its need) Community Support details Applications of speech recognition Key Takeaways: Unravel the mystery behind the AI which powers speech recognition for services such as Siri, Google Assistance etc Learn about various by which one can contribute to Project DeepSpeech & Common voice project Get introduced to major units of deep learning and state of art DL architectures powering speech to text applications Tags: AI, speech recognition, speech to text, machine learning, Python, tensorflow, deep learning, Voice search Projects links: DeepSpeech : https://github.com/mozilla/DeepSpeech https://arxiv.org/abs/1412.5567 Common voice: https://voice.mozilla.org/ https://voice.mozilla.org/en/data", + "Description": "Pitch: Our voices are no longer a mystery to speech recognition (SR) software, the technology powering these services has amazed the humanity with its ability to understand us. This talk aims to cover the intrinsic details of advanced state of art SR algorithms with live demos of Project DeepSpeech. A research says that \"50% of all searches will be voice searches by 2020\". World\u2019s technology giants have placed big bets with their investments in services providing voice search, personal digital assistant, IoT devices etc. Solving the problem of speech recognition is a herculean task, given the complexity involved with data like the human voice. The talk will cover a brief history of speech recognition algorithms, the challenges associated with building these systems and then explain how one can build advanced speech recognition system using the power of deep learning and for illustration, we will deep dive into Project DeepSpeech. Project DeepSpeech is an open source Speech-To-Text engine developed by Mozilla Research based on Baidu's Deep Speech research paper and implemented using Google's TensorFlow library. Speech recognition is not all about the technology, there's a lot more concerns, challenges around how these AI models are being part of our day to day life , it's biases etc. The bigger question revolves around centralization of these AI services, projects like Common Voice addresses these problems by enabling all to be part of this revolution, a part of the talk will focus on how people need to approach these type of research keeping in mind the community and humanitarian benefits as first priority", + "Last Updated": "25 Jun, 2018", + "Prerequisites": " Basic Python Feel enthusiastic about ML & AI services Interest to learn about speech recognition systems", + "Section": "Data science", + "Speaker Info": "Vigneshwer is an innovative machine learning researcher with an artistic perception of technology and business, having several years of experience in developing robust machine learning solutions for video and text analytical problem statements and have played key roles in analyzing problems, creating hypothesis matrix and delivering novel algorithms and data-driven solutions for many fortune 500 companies. An open Source aficionado, Official Mozilla TechSpeaker and the author of Rust cookbook", + "Speaker Links": "Github | Website | Facebook | Twitter | LinkedIn | Talk", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Vigneshwer Dhinakaran (~dvigneshwer)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-speech-recognition-with-project-deepspeech~erNpe/", + "title": "Demystifying speech recognition with Project DeepSpeech" + }, + "21": { + "Content URLs": "https://github.com/vibrantabhi19/PyConIndia2018 (A Github Link to the slides and the Jupyter Notebooks) https://docs.google.com/presentation/d/1UmT3PbazC6sO_owIeiLNj5G1EdTwrdpS84JWenO-3eE/edit?usp=sharing (Introduction Slide for CNN and PyTorch) Some more slides and notebooks as and when we come up with more ideas to make the workshop interacting and interesting", + "Description": "Just like in our everyday lives, AI and robotics are increasingly a part of our healthcare ecosystem. Currently healthcare is broken; there\u2019s shortage of doctors; poor quality of care. There is a dire need to provide assistance to the whole medical industry to improve healthcare. PyTorch, which is a very popular modular deep learning framework for fast, flexible experimentation is an invaluable resource for such problems. It supports seamless conversion of Numpy arrays into GPU tensors and vice versa. The dynamic computational graph allows to change the network behavior on the fly unlike static graphs and due to Its highly modular nature helps in fast debugging. Unlike other production grade tools, Pytorch helps with lots of Research and Experimentation with novel architectures and is very useful to test ideas a bit more quickly and prototyping. With Medical Imaging being the field most impacted by AI, our goal in this workshop is to give a good head start covering the heuristics of Medical Imaging, the concepts involved in it and how to code your way out. This workshop would be divided into two halfs. First Half: Pytorch Introduction\nDuration: 1 hour 20 minutes\nThe first half would be a gentle introduction to PyTorch framework. We will introduce the audience with the basics of PyTorch. This workshop will cover topics like: What is PyTorch? (Use cases and war stories) Tensor 101 Ndarray/Tensor library Numpy Bridge, Fast CPU to GPU conversion of tensors The automatic differentiation engine or autograd Difference between Static and Dynamic computational graphs Advantages of dynamic computational graph with examples The optimization package Scope of debugging Ecosystem Linear Code flow in Pytorch (One of the core philosophy of PyTorch) Saving and loading models* Deep Learning workflows* Tutorial on Transfer Learning.* Workflows which involve writing custom data-loaders will also be introduced in brief.* A 10 minute coffee/kit-kat break. :-) Second Half: Let\u2019s dive in. Duration: 1 hour 15 minutes. Introduction to Radiology: What is radiology? What do the images look like? How is AI used here? How will AI help improve radiology practice? Liver, Tumor and Vessel Segmentation - setting the context of why it is needed. Challenges faced in solving liver segmentation. How we solved the challenges - edge maps, data imbalance and overall architecture and data used. Hands on with live Liver Segmentation using PyTorch. Challenges faced in vessel segmentation and classification. How we solved the challenges - vesselness filters, overall architecture and data used. Hands on with live Vessel Segmentation using PyTorch. Putting it all together A 15 minutes Q & A session", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Zeal to learn new things would be enough but basic knowledge of Python would be good to go but the following are always encouraged: Basic Knowledge of algebra. Python Libraries such as Numpy. Basic knowledge of working with Neural Network (not a strict requirement as we will be covering most of it). We also encourage the participants to have a look into the following linked talks/videos/literature to get a head start into the topic. The related materials from web for ideas: https://github.com/soumith/talks/blob/master/2017-NIPS/Coding-papers-in-pytorch.pdf https://github.com/soumith/talks/blob/master/2017-GATech-Atlanta/PyTorch-frameworks_overview_deepdive.pdf https://www.youtube.com/watch?v=LEkyvEZoDZg https://www.youtube.com/watch?v=VMcRWYEKmhw https://www.youtube.com/watch?v=Rv9naeLXolY&index=3&list=PLrzfRWNHZPa0gKBEXTJ0gbDu8NsR07KEH https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/01-basics/pytorch_basics/main.p", + "Section": "Data science", + "Speaker Info": "Abhishek Kumar: Deep Learning Engineer, Predible Health, Bangalore. I am presently working as Deep Learning Scientist at Predible Health, here, we have build state of the art segmentation network for liver, tumour and vessel segmentations. I have previously taken workshop at IIT-Bombay Techfest, I have spoken at Shri Mata Vaishno Devi University at their SFD celebrations and at MuPy (Manipal Institute of Technology's annual Python Conference), Kongu University and a few other colleges/Universities. I have been a constant contributor in the open source world and have been attending PyCon and other conferences every year. An athlete, a Real Madrid F.C follower and a part time stand-up comedian (good enough to make you laugh). Aditya Bagari: Final year Undergrad, Indian Institute of Technology, Madras I am a final year Undergraduate student at IIT-Madras doing my Dual-Degree in Engineering Design with specialisation in Bio Medical Sciences. I have been working on Medical Imaging and PyTorch for almost a year and I have been a constant admirer of Open Source Technologies and frameworks. Feel free to drop any suggestions or modifications that you want in this workshop. See you at PyCon", + "Speaker Links": "Abhishek Kumar: Website (A very outdated one), LinkedIn , Medium , Github . Aditya Bagari: LinkedI", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Abhishek Kumar (~vibrantabhi19)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploring-pytorch-for-ai-assistance-in-medical-imaging~bqXpa/", + "title": "Exploring PyTorch for AI assistance in Medical Imaging" + }, + "22": { + "Content URLs": "This talk will be based on my article on Towards Data Science The hands-on examples have also been open-sourced on GitHu", + "Description": "Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. We will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D) using a hands-on approach with Python and popular open-source visualization libraries like matplotlib and seaborn. The talk shall be structured as follows: Motivation for Effective Data Visualization A quick refresher on Data Visualization Brief introduction into python open-source frameworks for visualization pandas matplotlib seaborn bokeh Univariate analysis with hands-on examples Multivariate analysis with hands-on examples Visualizing data in 2, 3, 4, 5 and 6 dimensions Visualizing a combination of numeric and categorical data Strategies for effective data visualization Conclusion", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Basics of Python, data terminology (rows, columns, feature, data points, data types) helps but we will be covering briefly during the session. Hence it's not essential", + "Section": "Data science", + "Speaker Info": "Dipanjan Sarkar is a Data Scientist at Intel, on a mission to make the world more connected and productive. He primarily works on data science, analytics, business intelligence, application development, and building large-scale intelligent systems. He holds a master of technology degree in Information Technology with specializations in Data Science and Software Engineering. He is also an avid supporter of self-learning. Dipanjan has been an analytics practitioner for several years now, specializing in machine learning, natural language processing, statistical methods and deep learning. Having a passion for data science and education, he is a Data Science Mentor at Springboard, helping people up-skill on areas like Data Science and Machine Learning. He also acts as a contributor and editor for Towards Data Science, a leading online journal focusing on Artificial Intelligence and Data Science. Dipanjan has also authored several books on R, Python, Machine Learning, Social Media Analytics, Natural Language Processing & Deep Learning. More about me: LinkedIn: https://www.linkedin.com/in/dipanzan/ GitHub: https://github.com/dipanjan", + "Speaker Links": "LinkedIn: https://www.linkedin.com/in/dipanzan/ Blog Posts: https://towardsdatascience.com/@dipanzan.sarkar GitHub: https://github.com/dipanjanS Featured stories on KDnuggets: https://www.kdnuggets.com/?s=dipanjan+sarkar Recent books:- https://www.springer.com/us/book/9781484223871 https://www.springer.com/us/book/9781484232064 https://www.packtpub.com/big-data-and-business-intelligence/hands-transfer-learning-pytho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Dipanjan Sarkar (~dipanjan)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-art-of-effective-visualization-of-multi-dimensional-data-a-hands-on-approach~ep6Vb/", + "title": "The art of effective visualization of multi-dimensional data - A hands-on approach" + }, + "23": { + "Content URLs": "Will be updated soon", + "Description": "We all(probably) love facial recognition feature isn't it?. We all edit our images before posting it to social media to give a flamboyant touch and its done in too simple steps. Open the editing software, select what you want to configure(filters, Sharpness, etc.) and you're done. Quite easy, right? But what if you know how the back-end of how these softwares run? what if you know the what kind of codes make your camera detect objects? Well with OpenCV and python its simpler than you can imagine! My talk will be about OpenCV with Python. OpenCV is an acronym for Open Source Computer Vision Library . Its a library used for image processing. The code can be written in C++, Java or Python but since we all love Python, we'll use that. We will be using ' cv2 ' library for all the image processing and detection. My talk will feature: How images are stored in computer and how each pixels store image. Different types of Colour Bands and the role of Colour Bands in forming an image. Editing images with cv2 library in python. Blurring, Sharpening, Greyscaling, and other uses of image kernels. Object and Face Detection and live object Tracking using python and OpenCV.", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Basic knowledge of Python and basic mathematics(Class 10th)", + "Section": "Others", + "Speaker Info": "I am undergraduate final year student, CSE branch from REVA University. I am a passionate programmer. I am an IEEE Volunteer. I was the Chair of IEEE Computer Society Chapter REVA University. Right now i am Student Branch Coordinator at IEEE Region 10(Asia/Pacific).\nCurrently I am interning at Valtech India as a Java Developer.\nI have taught python to more than 150 students in my college by taking sessions. I have taught OpenCV to more than 80 students.\nI have started loving python from 2016 when I read the book 'learn python the hard way by Zed Shaw'. My almost all the undergraduate projects are based on python", + "Speaker Links": "Blog: bit.ly/itsrohanvj\nGithub: itsrohanvj\nLinkedin: www.linkedin.com/itsrohanv", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Rohan Vijay (~rohan96)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/computer-vision-with-python~bo9Xe/", + "title": "Computer Vision with Python." + }, + "24": { + "Content URLs": "https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology I will update slides and code soo", + "Description": "Central dogma of life or of molecular biology is the core molecular process which keeps us alive! It's the machinery which converts DNA to mRNA to protein to active protein which eventually gets distributed in the body. DNA -> mRNA -> Protein Through this talk, I'll give a live demonstration of the processes by which this mechanism takes place and unravel its mysteries using Python! I'll explain how python is helping us simulating biological processes in the most elegant manner. How is DNA transcripted to mRNA? How is mRNA translated to protein? These are some of the questions I\u2019ll answer by simulating the actual processes using Python. By solving small challenges involved with this mechanism, I\u2019ll tell the audience, why Python is the best computer language for a bioinformatician and how great python libraries can make the life even easier especially BioPython. The challenges I am talking about are real bioinformatics problem, although basic, including translation, transcription and reverse complement. In the end, I\u2019ll brief some huge accomplishments of bioinformatics and computational biology and how we can contribute to this sector which has a promising future as well. Contents of the talk: Introduction : Introduction to gene and how we (computer scientists)\n recognize a gene Central Dogma of Life : a Live action of how a gene\n is converted to RNA and then to protein using Python. Why Python is best for biology? : Bioinformatics can be best studied using Python Impact of this sector : Accomplishments of Computational Biology and\n bioinformatics Conclusion : Possible ways in which we can contribute. Q & A session : Questions and answers session. Outcome: After the talk, the audience will have an understanding of how we function at a cellular level, how proteins are formed in our body and how can we simulate other biological processes using Python and will recognize the power of Python which can be harnessed in biology as well as other sciences. They will also have a basic introduction of BioPython", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Curiosity to learn :", + "Section": "Others", + "Speaker Info": "I have completed my B.Tech in Biotechnology this year from IIT Roorkee. I have interests in Web applications, Artificial Intelligence and Computational Biology. I have worked a couple of years in Computational Biology and Translational Bioinformatics Lab at my Institute and currently a Google Summer of Code student working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API ", + "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "hulksmash (~someshchaturvedi)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/simulating-central-dogma-of-life-using-python~enV7e/", + "title": "Simulating central dogma of life using Python" + }, + "25": { + "Content URLs": "Will be updated soon", + "Description": "Get to know Flask and how to create beautiful REST APIs in no time. Fall in love with Flask and learn the best practices for building APis in a hurry. Flask is a lightweight micro-framework for Python. Its simplicity and elasticity make it the best choice for building APIs in no time. In my talk, I will cover the basics concepts of Flask and Requests. I will show the tools that can automate the most common tasks in API development and will share the design patterns to avoid common pitfalls. Some of the specific tools and topics that I'll cover: Flask-Restplus, SQLAlchemy, request lifecycles, REST + CRUD API patterns, Flask architecture", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "No previous experience in Flask is needed", + "Section": "Web development", + "Speaker Info": "Sara is a seasoned software engineer and the Co-Founder of Gradient.gt, a data science and machine learning consulting company based in Guatemala, where she works crafting web applications and solutions to companies in need. When she is not coding, she spends her free time baking sweet treats and watching Rick and Morty", + "Speaker Links": "www.sara-codes.com Linkedin.com/in/sarairisgarcia Gradient G", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "montjoile", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-apis-in-no-time-using-flask~bmVGd/", + "title": "Designing APIs in no time using Flask" + }, + "26": { + "Description": "A framework which will give a drag and drop web development option using Django as the backend", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "Python and basics of Djang", + "Section": "Web development", + "Speaker Info": "Sanket Sarkar [ Microsoft Technology Associate {Introduction to Python Programming}]\nA final Year Student of B.Tech", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Sanket Sarkar (~sanket78)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/drag-and-drop-framework-for-django~elVMb/", + "title": "Drag and Drop Framework for DJANGO" + }, + "27": { + "Content URLs": "Content will be updated soon", + "Description": "You all would have often faced the issue of not being able to recognize handwriting, either it is a Doctor's prescription or sometimes, even your friend's assignment. This problem might have caused some harm, maybe due to the delay in submitting the assignment or seeking chemists' that can recognize that particular handwriting.\nTherefore, in this talk, we will be focusing on how Python and Data Science can be used to recognize handwritten digits and character which will ease out the pain of recognizing haphazard writings. Topics to be covered: What is Handwritten Digit and Character Recognition? Why we need it and uses of it? How Python can help in achieving this? Future Scope", + "Last Updated": "24 Jun, 2018", + "Prerequisites": " Basics of Python Basics of Data Science", + "Section": "Data science", + "Speaker Info": "I'm Prashant Pandey. I've deep interest in Data Science, especially in Python. I've been working in the domain of Data Science since one year now, and have completed several projects. Presently, I'm working on Handwritten Digit and Character Recognition", + "Speaker Links": "https://github.com/Prashantpandey2398", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Prashantpandey2398", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handwritten-digit-and-character-recognition-using-python~bkV6a/", + "title": "Handwritten Digit and Character Recognition using Python" + }, + "28": { + "Content URLs": "Will be updated soon", + "Description": "Your machine learning models might be intelligent enough to make predictions but may lack the wisdom to prevent bias. They may be as vulnerable as a child getting influenced by inappropriate sources encouraging racism, sexism or any unintended prejudice. Models learn exactly what they are taught. The more biased your data is, the more biased is your model. For instance, a text model by Google says how \u201cEngineer is to a Man\u201d is the same as \u201cHousewife to a Woman\u201d. This shows how incidental data can lead to unintended bias. Machines are given the power to judge so there is a need for us to ensure we prevent biased/unfair judgements. In this talk, we are going to discuss What is Machine Learning bias? How is it caused? Different ways to identify bias? Techniques to prevent bias One Famous example of bias:", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "Knowledge in python3 and pandas Knowledge of building machine learning models Little idea on deep learnin", + "Section": "Others", + "Speaker Info": "I am a software developer, speaker, opensource contributor and a wannabe developer evangelist. I love everything python and NLP(Natural Language Processing) research. I have been volunteering with various local startup and tech communities to promote entrepreneurship and technology. I work at mroads and help them develop better a.i", + "Speaker Links": "Links: Linkedin: https://www.linkedin.com/in/poornagurram/ Github: https://github.com/poornagurram StackOverflow: https://stackoverflow.com/users/5443381/poorna-prudhv", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "G POORNA PRUDHVI (~poornagurram)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-fair-machine-learning-systems~egVkd/", + "title": "Building fair machine learning systems" + }, + "29": { + "Content URLs": "Will come soo", + "Description": "Blockchain Technology is the talk of the town. Almost all articles published have some relation to Blockchain concepts.\nWhile Public Networks usually pertain to Cryptocurrency, Private networks pertain to business-level implementations. In order to develop with this technology as our base, it is important to understand the key features, as well as make implementations using the existing skillset, which happens to be the Python Programming Language. The talk will feature Complete in-depth explanation of Blockchain technology, and the working of Bitcoin as an example. Developing your personal Cryptocurrency with Python Introduction to Hyperledger Sawtooth, and understanding how and why to use Python with it. Best practices to consider in mind while developing for a blockchain. By the end of the talk, you will be able to Explain the concepts of Cryptocurrency and Blockchain technically. Understand Python's role in one of the most popular frameworks created by Intel, and implement your own ideas with the same.", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "General Pytho", + "Section": "Others", + "Speaker Info": "Hi, I'm Priyansh! Here's a quick bio. CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms. Technical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", + "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Priyansh Jain (~Presto412)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-with-python~e0yLa/", + "title": "Blockchain with Python!" + }, + "30": { + "Content URLs": "Will be updated soo", + "Description": "Automation is something we all desire, may it be the twitter feed of a celebrity, or perhaps the latest price of bitcoin. For students, it can range from tracking assignment deadlines or message updates. For developers, it can be the tracking of an important issue or auto merging of pull requests. For management, deadlines for a work assignment or a due presentation. With Python, everything listed above is possible. The talk will feature how to start automating the small things that can prove highly productive. We will use simple libraries first, and this will be followed by using fully headless browsers like selenium and understanding the concepts of web crawling. Integration of API services like Google Calendar and Google keep, to sync all the data collected will be demonstrated. Finally, we will deep dive into an interesting open-source project I made, and how I have automated most of my college work", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "Basic understanding of REST APIs and Frameworks, and Beginner-Intermediate Level of Python Programmin", + "Section": "Developer tools and Automation", + "Speaker Info": "CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms.\nTechnical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", + "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Priyansh Jain (~Presto412)", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-your-life-with-python~b873a/", + "title": "Automating your life with Python" + }, + "31": { + "Content URLs": "Will be updated soon", + "Description": "Dash is a Python framework for building analytical web applications, built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs to your analytical Python code. The workshop will include building interactive dashboard with Dash framework. How to visualise the data purely in python will be the key take away", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "Python 3 Pip3", + "Section": "Web development", + "Speaker Info": "I am software engineer working at Juxt Smartmandate, who believes in creating products using open source technology", + "Speaker Links": "https://github.com/kapoorabhish https://www.linkedin.com/in/abhishek-kapoor-4b7b9295", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "kapoorabhish", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-interactive-dashboard-using-plotly-dash~e771e/", + "title": "Building interactive dashboard using Plotly Dash." + }, + "32": { + "Content URLs": "A sample code can be found here :\nhttps://github.com/KaustabhGanguly/Recurrent-Neural-Networks-to-predict-Google-Stock-Pric", + "Description": "I will show you how to predict google stock price with the help of Deep Learning and Data Science .\nThe predictions are not realistic as stock prices are very stochastic in nature and it's not possible till now to accurately predict it .\nAs I'll only have 30 mins to talk , I can't train the data and show you as it'll take several hours for the model to train on google collab . So , I will show you : Basics of Recurrent Neural Networks and LSTM Basics of pytorch Coding line by line with describing every words Then starting to train the model and prematurely closing it and move forward to show you the results that I'll bring with me after training .", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "You should have basic pyTorch understanding but I'll guide you anyways through the basics .\nBasic understanding of LSTM or RNN is preferred but not required ", + "Section": "Data science", + "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India . I'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 . I'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", + "Speaker Links": "Follow me on github : github.com/kaustabhganguly Connect with me on linkedin : linkedin.com/in/kaustab", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Kaustabh Ganguly (~KaustabhGanguly)", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-stock-price-time-series-prediction-with-rnnlstm-using-pytorch-from-scratch~b67Rd/", + "title": "Google Stock Price Time Series Prediction with RNN(LSTM) using pytorch from Scratch" + }, + "33": { + "Content URLs": "The code is in this repo :\nhttps://github.com/KaustabhGanguly/Smile-Detector :", + "Description": "In this era of deep learning and machine learning , the beginners may get lost sometimes , as there is a steep learning curve involved with the process .\nWhen I was starting out on machine learning , I always wanted to get my hands dirty in the advanced stuffs but It was hard for me and there was no guidance .\nSo , in this talk and coding session I will guide you through how you can build your own facial recognition system and implement a smile detection very quickly and easily with the power of openCV and python . It will take 10 mins and any beginner with basic knowledge of python can grasp the concepts easily .\nI will not use convNet or anything ,but a model called HaarCascades . It's an old mathematical model which was/is mainly used where deep learning is not an option . I will guide you through the basics and tell you some quick things and facts and we will enjoy a lot . See you on pyCon 2018 ! kindly upvote if you want some quality 10 mins learning something new ", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "Basic Python knowledg", + "Section": "Data science", + "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India .\nI'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 .\nI'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", + "Speaker Links": "Follow me on github :\ngithub.com/kaustabhganguly\nConnect with me on linkedin :\nlinkedin.com/in/kaustab", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kaustabh Ganguly (~KaustabhGanguly)", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quick-and-easy-implementation-of-smile-detector-on-your-webcam-using-python-and-opencv-from-scratch-without-any-neural-network-and-for-beginners~e5E8e/", + "title": "Quick and easy implementation of Smile Detector on your Webcam using python and openCV from Scratch without any Neural Network and for beginners ." + }, + "34": { + "Content URLs": " Apache Beam : https://beam.apache.org/ Apache Beam Python SDK : https://beam.apache.org/documentation/sdks/pydoc/2.4.0", + "Description": "Data together with 3Vs characteristic, volume, variety and velocity is labelled as Big Data. Big Data and parallel processing have been hot topics since Google\u2019s paper on MapReduce and till today the era of different runners like Apache Spark, Google Cloud Dataflow etc. Apache Beam is a unified big data processing paradigm which enables the user to run batch and streaming data processing jobs on multiple execution engines like Apache Spark, Apache Flink, Google Cloud Dataflow etc. *Objective of the talk* : Overview of Apache Beam Python SDK Core SDK constructs like Pipeline , PTransform , PCollection etc. Creating custom DoFns and composite Transforms Creating a Pipeline with customizable options Running a pipeline on different runners like DirectRunner , DataflowRunner etc Unit testing a Pipeline with asserts Demo: StreamingWordCount example using Google Cloud Dataflow Q&A", + "Last Updated": "22 Jun, 2018", + "Prerequisites": " A little knowledge about Python 2.7 Enthusiasm for Parallel Data Processing Motivation to play with lots of Data", + "Section": "Others", + "Speaker Info": "I am Mukul Arora, working as a Software Engineer in Schlumberger India Technology Centre. I graduated from Delhi Technology University in May 2017. I am a Data Science and Big Data practitioner and have been highly involved in solving Computer Vision and Medical Imaging problems using Deep Learning Techniques. Currently, I am exploring efficient ways to solve Big Data problems on Cloud.\nI am an avid cricket fan and love to write poems", + "Speaker Links": "LinkedIn : https://www.linkedin.com/in/mukularoradce/ Github : https://github.com/codemukul95 YourQuote : https://www.yourquote.in/mukul-arora-ffds/quotes", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "mukul arora (~mukul11)", + "created_on": "22 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unified-and-portable-parallel-data-processing-using-apache-beam~b4Dxb/", + "title": "Unified and Portable Parallel Data Processing using Apache Beam" + }, + "35": { + "Content URLs": "A similar version of this talk was recently delivered at Pycon APAC2018 (Singapore). Slide deck: https://goo.gl/xRRdKt An attendee's review of my talk: https://tryolabs.com/blog/pycon-apac-2018-singapore-experience", + "Description": "Offensive / abusive content is a major issue for social-media and digital interaction platforms. In some jurisdictions (Eg: Europe), platform providers are required by law to remove such content within 24 hours of posting or risk hefty fines (upto \u20ac50M in Germany). In order to meet the governance mandate, we need to have systems in place that can automatically detect abusive content at scale. This talk is based on my practical experience of building an automated solution to solve this problem. This talk begins with discussing some of the approaches currently being employed for offensive content detection at scale: word filtering, rule-based systems and actual human annotation. The former two are restricted by the following: Offensive content is context specific. A given word (f ck) can be used in both positive (that\u2019s f cking awesome) and negative (that\u2019s f*cking terrible) contexts. Robustness to spelling variations (The word \u2018shit\u2019 can be spelt as \u2018sh*t\u2019, \u2018sh!t\u2019, etc) Failure to detect content that is offensive in idea but uses non-offensive words. (Eg: your mom is a fat cow, X people are inferior, etc) Manual human annotation is notoriously hard (ask Google!) and expensive to scale. The talk presents a Deep neural network based approach to overcome the previously mentioned limitations. It introduces and discusses the building blocks of model architecture (deep convolutional networks, word embeddings, etc). The second half of the talk focuses on implementing the above model to solve the problem at scale as a RESTful micro-service using python, Django, Tensorflow and Docker. This architecture can also be used to implement other text classification systems as well (eg: user intent detection systems, topic-of-discussion classifiers, etc.), making the talk relevant for a wider user base. Attendees will: Gain insights into building deep learning based text-classification systems that can scale Learn the nitty gritties of the offensive content detection and text classification Learn about the basic concepts of Deep Learning and NLP (convolutional neural nets, multi-layer perceptron, word embeddings, etc.) Understand the scientific and software challenges involved in text classification and learn to overcome them Be able to apply the learnings from here to other text classification problems as well", + "Last Updated": "22 Jun, 2018", + "Prerequisites": "Just bring an open mind ;", + "Section": "Data science", + "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. He is currently employed as a Machine Learning Engineer. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", + "Speaker Links": "https://www.linkedin.com/in/alizishaan-khatri-32a2063", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Alizishaan Khatri (~alizishaan)", + "created_on": "22 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/detecting-offensive-messages-using-deep-learning-a-micro-service-based-approach~e30Ra/", + "title": "Detecting offensive messages using Deep Learning: A micro-service based approach" + }, + "36": { + "Content URLs": "Git Hub Repository : click here Demo: click her", + "Description": "The workshop will be escalating from a very beginner level and so I only require you to know the basics of python and if possible a glance of the OpenCV library. The workshop will be proceeding accordingly : Basics of Image processing. Image classification using Deep Learning ( CNN ). Deploying your own Emotion recognizer. ", + "Last Updated": "21 Jun, 2018", + "Prerequisites": " Basics of Python Please download and install the following libraries in beforehand : Pytorch OpenCV Fastai numpy matplotlib dlib imutilis We will be using all of the mentioned libraries to make the goings of the workshop easy to understand and implement. Additional Files : Please download from her", + "Section": "Data science", + "Speaker Info": "I am shaaran and my main aim is to take technology to everyone and spread my knowledge as far as I can, in a journey to fulfill my dreams I have went to many institutions and have conducted workshops and talks in Robotics and AI, I am currently a second-year student at VIT University and also a part of many organizations like Google Developers Group, RoboVITics and more , I have interned at Toshiba recently and have made a new AHU control system using IOT and AI", + "Speaker Links": "Github: click here Linkedin: click her", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "shaaran Lakshminarayanan (~devshaaran)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-your-own-emotion-recognizer-from-scratch~b2rzb/", + "title": "Building your own Emotion recognizer from Scratch !" + }, + "37": { + "Content URLs": "https://github.com/someshchaturvedi/customizable-django-profiler Will be updating slides soon", + "Description": "Django, as we all know, is an excellent framework for building high stable, scalable, extensible web apps. Django framework operates around middlewares. Do we really understand how a middleware works? What happens when the request comes in and response goes out? Which middleware is used for what purposes? Why is the order of middleware stack important? How can we implement a custom middleware? Benefits and complications of implementing custom middlewares My talk will cover all the above questions along with a live demo of a profiling middleware ( customizable-django-profiler ) which is used to track down the function calls associated with an API call taking more time for execution. Contents of the talk: Introduction : Introduction to middleware. Middleware architecture : I will talk about the middleware architectural design. It\u2019s basics and various use cases Implementation of middleware in Django : Explain how the request-response cycle works along with targeting above mentioned questions on the go. Live demo : I will demo the development of a simple custom middleware which can be used for profiling requests. Conclusion : Possible use cases for Django middlewares. Q & A session : Questions and answers session. In the end, the audience will have an understanding of Django middleware stack, middleware architecture, request-response cycle in Django and will be able to develop their own middleware for Django from scratch", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Basics of Python and Djang", + "Section": "Web development", + "Speaker Info": "I am recently graduated from IIT Roorkee. I have been working on web applications (especially Django for more than 3 years now). Selected for Google Summer of Code this year and working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API . My areas of interest are Web Applications, Artificial Intelligence and Computational Biology", + "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "hulksmash (~someshchaturvedi)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-django-middleware-stack-with-a-live-demo~e1qme/", + "title": "Understanding Django middleware stack with a live demo" + }, + "38": { + "Description": "Data proliferation is putting pressures on business leaders to become data-driven. Although, leaders have to rely on data analysts to run those queries and get insights out from data warehouses. Its a common principle-agent problem wherein data analysts only ask questions from data which they are directed to ask, but its never a one-way street. One has to flirt with data for a long time to get to know it and leaders get stuck in the loop of data analyst direction as leaders are not equipped with or don't have time to write SQL queries. This calls for a natural language query wherein a business leader can ask a question in simple plain English and data is spitting out either in a table or graph. This session is guided towards how Innovaccer has solved this problem and provides an architecture, knowledge base building, and natural language processing guidance to build one on your own. The session will also emphasize on the fact that accuracy of such a software will be very poor if it is industry agnostic as SalesForce and ThoughtSpot have tried in the past. Thus, one has to tame it to their own business context or vertical", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Basics knowledge on natural language processing, not even how to code it, but what are its basic components. https://www.nltk.org", + "Section": "Data science", + "Speaker Info": "Kanav Hasija is Co-Founder and Chief Product Officer at Innovaccer. He has developed a healthcare data platform with his team which helps connect to various healthcare IT systems to get a longitudinal view of the patient record and turn it into analytical insights on risk, cost, and utilization behaviour of patient to act on them and treat them before they get sick to reduce the cost of healthcare. The platform today has more than 10 million lives on the platform and an estimated $1 Billion has been saved till date in US healthcare costs while keeping people healthy with a quality of care bump of 15%. He is a coder and mathematics enthusiast since the age of 10, completed his bachelor in engineering from IIT Kharagpur and pursued higher studies in Intellectual Property Law from UNH Law in the US. He is recipient of various awards like Samsung-Stanford Patent Prize, Honorable Mention for Excellence in Technology, Best Graduate Student Award, and is also an author in a few publications like IEEE. Harshil Rastogi is a software development engineer at Innovaccer. He has worked on various enterprise-grade software components in the fields of data management, data transformation, and natural language processing", + "Speaker Links": "https://www.linkedin.com/in/kanavhasija/ https://www.linkedin.com/in/harshil-rastogi-3a754b65", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Kanav Hasija (~kanav)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bringing-analytics-in-hands-of-leaders-natural-language-query-in-python~bYx2a/", + "title": "Bringing analytics in hands of leaders: Natural Language Query in Python" + }, + "39": { + "Content URLs": "Speaker will focus on when and how to use design patterns, rather than what are the design patterns available. Github repository for the talk", + "Description": "Having less time to design software and solving the design problems correctly, to create robust , modular and highly maintainable code is current challenge.\nMight be, you are aware of some of the design patterns but it will never solve your problems until you have deep understanding on the problem and right place to use design pattern. If you think, you need to design a very unique architecture, then may be you are missing powerful available design pattern that can provide you generic solution template. Let's learn ( and become expert), to speed up development process; guessing issues that can come up later development stages and selecting the right design pattern in the right stage of the software development in Python", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Coders and programmers who want to learn about software design and architecture", + "Section": "Others", + "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", + "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Shekhar Prasad Rajak (~Shekharrajak)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/i-would-have-known-this-software-design-techniques-before~eXwgd/", + "title": "I would have known, this software design techniques before.." + }, + "40": { + "Description": "for students,\nunderstanding data analysis with pandas, using ipython shell or terminal and jupyter notebooks", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "understanding of python scripts", + "Section": "Data science", + "Speaker Info": "I'm a 3rd year B.tech(information science) student from Bangalore, Karnataka", + "Speaker Links": "https://github.com/pandyamaru", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Marut Pandya (~pandyamarut)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-with-pandas~bWvxa/", + "title": "Data analysis with Pandas" + }, + "41": { + "Content URLs": "Will be updated soon", + "Description": "Talk Summary :- Recently, there is a boom in concept of face recognition system with the introduction of Face ID by Apple in their iPhone X mobile phones. This was also incorporated by OnePlus for their mobile phones too. The most notable use of this technology is at Baidu, an internet company, are using face recognition instead of ID cards to allow their employees to enter their offices. Another place where this technology is prominently seen is in auto photo and video tagging feature of Facebook. In this talk we will build a Facial Recognition program using python library \u201cface_recognition\u201d and then we will dive deep in the behind the scenes action of this library and will try to build a One Shot Learning face recognition model using PyTorch. We will be implementing a Siamese neural network on AT&T Laboratories Cambridge dataset. We will also cover the basics of this neural network, triple loss function and and will discuss the reason for choosing this architecture. I will explain how the network models a relation between two images and relates them. Outcome of this Talk :- Attendees will be able to possess the power to implement state of the art Facial Recognition program in a few minutes. They will also get to know how facial recognition works when we have very small dataset. They will be able to make a state of the art One Shot Learning face recognition based on Siamese Network (the working force of face_recognition and implementation of Google\u2019s FaceNet). Agenda :- Introduction to Face Recognition [2 mins] Introduction of python library \u201cface_recognition\u201d [1 min] Building a face recognition program using \u201cface_recognition\u201d library\n (possible live demo of the output) [6 min] How \u201cface_recognition\u201d encodes faces [2 min] Introduction of Triplet Loss and Siamese Network and reason to choose one shot learning (which is used to\n encode faces) [5 min] Implementation of Siamese Network using PyTorch on AT&T Laboratories\n Cambridge dataset and its results [10 min] Q&A Session [3 min]", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Basic Knowledge of Machine Learning and Neural Networks Love for Pytho", + "Section": "Data science", + "Speaker Info": "Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", + "Speaker Links": "Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Saurabh Ghanekar (~saurabh29)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-state-of-the-art-facial-recognition~eVrXe/", + "title": "Understanding State of the Art Facial Recognition" + }, + "42": { + "Content URLs": "Github repository links will be updated soon", + "Description": "In this talk, I am going to talk about advanced concepts of Python related to Caching. A cache can be easily understood as a saved answer to a question. Caching can speed up an application if a computationally complex question is asked frequently. Instead of the computing the answer over and over, we can use the previously cached answer. Caching is an important component while scaling applications which are to be used by many users. It solves various problems related to cost and latency. Usually it takes more time to retrieve data from DB rather than cache. Using a cache to avoid recomputing data or accessing a slow database provides us with a great performance boost. I will describe in depth the different methods of Caching, their pros and cons. This talk will help developers focus on their code before scaling their applications. It will provide immense performance improvements with this simple concept. Outcomes: The novice audience will be able to understand basic Caching Mechanisms. They will be able to utiilize their knowledge which will serve pivotal while scaling applications Contents to be covered in talk: Local Caching: What is it, how to do it, example, built-in Python libraries: (using cachetools ), advantages, dis-advantages Memoization: What is it, pseudo-code algorithm, implementation using example, built-in Python libraries: (using lru_cache ), advantages, dis-advantages Distributed Caching: What is it, techniques: (using memcached , using pymemcache ) Agenda: Initial 10 minutes: Introduction to Caching and its various techniques. 10 - 20 minutes: Examples and code walk through for various techniques. 20 - 25 minutes: Comparative analysis of how caching is better than non-scaled applications. 25 - 30 minutes: Q&A session", + "Last Updated": "19 Jun, 2018", + "Prerequisites": " Basics of Python", + "Section": "Core python and Standard library", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-caching-in-python~aQm9a/", + "title": "Understanding Caching in Python" + }, + "43": { + "Content URLs": "Will be updated soon", + "Description": "Talk Summary: Bitcoin has become so mainstream these days. It unveiled the importance of decentralization. But how does Bitcoin work? It\u2019s because of its core technology called Blockchain. After the Internet, Blockchain technology is regarded as the next big revolution. This talk gives a hands-on demonstration of how Blockchain technology works by building a toy version from scratch. Outcomes: After this talk the audience should be able to understand the basic working principles of bitcoin. They will be able to leverage their knowledge as a starting point of open-source contributions to projects like Ethereum. This demonstration will consider three important features of Blockchain Technology. All these features are essential to blockchain technology and we will be building a minimal version in Python. Agenda: 0 - 5 mins:\n Blockchains are secure because they use SHA256 or SHA512 algorithm for cryptography. I will describe the logic behind these hashing algorithms and give some computational facts about them. 5 - 10 mins: \n I will use the Python library called \u2018hashlib\u2019 to implement the SHA256 algorithm in Python. This makes us to convert data into SHA256 hashes. 10 - 15 mins:\n The SHA256 algorithm is used to convert all the transactions and their details into a single hash. Once the everything is converted into a hash, this hash must be stored for future usage. After a new transaction is approved, this new transaction and its details are again converted into a new hash along with the previous hash. I will demonstrate the process of storing the hash and using it again for a new transaction. 15 - 20 mins:\n Here I will explain a basic working principle of blockchains and how linking the previous transactions with the new one helps in the their security. The hashes stored are called blocks and the process of liking the previous hash the new hash makes a chain like connection thus forming a Hyperledger. 20 - 25 mins:\n Later in the process of mining will be explained using the variable quantity called Nonce. This explains why bitcoin miners need high computation power to do Proof-of-Work. \nI will also cover a variety of essential terms and concepts through the course of the talk which haven\u2019t been detailed in the agenda. Also, I will use python module called 'TkInter' to build a basic GUI for our blockchain. Last 5 mins:\n Questions and further reading + code sharin", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "Love for Python and acquaintance with its libraries", + "Section": "Core python and Standard library", + "Speaker Info": "I am Koushik, a Computer Science sophomore whose research interests lie in decentralization and cryptocurrencies, occasionally working on deep learning projects. As a member of the Next Tech Lab, a QS-Wharton award-winning student-run lab, I work in the Satoshi research group for blockchain technology. I also regularly participate and give talks in paper-reading groups and meetups like PyData", + "Speaker Links": "Visit my profile on LinkedI", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "KOUSHIK BHARGAV M M Srinivas (~koushik_bhargav_m)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchains-from-scratch~dPl4d/", + "title": "Understanding blockchains from scratch!" + }, + "44": { + "Description": "With examples build the concept of creating a language model using text data", + "Last Updated": "19 Jun, 2018", + "Section": "Data science", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "divya chowdhary (~divya69)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~aOkra/", + "title": "Language Model (Text Analysis) using Python from scratch" + }, + "45": { + "Description": "Abstract: Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. The Big Question: \"Is everything Perfect in AWS Lambda?\" .... Well it depends on how you use it and this is what I will cover in my Talk. Note: This Talk will have some code references using PYTHON Outline: What will you learn from this session/talk: What are Lambda Functions . What are the different features of Lambda Functions. The famous Lambda Timeout . The Deployment and Resource Limits . The Cold Start issue and its workarounds. The Cost Factor Why do you need to know this: Helps develop decision making in the project design architecture The Case Study: Case Study in which you should/should not use Lambda Functions. Real Life project experience: The hidden learning with an on job project on the limitations to Lambda Function. Q&A ", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "Python: Basics of Serverless Computing Basic of Python Programming Basics of Python Libraries Usages (Imports)", + "Section": "Others", + "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", + "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Ritu Mehra (~ritu86)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-lambda-with-python-dos-and-donts~dNjvd/", + "title": "AWS Lambda with Python : Do's and Dont's" + }, + "46": { + "Content URLs": "https://docs.openstack.org/infra/jenkins-job-builder", + "Description": "Jenkins job builder is an openstack project used for automation and reusing of templates in yaml and json to make jobs and subscribe them to Jenkins. People who like to save time on tedious details can use this open source software and live there life a little better", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "Jenkins( a little bit )\nPython\nPip\nRelated libraries like PyYAML, Jinja etc", + "Section": "Developer tools and Automation", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Himanshu Chhabra (~himanshu87)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jenkins-job-builder-automating-jobs~aMgGd/", + "title": "Jenkins job builder - automating jobs" + }, + "47": { + "Content URLs": "Coming soon", + "Description": "Do you know, your favorite superheroes in Avengers , cute characters of Kung Fu Panda and the epic wars of Baahubali were brought to screen with the help of python ? If you are into gaming , you need to thank python for the characters you have played and the world you have explored. Even the next generation technologies like AR and VR use python to deliver their magic to you in new formats. It won't be a overstatement if we say python is the backbone of the animation Industry In this talk we go behind the scenes and see how our favorite programming language is used in the animation industry, why it plays a huge role and the kind of applications built with it", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "A bit of curiosity and interest in learning about usage of python in various industries, usually less represented in the python community", + "Section": "Others", + "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", + "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "sreenivas alapati (~cg-cnu)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/amazing-world-of-animation-powered-by-python~dLDrd/", + "title": "Amazing world of animation - powered by python" + }, + "48": { + "Content URLs": "Coming Soo", + "Description": "It's really hard to escape the 3D buzzword. You find it used in all sorts of places, right from the movies you watch, Games you play, 3D printing , webgl graphics in the browser and VR , AR applications. In this workshop we are going to cover the basics of 3D and do a hands on session on creating 3D Art using a professional open source application called Blender . Of course, python is a major part of blender and we will put your python skills to some good use. What is this workshop NOT about : This is not one of your boring programming workshops. We are not going to try improve your python knowledge ten folds in a matter of 2 hours. What is this workshop about : Come to this workshop if you want to be a kid again and have fun creating art in 3D using Blender and Python !!! Who am I : Hello, Sreenivas here! I am a 3D artist turned programmer. I work in the animation and VFX Industry and battle production issues with the power of python. I love art, technology and excited about combining both. I support open source by evangelizing Blender and Krita . Who are you : You are a person with an open mind, bitten by the curiosity bug and intrigued by how 3D Art is made. You have at least basic knowledge of python and ready to use your super powers to create 3D Art. Takeaway : By the end of the session\u2026 You will know a broad overview of 3D Art . Have a working knowledge of the professional open source 3D application, Blender . Get a deeper understanding of the workflow for creating 3D art. Use your python skills in the process of creating 3D Art.", + "Last Updated": "19 Jun, 2018", + "Prerequisites": " Laptop with a decent GPU (any modern laptop) A mouse with a middle click button (scroll which is clickable) Download and install Blender from https://www.blender.org/download/", + "Section": "Others", + "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", + "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "sreenivas alapati (~cg-cnu)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3d-art-using-blender-and-python~aKBxe/", + "title": "Creating 3D Art using Blender and Python" + }, + "49": { + "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. \nThe website for the workshop at PyCon India 2015 is here . \nYou can find the introduction slides here , the sphinx tutorial here and the exercises in form of IPython notebooks. Note: that the notebooks are hosted statically, you can download from here and run locally to have an interactive session", + "Description": "SymPy is a Python library for symbolic mathematics. It aims to be an alternative to systems such as Mathematica or Maple while keeping the code as simple as possible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.\nThe talk will highlight the following: SymPy, what it is and how it is different from others. What is symbolic computation and how SymPy achieves it. Power of SymPy: Symbolic manipulations Equation solving Calculus Linear Algebra ", + "Last Updated": "18 Jun, 2018", + "Prerequisites": "Basic mathematics, just enough to appreciate the manipulation done by the computer algebra system and Python. No prior knowledge of SymPy or other Python libraries is required", + "Section": "Data science", + "Speaker Info": "SymPy India developers will be conducting the talk: Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers module", + "Speaker Links": " Resource repository: https://github.com/sidhantnagpal/pycon-sympy SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://www.youtube.com/watch?v=5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://www.youtube.com/watch?v=nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://www.youtube.com/watch?v=AqnpuGbM6-Q SymPy Tutorial, SciPy 2014: https://www.youtube.com/watch?v=Lgp442bibDM SymPy Tutorial, SciPy 2013: https://www.youtube.com/watch?v=dAgShwIx72c", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Yathartha Joshi (~Yathartha22)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-sympy~dGxJe/", + "title": "Symbolic Computation with SymPy" + }, + "50": { + "Content URLs": "Will share the Slides post my Talk through a proper channel", + "Description": "Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. Note: In this workshop all the implementation will be done using PYTHON Session Takeaways: How to use different features of AWS to create your Serverless Application. What is Serverless Computing and how \"Functions as a Service\" is a revolutionary way to develop applications. Understand AWS Lambda Functions, the FaaS offering on Amazon Web Services. Understanding of the AWS services - Lambda, S3, EC2, CloudWatch, API Gateway, RDS, IAM How to access the AWS services using Python libraries in the Lambda Function. Hands On Cloud Native Web Applications Development using AWS Lambda and other offering. Practical examples of how you can combine multiple services and events in AWS and develop applications rapidly using AWS Lambda Functions", + "Last Updated": "18 Jun, 2018", + "Prerequisites": "Python: Basic of Python Programming Basics of Python Libraries Usages (Imports) AWS Free Tier account - https://portal.aws.amazon.com/billing/signup?redirect_url=https%3A%2F%2Faws.amazon.com%2Fregistration-confirmation#/start", + "Section": "Web development", + "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", + "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Ritu Mehra (~ritu86)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/serverless-application-development-using-aws-and-python~eEvga/", + "title": "Serverless Application Development using AWS and Python" + }, + "51": { + "Content URLs": "https://docs.google.com/presentation/d/1_hyRLHdITpIMzhAbpxuaTQkm6qop4ZWQt6ERGW4MFag/edit?usp=drivesdk&ouid=10471550379351873801", + "Description": "This is a simple talk about web scraping using python.In this lecture we going to have a clear picture of webscraping. \nBy the end of the lecture audience are going to have a clear picture of \nWhat is web scraping? \nWhat is the use of it? \nWhat are the useful libraries in python for web scraping? \nPros and cons of the libraries\nAnd mainly how to parse the Websites with practical examples", + "Last Updated": "18 Jun, 2018", + "Prerequisites": "A little amount of python knowledge is useful but not mandatory. I'm going to explain right from the very beginnin", + "Section": "Others", + "Speaker Info": "I am a student of Vishnu Institute of technology, Bhimavaram. I am studying 2nd IT. I was fallen in love with coding when I listened to the 1st lecture of my academic about C programming. That day changed my life. I have been working on python from January 2018.\nI am a quick learner, self disciplined, self motivated guy. \nMy hobbies are coding and learning new thing", + "Speaker Links": "https://www.sololearn.com/Profile/495149", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Deepak Puppala (~deepak12)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping~bDrKe/", + "title": "WebScraping" + }, + "52": { + "Content URLs": " Hydra Draft Hydra Ecosystem Wiki Hydrus Hydra Flock Demo Hydra CG homepage I'll be sharing my slides after the talk", + "Description": "Building Web APIs seems still more an art than a science. How can we build APIs such that generic clients can easily use them? And how do we build those clients? Current APIs heavily rely on out-of-band information such as human-readable documentation and API-specific SDKs. However, this only allows for very simple and brittle clients that are hardcoded against specific APIs. Hydra, in contrast, is a set of technologies that allow us to design APIs in a different manner, in a way that enables smarter clients. The main aim of this talk is to provide an overview of Semantic Web, Hydra Draft, and Hydrus. Hydra - Hydra is a framework to enable REST API to be described semantically using RDF. It is based on JSON-LD and proposed as W3C draft . Hydrus - Hydrus is a Flask server meant to build and deploy Hydra-based Web APIs in a straightforward and effective way. Hydrus utilises the power of Linked Data to create a powerful REST APIs to serve data. Hydrus uses the Hydra draft standard for creation and documentation of it's APIs. The flow of the talk will be as follows: My Introduction Brief Overview of Semantic Web and JSON-LD What is Hydra Draft? Detailed introduction to Hydrus How can we use Hydrus to create REST APIs easily? Future Scope An interactive Semantic Web demo. Q/A session", + "Last Updated": "18 Jun, 2018", + "Prerequisites": " Python Basic knowledge of APIs and Web", + "Section": "Web development", + "Speaker Info": "My name is Akshay Dahiya. I'm a Mentor and Organization Admin for Python Hydra in Google Summer of Code 2018 and I love working on Semantic Web and AI related projects. \nRecently, I have been learning through Udacity, adding more structure to my education on Web Technologies, Machine Learning, Deep Learning and Software development in general. I also mentor students across various Udacity Nanodegree programs (FullStack Nanodegree, React Nanodegree and Deep Learning Nanodegree) in my free time", + "Speaker Links": " http://www.xadahiya.me/ https://github.com/xadahiya/ https://www.linkedin.com/in/xadahiya/ http://www.typingeek.com/", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Akshay Dahiya (~xadahiya)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3rd-generation-web-apis-using-hydra-and-hydrus~dBpYa/", + "title": "Creating 3rd Generation Web APIs using Hydra and Hydrus" + }, + "53": { + "Content URLs": "A library for ANTLR that is being built by me is available here: https://gitlab.com/virresh/coala-antlr ANTLR's official page: http://www.antlr.org/ My blogs related to ANTLR in Python: https://virresh.wordpress.com/tag/antlr/ An example calculator: https://github.com/virresh/ANTLR4-Exampl", + "Description": "This talk aims at introducing ANTLR for python 3, and talk about Abstract Syntax Trees. It will present an overview of the process, the intricacies and will end with a concrete example to show the utility. ANTLRv4 is a tool that can generate parse trees for any compatible grammar, and provide tools to walk through that tree, so I will illustrate how to use that rather than dwelling more on the theory aspect of the parse trees and boost up the development of language tools. There is a speciality with ANTLRv4, we can separate context from the grammar (so we can get very close to the expectation that grammars are context free). I expect the session to be beginner friendly so no pre-requisites save some basic python expected. Also I will cover some basic examples, and also a demo of an actual language grammar to create a meta-program if time permits. The session is expected to have the following things: What is a grammar ? What are Parse trees and how do they compare to ASTs ? What is ANTLR ? (The parser generator and the runtime provided) How do we use a parse tree ? (dwelling on setting up the environment for ANTLR based development and a short, basic calculator building example) Visitors and Listeners A short real world example on detecting technical constricts in actual programming languages (probably Python itself)", + "Last Updated": "17 Jun, 2018", + "Prerequisites": "A working knowledge of python basics and some familiarity with some sort of command line interface is ideal (best suited if you are familiar with any unix/linux based systems, simple script invocation etc", + "Section": "Developer tools and Automation", + "Speaker Info": "I'm a student presently pursuing BTech in CSE at IIIT-Delhi, and am a GSoC student this year at coala.io and have been programming various stuff using python for around two years. I am developing a library to facilitate easy usage of ANTLR for building linting tools. I've worked on a large array of technologies in any area that I get to know about, ranging from Full stack development, to Systems programming to Language tools. I do my best to pick up and experiment with whatever technologies I can, and I love to learn ", + "Speaker Links": "GitHub: https://github.com/virresh Website: https://virresh.github.io/ Blogs: https://virresh.wordpress.com/ LinkedIn: https://www.linkedin.com/in/virresh", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Viresh Gupta (~virresh)", + "created_on": "17 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-antlr-with-python~az5ye/", + "title": "Using ANTLR with python" + }, + "54": { + "Description": "We have a word for it now - Domotics . The fun started a year back when I laid hands on this beautiful device from Amazon, which could not only manage your music, reminders, lists but also make calls and send messages. Basically, a smart phone in the cloud to be used without hands. But a developer sees endless possibilities with this powerful tool. Although speech recognition technology itself is nothing new, Amazon Echo has made its way to the homes of regular consumers. This talk is specially focused on giving a head start to the attendees about building and using powerful applications in python using an Alexa device. Being a python developer for the past 10 years and working on alexa skills for the past year, I intend to share my experience with the python community and enthusiasts. Broadly, this talk will be covering the following topics: How the echo framework and Alexa skills work An introduction to creating alexa skills in python with flask-ask Handling requests , responses , contexts and sessions . Testing applications with ngrok and deploying to the cloud. A sneek peek into other home automation possibilities like micropython embedding with popular microprocessors. The talk would be illustration and example driven and will include demos of cool app(s) I have been working on", + "Last Updated": "17 Jun, 2018", + "Prerequisites": "This talk is intended for developers who have a decent grasp on the basics of the python framework and trends, although you do not need knowledge of any specific packages or libraries. Just an enthusiastic mind is enough! The primary takeaway of this talk would be learning how to get started ideating and building applications for an alexa enabled smart home device and discuss some cool developer tips", + "Section": "Developer tools and Automation", + "Speaker Info": "Sonal Raj ( @_sonalraj ) has been an avid pythonista for 10 years. He has been working as an integral part of the financial technology industry for the past 4 years. Sonal holds a masters in Information Technology and has been a research fellow at the Indian Institute of Science, Bangalore. His domains of interest include distributed systems and graph databases, and he loves to explore new gadgets and develop new technology. He is also the author of the best selling book 'Neo4j High Performance' ", + "Speaker Links": " Talk at PyCon India 2014 Talk at PyCon India 2013 Real Time Computation with Apache Storm - IISc Bangalore Human Computer Interaction Systems : Slides Website Github Reasearch Profile", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Sonal Raj (~sonal)", + "created_on": "17 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/alexa-enabled-smart-home-programming-with-python~dy5nd/", + "title": "Alexa enabled smart home programming with Python" + }, + "55": { + "Content URLs": "http://github.com/gnsrikanth/simplelinuxbackdoor", + "Description": "In this talk, we discuss how python scripts can be used in the world hacking. Python can be used to automate many tasks and see how we can use network protocols using python. Programming isn't just codes, but it's a way of communication. This talk is more an awareness of the possibilities python can be used and hacking is one of them. We break down steps to hack a system and automate tasks using python. Topics covered: Sockets in python Using TCP, UDP protocols and creating a Server/Client A basic backdoor for windows Using HTTP protocol to steal users data Using encryption to obfuscate network traffic Subprocess module Pyinstaller to make binaries of malware Bypassing antivirus (we will test by uploading exe to virustotal) Using Sqlite3 to retrieve chrome passwords Emailing subprocess outputs with python Send data to google forms as POST Simple Ransomware code Other Python tools for hacking", + "Last Updated": "16 Jun, 2018", + "Prerequisites": "Basics in python, Operating system fundamentals, Networking basics", + "Section": "Networking and Security", + "Speaker Info": "I am Grandhi Srikanth, and truly passionate in cyber security. I hold C|EH, CCNA in Routing and Switching, Cyber Ops certification and interested in creating malware codes and as python makes it simple, I like using python", + "Speaker Links": "Twitter: @gn_srikanth LinkedIn: https://www.linkedin.com/in/grandhi-naga-srikanth/ Blogs: www.thebinarynoob.com Github: https://github.com/gnsrikant", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Naga Srikanth Grandhi (~naga_srikanth)", + "created_on": "16 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/coding-back-doors-with-python~ax5Bb/", + "title": "Coding Back-doors with Python" + }, + "56": { + "Content URLs": "Apache_Build_Monitor Jenkins' REST API & Pytho", + "Description": "As a build and release engineer, have you felt how good it would be to know the status of scheduled nightly builds before you reached office ? As a developer, have you wondered, while you were away from the desk, what's the status of quality gate builds that should be passed before the changes can be integrated to the mainline ? Intent of this talk is to outline what's offered via Jenkins's REST API and showcase some of the possibilities by consuming the API using Python", + "Last Updated": "16 Jun, 2018", + "Prerequisites": " Read-up docs on Python libraries XML, JSON Capability to follow and assimilate code snippets", + "Section": "Developer tools and Automation", + "Speaker Info": " Speaker works for a CyberSecurity firm in Bengaluru, India Likes being outdoors and reading books.", + "Speaker Links": "Linkedi", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Ramanathan Muthaiah (~ramanathan)", + "created_on": "16 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/consuming-jenkinss-rest-apis-in-python~dw58a/", + "title": "Consuming Jenkins's REST APIs in Python" + }, + "57": { + "Content URLs": " Code will be updated on github very soon.", + "Description": "There are many framework available in the market for free and with a lot\u2019s of feature like Django , Flask , Tornado . These framework help us to build web application and serving the files over the network without worrying about the low level details like how it works , how the files are being severed to the clients , web browser and how it handles the clients to be connected and serving the data to the lot\u2019s of clients with minimum amount of time with managed thread. So in this talk I\u2019ll share my knowledge how does the web server work and how we can build our own framework like other available framework and further enhance it , to make it big, and to handle the clients with multiple processes and threads. In this talk I will be talking about : What is a WebFramework and How does a web framework work? How we can make a simple web sever to serve the \u201chello world\u201d webpage to the browser How we can make the HTTP custom request header to tell the browser about the current status of request on the different situation like 200 , 404 , 500. how to server files like html, css to generate the advance webpages using socket to the browser. Getting the requested URL Params and serving the files over the network. Making a Download link and let the user to download the files over socket. Improvement of request and response time of the web server and optimising it so that the web server can handle more and more clients over the network. ", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "1. Basic python understanding. 2. Python installed on your system. 3 .Socket library (you can install it using the pip installer", + "Section": "Core python and Standard library", + "Speaker Info": "I am Nawneet Kumar, CTO at Elezire Technologies Pvt. Ltd. I have worked in Different Projects and in Different Languages in my past year. I have worked in era like IOT Development , Android Application Development , IOS Development and Web Development", + "Speaker Links": "Linkedin : https://www.linkedin.com/in/nawneet-kumar-77b64814b/ github : https://github.com/navSharma4", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "nav.sharma47", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-own-webframework-like-django-flask-tornado-to-serve-web-application-using-core-socket-programming~av55e/", + "title": "Building Own WebFramework like Django , Flask , Tornado to serve Web Application using Core Socket Programming" + }, + "58": { + "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/welch/seasonal Example Slides: https://www.slideshare.net/CheukTingHo/pydata-amsterdam-2018-time-series-analysis-with-seasonal-data-9909335", + "Description": "For time series analysis, everyone\u2019s talking about ARIMA or Holt-Winters. But there\u2019s other models which could also break down a seasonal series into trend, seasonality and noise. We will use an open source Python library called Seasonal to analyse B2B worldwide travel data. Times series analysis is an important part of data analysis for lots of businesses. It is very often for stakeholders to be interested in the performance of the business by analyzing measurements of profit, cost, number of sale, number of searches etc over time. In this talk, we will do a case study of showing how we estimate the impact public holidays made on the travel business. The method of analyzing the time series by seasonal breakdown will be explored and the work flow of solving the problem will be explained. In the first half of the talk, an introduction about time series and its characteristic will be explained for audiences who is new to analysis on time series. The data we use will be from a business to business travel company. It has seasonality thought out the year, a weekly cycle and also a growing trend in business. As the company have clients around the world, data from different countries will shows different behaviors as well. Therefore, before we show the analysis, the complexity of the data will be explored. In the second half, we will introduce a open source Python library called Seasonal. Using this package, we will demonstrate how to break down the travel data and extract the fluctuation of the sale in different countries. By comparing the fluctuation and Google calendar, public holidays in different countries can be spotted and their impact on the business can be estimated. This talk is for people who are interested in time series analysis and its application in business. Audiences with or without experience would also found this talk useful in giving them insights in how a business could benefit in making use of the data and doing a proper time series analysis", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-time-series-analysis-with-seasonal-data~er5pd/", + "title": "Case Study in Travel Business - Time Series Analysis with Seasonal Data" + }, + "59": { + "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/networkx/networkx Slides (not finalized): https://docs.google.com/presentation/d/1y_Wmuv_hqs8OZTI8XLJ5ajvjEpllK7Xeifa52yTpw-k/edit?usp=sharin", + "Description": "When you make a search for a hotel room, do you know how many travel agents are searching for you at the same time? In this talk, we demonstrate how to use the millions of searches a sourcing company received to build a network of travel agents and finding the main hubs among them using NetworkX. Network analysis is getting more and more attention in Business Intelligence, people hope to get information out of the structure of an organization or a communication network. In this talk, we use the hotel room search requests from travel agents, including online public website, B2C, B2B and B2B2C, to build a relational network among them. By using this network as an example, we demonstrate how insights can be extract by studying network properties. In the first half of the talk, we will explain how the network is built using NetworkX, an open-source python library that is designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. When 2 agents are making the same search at the same time , a link ( or an \u201cedge\u201d in network analysts terms) is made pointing form the initial searcher to the subsequent searcher. Using a list of these searches, a directed graph is built. We will also demonstrate how to pick the biggest connected component out form the graph. In the second half, with the graphs created, we show how different functions of NetworkX can be used to study the graphs. By compare the graph properties of our graph to the other popular network graphs, we can get the insight of how the network was created. Also by studying the graphs, we can understand the behavior of the agents and can even figure out which agents are acting as main hubs in the network. This talk is for people who are interested in network analysis and would like to see how it can be used in a business case. Audiences with any level of python experience can learn some basic concept of network analysis work and how it can be applied to provide business insights", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-understanding-agent-connections-using-networkx~bq5pb/", + "title": "Case Study in Travel Business - Understanding agent connections using NetworkX" + }, + "60": { + "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/seatgeek/fuzzywuzzy Source code available on Github: https://github.com/Cheukting/fuzzy-match-company-name Slides (not finalized): http://slides.com/cheukting_ho/fuzzy-matchin", + "Description": "Ever encounter a tricky situation of knowing there\u2019s names that are the same, but matching strings straight away leads you no where? All you need is FuzzyWuzzy, a simple but powerful open-source Python library and some wit. This talk will demonstrate how to efficiently fuzzy match company names. Matching strings should be one of the first natural language processing problem that human encounter since we start use computer to handle data. Unlike numerical value which has an exact logic to compare them, it is very hard to say how alike two strings are for a computer. One may compare them character by character and have an idea of how many characters in the pair of stings are the same. Unfortunately in most application we need computer to perceive strings like we do and therefore we have to use fuzzy matching. Fuzzy matching on names is never straight forward though, the definition of how \u201cdifference\u201d of two names are really depends case by case. For example with restaurant names, matching of words like \u201ccafe\u201d \u201cbar\u201d and \u201crestaurant\u201d are consider less valuable then matching of some other less common words. Also, do we consider company names that matches partly (like \u201cHappy Unicorn company\u201d and Happy Unicorn co.\u201d) are the same? In the first half of the talk Levenshtein Distance, a measure of the similarity between two strings, will be explained. Different functions in FuzzyWuzzy like \u201cpartial_ratio\u201d and \u201ctoken_sort_ratio\u201d will also be explored and compared for difference. It is very important to understand our tool and choose the right one for our task. Then in the second half, we will start tackling the example problem: matching company names, we will show that besides using FuzzyWuzzy, we have to also handle problem like finding and avoid matching of common words and speeding up the matching process by grouping the names. By combining all tricks and techniques that we demonstrate, we will also evaluate how efficient this method is and the advantage of using this method. This talk is for people in all level of Python experience who would like to learn a trick or two and would like to be able to solve similar problems in the future. Theory of how the library works will be explained and It is easy to be pick up even for beginners", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fuzzy-matching-smart-way-of-finding-similar-names-using-fuzzywuzzy~epKVd/", + "title": "Fuzzy Matching - Smart Way of Finding Similar Names Using FuzzyWuzzy" + }, + "61": { + "Content URLs": "Project source code on Github: https://github.com/Cheukting/GCP-GPU-Jupyter Demo code: https://github.com/Cheukting/jupyter-cloud-demo Example slides: https://www.slideshare.net/CheukTingHo/pycon-israel-launch-jupyter-to-the-clou", + "Description": "There are lots of reasons using a cloud service is favorable, but how to make sure consistency between development and deployment? With Docker and Terraform, we can create the same environment on cloud easily. For example, we will deploy a Jupyter notebook on Google Cloud Platform using both tools. In this talk, we will use a task: hiring a GPU on Google Cloud Platform to train neural network, as an example to show how an application can be deployed on a cloud platform with Docker and Terraform. The goal is to have Jupyter Notebook running in an environment with Tensorflow (GPU version) and other libraries installed on a Google Compute Engine. First we will briefly explain what is Docker and what is Terraform for audiences who has no experience in either or both of them. Some basic concepts of both tools will also be covered. After that, we will walk-through each steps of the work flow, which includes designing and building a Docker image, setting up a pipeline on Github and Docker Hub, writing the Terrafrom code and the start up script, launching an instance. From that, audiences will have an idea of how both tools can be use together to deploy an app onto a cloud platform and what advantages each tool can bring in the process. This talk is for people with no experience in application deployment on cloud service but would benefit form computational reproducibility and cloud service, potentially data scientists/ analysts or tech practitioners who didn\u2019t have a software developing background. We will use an example that is simple but useful in data science to demonstrate basic usage of Docker and Terraform which would be beneficial to beginners who would like to simplify their work flow with those tools", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Developer tools and Automation", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/launch-jupyter-to-the-cloud-an-example-of-using-docker-and-terraform~boKXb/", + "title": "Launch Jupyter to the Cloud: an example of using Docker and Terraform" + }, + "62": { + "Content URLs": "Source code available on Github: https://github.com/Cheukting/Style-mimicking-text-generator Example slides: https://slides.com/cheukting_ho/pylondinium1", + "Description": "Computers are getting closer to speak like humans. But can we even make them speak in particular ways, like as Trump or Shakespeare? In this hands on talk we will see how this is possible with the latest deep learning techniques combined with word embeddings and other advanced NLP technique. In this talk, first we would introduce two neural network and machine learning mechanisms which in popular and widely used in NLP (natural language processing): Word Embeddings and Recurrent Neural Network. Word Embeddings is a way to extract the context of a word by \u201clearning\u201d its presence in a paragraph; while Recurrent Neural Network, including LSTM (long short-term-memory), enable us to \u201ctrain\u201d sequential data. After that, we will showcase how to implement these mechanisms in a neutral network. With that, we can \u201cbuild\u201d a machine to generate articles, plays or speeches in the style of the training corpus and have lots of fun. In the first half of the talk, concepts of how Word Embeddings and LSTM works will be explained. Audiences will understand why this is essential in the field of NLP and why we are using it. In the second half, a code demo will be used to showcase how to implement these mechanisms. Through an example, audiences will learn how Keras is used together with Tensorflow and Python to build a sequential neutral network. We will showcase generating a paragraph using Shakespeare\u2019s play and another one using Trump\u2019s speech. This talk is for people who have some experience with data science and understand the concept of how a neural network works, but would like to go deeper into the details of how does it applied to NLP to solve more complex AI problems. We used very simple code but did a complex task like text generation, that opens the door for a lot of people who wants to experiment with deep learning", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "Basic concepts of Neural Network like Stochastic Gradient Descent and back propagation, as it will not be covered in the talk due to time limit", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-keras-building-an-ai-that-talks-like-shakespeare-or-trump~enX7b/", + "title": "Deep Learning with Keras : Building an AI that Talks like Shakespeare or Trump" + }, + "63": { + "Content URLs": " Hello world of chatbots world - wordbot An Experiment with Opensource chatbot engine - RASA NLU ", + "Description": "Google Assistant and Siris\u2019 of the world have tickled our curiosity enough to deep dive and understand under the hood technologies that make a chatbot. Though we don\u2019t have Google level of data to create a generalized chatbot, we can use the existing NLP engines and create chatbots that produce valuable results in a specific domain. For eg., anything that goes in your FAQ page can be converted into content for a chatbot. In this talk, I\u2019ll share my 2-year journey with chatbots. Existing bot platforms and how to leverage it to build your own chatbots and connect it with messaging platforms like slack, telegram etc., \nI\u2019ll also share my experience from my experiment on trying to build your own NLP engine. Key Takeaways Chatbot\u2019s architecture Natural language Processing, Understanding, and Generation what and how it plays an important role in building chatbots How to use existing chatbot engines to build a chatbot How to connect chatbots to Slack, FB Messenger etc., How to build your own chatbot engine", + "Last Updated": "14 Jun, 2018", + "Prerequisites": "Basic knowledge of Pytho", + "Section": "Data science", + "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape - Tech Enthusiast - Django & Chatbot specialist - Mentor/Speaker Build2learn , Chennai Geeks. Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", + "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavan", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Bhavani Ravi (~bhavaniravi)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatbots-101-peeping-under-the-hood~bm6Gd/", + "title": "Chatbots 101 - Peeping under the hood" + }, + "64": { + "Content URLs": "GitHub Repo: https://github.com/sleebapaul/gospel_of_rnn.git Google Colab Notebook: https://drive.google.com/file/d/1qh94MdQr9SeTLxGkMJc6kZGguRID8LqW/view?usp=sharing Blog: https://sleebapaul.github.io/rnn-tutorial", + "Description": "Language modeling was a complex task of previous days. But advancements in Deep Learning has solved this problem very effectively. Using many to one architecture of Recurrent Neural Networks, I've built a language model which can effectively generate the fifth gospel of bible by learning from four existing gospels. This model is also able to divide verses and chapters along with meaningful passages", + "Last Updated": "14 Jun, 2018", + "Prerequisites": " Recurrent Neural Networks basics Deep learning basics Language modeling basics Familiarization with PyTorch", + "Section": "Data science", + "Speaker Info": "Sleeba Paul is a Power System graduate and published researcher who loves intelligent machines. He currently works as a Machine Learning Engineer at Refly; an AI startup in India where he works on content enhancement and video analytics", + "Speaker Links": "Personal website: http://sleebapaul.github.io/ LinkedIn: https://www.linkedin.com/in/sleebapaul/ Github: https://github.com/sleebapau", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Sleeba Paul (~sleeba)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gospel-of-lstm-how-i-wrote-5th-gospel-of-bible-using-lstms~elLMe/", + "title": "Gospel of LSTM : How I wrote 5th Gospel of Bible using LSTMs" + }, + "65": { + "Content URLs": " Research Paper Github repository of project with over 80 stars: pyCAIR Beta release on PyPI: pyCAIR Docs: pycair.readthedocs.io", + "Description": "In this talk, I will speak about a simple yet very powerful image manipulation mechanism. The naive user utilizes the services of any standard toolkit, be it a web service or a remote application for image manipulation. The black box approach to this process is: A user provides an image and other parameters as input to the toolkit which in turn produces the results and returns it back to the user. Often these results are not up to the mark. The image sometimes gets distorted, misaligned or blurred. Deviating from the standard mechanisms, I would like to talk about a technique called as Content aware image resizing . The primary factor in this technique is the content . It is the content which drives the entire technique. The image is cropped, enlarged or modified keeping in mind the primary factor. I will talk about an algorithm called as Seam Carving which is used under the hood to achieve the aforementioned technique. It is this algorithm and the power of Python libraries , that makes this technique perform better than the standard mechanisms. Agenda of Talk: Introduction: Basics of seam carving, how the algorithm works Understanding energy concepts, basics of computer vision and dynamic programming Walk over the pseudo-code and dry run of algorithm Comparative analysis of this technique with standard mechanisms Q&A Session Conclusion", + "Last Updated": "14 Jun, 2018", + "Prerequisites": " Basics of Python", + "Section": "Developer tools and Automation", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pycair-smart-image-resizing-using-python~bkK6b/", + "title": "pyCAIR: Smart Image Resizing using Python" + }, + "66": { + "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", + "Description": "Problem description : Deep learning algorithms have shown great results in speech recognition domain, So here we have used deep learning techniques to enable the machines to read the lips from a video without sound better than humans. By analysing the movement of lips of a person we are trying to predict what that person is trying to speak.\nAutomated Lip reading can be helpful in many ways. Some of them are: Silent dictation in public spaces. Covert conversation. Helping the people with speaking ade in talking to other people. Improved hearing aids. Speech recognition in a noisy environment. The talk will be focused on : How the problem should be tackled. Discussion of different phases Algorithms and python libraries used for implementation.", + "Last Updated": "14 Jun, 2018", + "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations Basic understanding of Recurrent Neural Networks : An excellent resource to understand this is Understanding LSTM Networks . Similar to CNN the motive should be to understand the basic working of Recurrent Neural Networks. The coding part will be discussed in the talk.", + "Section": "Developer tools and Automation", + "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", + "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Saqhas", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-lip-reading-using-convolutional-neural-networks-in-python~ejMvd/", + "title": "Automated Lip reading using convolutional Neural Networks in python" + }, + "67": { + "Content URLs": "Will be provided soo", + "Description": "Everyone need not to know everything to build something great. If you are a student and wants to build a major/minor or a professional level project without worrying about the DevOps/Servers and its cost. If you are a Data Scientist and works with files/data and want to make your analytical tool public but you don't want to get in Server handling and learning some web framework . If you are a Frontend developer or work in a fast paced organisation where shipping out fast, better, robust and always running services are required. If you want to prepare a POC or a working model API fast without the requirement of server engineer. Then, this Talk is the place which your are looking for. This talk will be focused on How one can build really scalable and robust web APIs without learning any web framework that too in a very very easy manner. We will be talking about a python package I have made called Lamlight which makes the process of building web APIs as simple as a Git push . This package provides a CLI tool and answers the limitations imposed by the services like AWS lambdas . Lamlight enables Developer to: Make web APIs without learning any web framework or DevOps. Just focus on the core business logic because everything else it will provide you. (Eg: full python boilerplate, CLI automation tool ) Live code Changes. Put large dependencies on your Serverless web api like Numpy, Scipy, Pandas. Save 80% of time by making the process as simple as Git push. Objective of the Talk: Problems faced in a Servered Architecture. Introduction to Serverless Web APIs. Why Shift to Serverless Web Architecture. Platforms providing these Services and their limitations. Get Faster and beat these Limitations. Problems solved by Lamlight. Explanation of its working. Live demo. Q & A The talk would be extremely beneficial for students, Algorithm developer, Frontend Developer, Data scientists and others who are not familiar with server side development and server technologies or want to save time of server handling but still want their work to be done", + "Last Updated": "14 Jun, 2018", + "Prerequisites": " Love for Python Linux AWS(Optional)", + "Section": "Developer tools and Automation", + "Speaker Info": "Hello I am Rohit Negi. I am a developer with 1 year of professional experience and +2 years of freelancing experience. I have a Bachelor's degree and I am currently working as a developer in Elucidata Corporation, where I work on making technical architectures for the system to get connected and work robustly , designing Server APIs, Working with Frontend technologies like Angular to make the robust Frontend apps. I am very passionate about creating new and better stuff", + "Speaker Links": " https://www.linkedin.com/in/rohit25negi/ Email: rohit25.negi@gmail.com", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Rohit Negi (~rohit17)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lamlight-develop-webmobile-apps-without-learning-django-flask-and-any-other-web-framework~egKke/", + "title": "Lamlight: Develop web/mobile apps without learning Django, Flask and any other web framework" + }, + "68": { + "Content URLs": "GitHub More content will be updated soon", + "Description": "What is Transfer Learning? Transfer Learning is the method of reusing our existing knowledge developed for one task to solve a similar task. Say, you want to detect cars on night-time images and instead of learning from scratch we could reuse our existing knowledge from a model which has been trained on day-time images. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. I believe Transfer Learning is a major achievement in our quest for Artificial General Intelligence (AGI) as Transfer Learning allows us to generalize our knowledge which is something we humans excel at. Andrew Ng, ex-chief scientist at Baidu, co-founder of Coursera and professor at Stanford, said during his widely popular NIPS 2016 tutorial, \u201cTransfer Learning will be the next driver of ML success.\u201d Training Deep Neural Networks from scratch is an expensive process. Not only does it require a lot of compute resources and time, deep Learning models require a huge amount of data and it is a major bottleneck when it comes to start-ups and niche areas of research like health care. What you will learn :- How to build an image classifier in a few minutes using Transfer Learning When and how to fine-tune pretrained models Freezing layers of a pretrained model depending upon the scenario Using ConvNet as a feature extractor Using differential learning rates Constraints of using pretrained models Transfer Learning : Beyond Computer Vision Cross-Lingual Domain Adaptation : Using the knowledge we have learnt from one language and applying our knowledge to another language is another application of transfer learning with huge potential. Cross-lingual adaptation methods would allow us to leverage the vast amounts of labeled data we have in English and apply them to any language, particularly languages with very less labeled data such as Indian languages. Reinforcement Learning and Learning from Simulations : Training an agent (in Reinforcement Learning) to achieve general artificial intelligence directly in the real world is too costly and hinders learning initially through unnecessary complexity. It is better to train an agent in a simulated environment such as the OpenAI Gym before deploying it in the real world. Eg: Self-driving cars Agenda 1.Introduction to Computer Vision (3 min) 2.Introduction to Transfer Learning (3 min) 3.Why should you use Transfer Learning? (2 min) 4.When to use Transfer Learning? (2 min) 5.Build an image classifier in minutes using Transfer Learning (2 min) 6.Effective Transfer Learning techniques (6 min) 7.Feature Extraction using pretrained models (3 min) 8.Constraints of using pretrained models (1 min) 9.Transfer Learning beyond Computer Vision (3 min) 10.Transfer Learning : A right step towards Artificial General Intelligence (AGI) (2 min) 11.Q&A session (3 min", + "Last Updated": "14 Jun, 2018", + "Prerequisites": "Basic knowledge of deep learning Love for Pytho", + "Section": "Data science", + "Speaker Info": "Hi! I\u2019m fascinated by AI and it\u2019s applications particularly in art and culture - generating art, fashion styles, music, literature, etc. I\u2019m a 3rd year student (just started) at SRM Institute of Science and Technology, Chennai studying Computer Science Engineering. I\u2019m also part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in AI, Blockchain, Computational Biology, Electrical Systems, Internet of Things, and Mixed Reality. I\u2019m currently working as a Computer Vision intern at Cogknit Semantics, Bangalore. I'm working on a fashion recommender system which analyses an image of a shirt/pant/shoe and suggests matching clothes to go along with it. I love Python because of it\u2019s simplistic philosophy and lucid coding style which allows me to think more about model architectures rather than fixing bugs in my code", + "Speaker Links": "Connect with me on LinkedIn Find me on GitHub Follow me on Twitter E-mail me at : niladrishekhardutt@gmail.co", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "niladri99", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-subtle-art-of-effective-transfer-learning~dw5ra/", + "title": "The Subtle Art of Effective Transfer Learning" + }, + "69": { + "Content URLs": "https://www.slideshare.net/mobile/karx01/micro-python-pycon-india-2018-proposal-kartik-aror", + "Description": "This session will aim to achieve 2 objectives Introduce you to (in a fun and practical way), what is microPython. equip you to be up and running to build your own systems!", + "Last Updated": "13 Jun, 2018", + "Prerequisites": "Must know a guy who owns a raspberry Pi", + "Section": "Embedded python", + "Speaker Info": "Hello World. I am Kartik Arora, founder at Akriya Technologies . Before starting my journey in the wild, I worked for Rivigo for a few months, and in Bing Team during my 2 years at Microsoft", + "Speaker Links": "https://twitter.com/karx_brb https://www.facebook.com/karx01 https://www.linkedin.com/in/karx01 https://github.com/kar", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kartik Arora (~kartik53)", + "created_on": "13 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/micropython-time-to-get-building~av58e/", + "title": "MicroPython : time to get building" + }, + "70": { + "Content URLs": "My python script", + "Description": "Information is being generated at an exponential rate everyday. There are multiple sources generating information. It becomes really tedious for a person to go and visit all the sources to obtain information. It could be of great help to the person if there can be a single source which cumulatively providing all the links of news generated by different newspapers. This is where web scraping and automation comes into picture. In this talk I want to explain how to scrape webpages hassle free , gather information and represent the gathered content in a easy to visualize format. By executing just a single Python file we can get all the data what we want from the web. Its not just about collecting the data, it is to reduce the repetitive work which a person does again and again to achieve the same goal. We can put repetitive work into a module and leave it upon the computer to do the same. This in turn will help us channelize our time more on the information rather than gathering that information. Agenda of Talk: Introduction: Web scraping, automation tools, parsing and scraping python libraries. How it helps in learning python extensively: My experience with web scraping and various use-cases on which I utilized. Q&A session.", + "Last Updated": "12 Jun, 2018", + "Prerequisites": " Basics of python", + "Section": "Developer tools and Automation", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking.", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "12 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/importance-of-webscraping-and-automation-using-powerful-python-libraries~er52d/", + "title": "Importance of webscraping and automation using powerful python libraries." + }, + "71": { + "Content URLs": "Will be updated on github before the conference", + "Description": " It is always essential to understand the genesis of evolution or the roots of revolution. Keeping in mind the above saying, in this workshop, I will provide a hands-on understanding of Blockchain technology using Python. There are multiple resources to get a firm understanding about this domain, but the best way to understand it is by using the concept of \"Learning-By-Doing\" . Following are few reasons why I want to willingly contribute to this domain: Blockchain is the underlying technology behind most of the\n cryptocurrencies and it has a potential of changing the way we work\n and communicate, making it more secure, efficient, and trustworthy. There is a immense amount of speculation going around in this domain\n with the rise of Bitcoin. What\u2019s happening with blockchain\n technology, I would say, is similar to the great American gold rush\n that happened in the mid 1800s. Innovators, investors, entrepreneurs, technologists all are hovering\n over the same underlying idea on how these cryptocurrencies work and\n how could blockchain be leveraged to create use-cases beyond\n crypto-systems. Also, I would love to mention few quotes to support the escalating phenomenon of Blockchain : The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping\neverything along its way by the force of its progression. -- William\nMougayar Over the next decade, there will be disruption as significant as the Internet was for publishing, where blockchain is going to disrupt\ndozens of industries, one being capital markets and Wall Street. -- Patrick M. Byrne I will help people in understanding the bits and bytes of this domain, including the basic cryptography concepts, algorithms and how to utilize the power of Python language to build their own blockchain. As we progress, we would engage into more advanced concepts pertaining to scalability and deployment once we build a minimalist prototype of aforementioned. Using on-the-go learning while developing will serve as a pivotal entry point for all the people who are willing to enter into this space and planning to build smart-contracts or invest in cryptocurrencies. Agenda for workshop : Introduction to Blockchain: Existing problems, what is Blockchain, why it matters, gist of few use-cases, related concepts. Python revisited: Functions, libraries, object-oriented programming terminologies, basic data structures, basics of zen of python. Blockchain under the hood: Cryptography 101, underlying data structure and algorithms, conceptual terminologies. Python and Blockchain amalgamated: Create blockchain using python. User-friendly front-end: Integrating the scripts in previous section with a basic front-end. Discussion regarding scalability methods and resources. Generating self-help focused Pypi library called pymyblockchain . (optional) Q&A session. Note: The above agenda is subject to change. It is tentative for now. Any changes will be updated here itself", + "Last Updated": "12 Jun, 2018", + "Prerequisites": "Basic python: Functions , Classes and Objects , Use of Libraries *No prerequisites apart from aforementioned. Even a person who is new to python will be able to grasp everything in workshop", + "Section": "Core python and Standard library", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "12 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchain-by-implementing-it-from-scratch-in-python~bq57b/", + "title": "Understanding blockchain by implementing it from scratch in Python" + }, + "72": { + "Content URLs": "https://www.tensorflow.org/ https://github.com/aymericdamien/TensorFlow-Example", + "Description": "Hey everybody!\nIf you have ever heard of this thing called as neural network , than this workshop is definitely for you .Neural networks are not new they been there for a long time . but they have become quite famous recently\ntensorflow is consisdered one of the best frameworks for getting started with neural networks and deep learning . About TensorFlow TensorFlow\u2122 is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google\u2019s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. We will also try and build an image recognition model using deep learning from scratch . Tensorlfow helps getting started with deep leaning and building neural networks ", + "Last Updated": "12 Jun, 2018", + "Prerequisites": "Basics of python and an open mind to learn new things ", + "Section": "Data science", + "Speaker Info": "Python lover . Machine learning enthusiast . Currently working on BIG ML ( training machine learning models on big data ) and efficient deployment of machine learning models on production ", + "Speaker Links": "Contributor at https://github.com/polyaxon/polyaxo", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Pankesh (~PankeshGupta)", + "created_on": "12 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-build-neural-networks-from-scratch-using-tensorflow~boKYb/", + "title": "Learning to build Neural networks from scratch using tensorflow" + }, + "73": { + "Content URLs": "Any related material will be shared soo", + "Description": "Financial data is difficult. It is sensitive to many unknown factors. So we need a good strategy for trading with deep learning. That's where reinforcement leaning comes in. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over.\nBy the end of the talk, you will learn:- What trading is? Why it's hard? How Can Deep Learning solve the trading problem? Why is reinforcement learning an effective solution?", + "Last Updated": "11 Jun, 2018", + "Prerequisites": " Willingness to learn Basic python", + "Section": "Data science", + "Speaker Info": "I have always been amazed by computers and how much you can do with soo little. Curiosity lead to passion. Passion lead me to work on some amazing things. AI is the buzzword around and I have been working on AI for quite some time and it's been a really great journey, challenging but rewarding. Recently, I started working with some startups. Currently, I'm working for a Silicon Valley startup, who has been working on making serious predictions on small data. I have also been interested in Fintech data. I started with simple fraud detection models and now I'm working on solving the trading problem with reinforcement learning", + "Speaker Links": "Connect on Twitte", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Himanshu Singh (~himanshu61)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-trade-with-reinforcement-learning~enX5b/", + "title": "Learning to Trade with Reinforcement Learning" + }, + "74": { + "Content URLs": "Will be uploading soon !", + "Description": "My philosophy has been : If you haven't build it you don't know it. So lets build a hadoop clone and see how it works . This workshop is basically about building your distributed processing system . It will take you through some basics of distributed system and we will try and build our very own distributed system in python ", + "Last Updated": "11 Jun, 2018", + "Prerequisites": "Google \"what is hadoop\" Google \"what is a distributed system", + "Section": "Networking and Security", + "Speaker Info": "class Pankesh (human)", + "Speaker Links": "class Pankesh (Human): def __init__ ( python=\"Python3\" ) :\n\n super.name = \"Pankesh gupta\"\n\n super.age = 25\n\n curiosity = True\n\n experience = 2\n\n education = \"Thapar University , Patiala", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Pankesh (~PankeshGupta)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lets-build-a-hadoop-clone-in-python~bm6Rd/", + "title": "Lets Build a Hadoop clone in python !!" + }, + "75": { + "Content URLs": "-> How does a web framework work -> WSGI basics -> Getting hands dirty with coding More information will be uploaded soo", + "Description": "Build your own web framework using python .\nLets unleash the power of python by building a web framework from scratch . \nIt will help you understand what actually happens under the hood in most famous web framework", + "Last Updated": "11 Jun, 2018", + "Prerequisites": "Web development basics\nCuriosity\nTrust in python :", + "Section": "Web development", + "Speaker Info": "Not so useful BTech ( biotechnology ) from Thapar University\n2 years of experience working in pytho", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Pankesh (~PankeshGupta)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-our-own-web-framework-like-flask-in-python-from-scratch~el0je/", + "title": "Building our own web framework like flask in python from scratch" + }, + "76": { + "Content URLs": " Will have own slides. Link will be shared with all This GitHub Repo contains some of the content that will be delivered during the course of the talk. A lot of other websites from where I pick a point or 2", + "Description": "Everyday we listen to this word \"DATA\".\nBut after listening to that word, some questions might pop up in your mind. WHAT IS DATA? WHY DOES ANYONE NEED TO WORK WITH DATA? HOW TO UTILISE AND WORK WITH THIS DATA? Data is now one of the most important things for any business to run. From small startups to large companies, everyone looks at data to improve their business.\nEveryone looks at data to increase their profits. Everyone looks at data to understand why they failed and where they failed. Everyone looks at data to understand how a product gained success in the market. Basically Data is everything today for companies. Data is available everywhere now and it's become more important than ever to actually work with data and luckily we have great modules to work with data in Python. I'll be focusing on these modules and the power that data possesses. My primary focus here would be about the power of data. I surely will be talking about how to use this data in Python to make the most out of it, but before that I'd like the entire crowd to know what the power of data is. This would be a good talk for beginners honestly. Even if you have no idea about how data could be used or what is data, after this talk, you'll get a decent idea about it. Through this talk the 3 questions mentioned above in bold will be answered. The talk would progress in the following manner : Self introduction (3 minutes) Introduction about the topic (2 minutes) What is data? (3 minutes) Where is this data? (2 minutes) How to make the most out of data? (3 minutes) How Python helps in this process? (2 mins) Name and explain about different Python modules like Pandas, Numpy, Matplotlib and Seaborn in brief (10 mins)", + "Last Updated": "11 Jun, 2018", + "Prerequisites": "No prerequisites required. This talk will deal about everything from scratch and will give you a basic understanding of what modules could be used in Python. So you could research on those modules after the talk, but for the talk, no prerequisites required", + "Section": "Data science", + "Speaker Info": "Hey everyone, I'm Rahul Arulkumaran, a B.Tech 3rd year Student pursuing my major in Computer Science Engineering from Mahindra \u00c9cole Centrale, Hyderabad. I'm an open source and data science enthusiast. Coding is one thing I love doing all day and all night. Never feel like quitting.\nPython is my go to language. Anything I think of developing comes to life using Python. I have a very strong connection with Python as it was the first programming language I learnt. I'm also a full stack developer and perform data science on various datasets. I'm a Contributing and Managing Member in the PSF. I also am the President of the Computer Science Club in my college. Apart from that, I head the website development team for TEDxMahindra\u00c9coleCentrale and the Marketing and Promotions team for Aether (the techno cultural fest of MEC). I'm the Co-Founder and CEO of a startup which goes by the name FreeFlo. It is a product based company that looks at developing products related to Machine Learning, Blockchain and other related fields. I'm also currently interning in IIIT-Hyderabad in the Machine Translations and NLP Lab in the field of sentiment analysis. It might seem although I'm not interested in the non tech aspects of businesses, but I actually love working in teams related to business development and marketing. So that's mostly about it. Looking forward to interact with all of you out there ", + "Speaker Links": " GitHub My Blog Facebook LinkedIn Twitter Telegram Gmail ", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Rahul Arulkumaran (~rahulkumaran)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/power-of-data-and-working-with-it-using-python~bkgJb/", + "title": "Power of Data and Working with it using Python" + }, + "77": { + "Content URLs": "Will be updated soon", + "Description": "Fog and haze (referred to as the atmospheric light) are the main cause of distortions, degradation in the quality of images clicked during foggy situations. But with the advancement in technology, thanks to Python and OpenCV libraries and brilliant minds of people out here in this small world, recovering almost a fog-free image has been made possible in recent times. And now we are moving towards making this algorithm more optimized so that it can work in real time for videos and live camera feed. Different mathematical models have been presented over the time for this algorithm but there are very few real-life implementations in any particular programming language, so here the Python implementation of this algorithm will be discussed. Basic steps and the ideas implemented will be discussed in a brief and different implementation will also be shown in the session", + "Last Updated": "10 Jun, 2018", + "Prerequisites": " Basic knowledge of the numpy functions. An idea about the OpenCV computer vision libraries and the different filters implemented there. Love for Python", + "Section": "Developer tools and Automation", + "Speaker Info": "Speaker: Vivek Modi Final Year undergrad at NIT Durgapur Tech Head at GNU/LINUX USERS' GROUP NIT Durgapur Summer Intern at DRDO (Integrated Test Range) Contributor in the project: Soumam Banerjee Final Year undergrad at NIT Durgapur", + "Speaker Links": "modiher", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Vivek Modi (~modihere)", + "created_on": "10 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-and-opencv-for-removing-fog-and-haze-from-an-image~ejBye/", + "title": "Using Python and OpenCV for removing Fog and Haze from an Image" + }, + "78": { + "Content URLs": " http://github.com/vaideesg/omsdk http://github.com/dell/omsdk", + "Description": "Abstract Ever wonder creating your own super-type-manager leveraging the python's own type constructs? Ever explored alternatives to APIs for integration? In this talk, we will cover our experience in building a new type manager (as part of developing open source OpenManage(tm) Software Development Kit) leveraging pythons own type constructs and explore how this new type manager provides a credible alternative to APIs, especially in those information-heavy environments like Device Management. Description Devices (like Servers, Switches, Telecom Switches) are data-intensive systems. Their information model is so intensive, that practically all operations (health, inventory, metrics, configuration) on the device ends up in primarily as CRUD operations on the information model they expose. Only a paltry few operations are exposed as APIs. When building an API for managing these devices, we realized that providing classic function-style APIs only degraded the user experience. What we realized was there was significant information available on the Servers, and providing an API for exposing traditional CRUD (Create, Retrieve, Update and Delete) for all information nuggets was just exploding the API sets. It was not necessarily covering all the scenarios that could be possible for management and did not seem to scale. Our approach was to take this information model within the devices and expose them as a huge navigable data structure representing the entire spectrum of the device and provide a language native experience. We created a new type manager leveraging the python class special operators ( getattr (), setattr (), le () etc.) to create a whole new type manager that provides additional controls and safeguards. Some of the safeguards include: Not allowing edits to read-only components Allowing only applicable changes only (ranges, enumerations) Providing native python experience for special types (IP Address Types etc.) Providing mechanisms to validate cross-attribute validations Providing custom indices for arrays (like Virtual Disks, Users) Providing mechanism for tracking changes to configuration Apply changes to the device optimally Provide mechanisms for identifying configuration drifts Outline : Outline of the presentation: Introduction Device Configuration - Aspects & Peculiarities Pitfalls of API approach for Device Configuration Type Manager - introduction Super Types - Enumerations, Fields, Classes and Arrays Bringing in Native Type Experience Data as API - Enriched user experience Demo Q&A Key takeways to audience Audience will get an exposure: How to create your own type manager by overloading python type constructs Exposure to alternative approach to creating APIs for data-heavy systems & explore benefits Learn how type manager simplifies your life as well as the life of your consumers. Secrets of the python inbuilt __ operators - and how you can leverage them to provide native type experience even for your own custom classes How you can create a better user experience for customers in a simple way How you can incorporate Object Oriented SOLID principles", + "Last Updated": "10 Jun, 2018", + "Prerequisites": " General familiarity with type concepts (fields, arrays, classes, enums) is needed Exposure to in-built operators like ( getattr etc. will help) Exposure to Systems Management would be useful.", + "Section": "Core python and Standard library", + "Speaker Info": "Vaideeswaran Ganesan, Senior Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and data center products. His passion is compiler design, analytics, systems management, networking protocols and automation. Ajaya Senapati, Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and storage products", + "Speaker Links": "Vaideeswaran Ganesan\n 1. My Github Repository 2. My Linkedin Article which I wrote while implementing this Fun with Python Code Generation Ajaya Senapati\n1. Lin", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Vaideeswaran Ganesan (~vaideeswaran)", + "created_on": "10 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-as-api-building-a-type-manager-with-python~egyrb/", + "title": "Data as API: Building a Type Manager with Python" + }, + "79": { + "Content URLs": "Any related material will be shared soo", + "Description": "Natural language processing(NLP) is a branch of artificial intelligence concerned with automated interpretation and generation of human language. From keyword search to Virtual Assistants, from spell checkers to language translators and from sentiment analysers to Chat bots, NLP finds its applications in most of our day to day applications.\nThis workshop aims at delivering a basic Hands on tutorial to get started with NLP in Python. It commences with an introduction to NLP, discussion on various applications and a linguistic breakdown of Language (English). By the end of this workshop you will be able to : Install relevant packages such as nltk, gensim and pattern . Applying text processing techniques such as Tokenization, Stemming, Lemmatization and Chunking . Forming a Document Term Matrix using Bag of Words Model . Building a simple Spam/Ham classifier using Bag of Words Model . Generating Word Vectors using Gensim Word2Vec module. Building a Sentiment Analyzer . This workshop provides preliminary insight and a simple explanation to enthusiasts who wish to explore the field of Natural Language Processing.\nIt enables you to talk to your computer!", + "Last Updated": "10 Jun, 2018", + "Prerequisites": " Basic knowledge of Python. Any knowledge of Python modules such as Numpy, Pandas etc. is and add on.", + "Section": "Data science", + "Speaker Info": "Hello, I am Osheen Nayak, working as a Software Engineer at Texas Instruments Bangalore. I belong to Delhi Technological University batch of 2017.\nI am a Machine learning and Data Science enthusiast and I have been actively driving various Machine Learning activities. I have delivered few talks on Machine Learning in the past one of them including \"A primer on Machine Learning and Artificial Intelligence\" in the IEEE forum to and audience of 50 people. I am an avid football fan and also an amateur player.Also, I like to play video games, cricket and chess", + "Speaker Links": "Connect on LinkedIn : https://www.linkedin.com/in/osheen-nayak-31022a10b", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "osheen nayak (~osheen)", + "created_on": "10 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-talk-to-your-computer-a-101-on-natural-language-processing-with-python~e0M5a/", + "title": "How to talk to your computer - A 101 on Natural Language Processing with Python" + }, + "80": { + "Content URLs": "Slides TBD Code repository TB", + "Description": "Abstract Today, massive systems are running on microservices communicating with each other using REST APIs. HTTP is easy to get started, loosely structured and does good job in exchanging messages. But it's convenience comes with a performance trade-off, which takes us back to other optimal alternative: gRPC Description In this talk we will see what gRPC is and how it is different from REST. We will get started with GRPC by generating stubs for python and \nbuild a simple gRPC API server. We will try to find out the advantages of gRPC over REST by doing a side by side comparison of our APIs. We then deploy our server in Kubernetes and discuss how we could scale our microservices. Outline Introduction to gRPC (3 min) gRPC concepts (5 min) Designing the APIs REST-fully (3 min) Going the gRPC way (5 min) Generating python stubs Duel: gRPC vs REST python servers (4 min) Demo (4 min) Deploying our gRPC apis in kubernetes Summary (3 min) Q & A (3 min) Key take aways to audience Audience will get a practical introduction to gRPC and protocol buffers. Now the audience will know an alternative to HTTP/REST. This allows them to design better microservices\nbased on their use cases. Bonus: Deploying and scaling python microservices in Kubernetes. Links Companies using gRPC in production Protocol buffers ", + "Last Updated": "09 Jun, 2018", + "Prerequisites": "This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners", + "Section": "Web development", + "Speaker Info": "Naren is a Product Engineer with specific focus on building robust backend systems. Past 5 years, he has built dozens of microservices and scalable systems using Python, Go and AWS cloud. He is an open source enthusiast who loves speaking at tech conferences and currently works as Senior Software Consultant at Tarka Labs. In his industry experience he\u2019s worn plenty of hats- like the one of a Trainer, Embedded Engineer, Product Engineer and Consultant and sometimes even helmets- while he\u2019s out cycling.\nWhen he\u2019s not stirring up code, you can find him whipping up a delicious gluten-free treat or training for cycling races.\nHe also blogs about software, productivity and goes by the handle DudeWhoCode across the internet", + "Speaker Links": "Past 5 years I have been architecting and building scalable backend systems using Python. I have built a dozen of microservices at scale. Recently I built a production infrastructure in Python that handles 20+ millions of API calls per day. At one point of time, I realised I should know some alternatives other than REST to communicate between the microservices. Out of curiosity I explored and used gRPC in few of my microservices. Since then, I wanted to share the knowledge so that developers will get to know other options while architecting their infrastructure. This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners. I have spoken in various conferences, my recent one was PyCon Singapore 2018. Below are some of my previous talks and speaker portfolio: Speaker Portfolio Featured talk 1 Featured talk 2 Featured talk 3 portfolio blog Github", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Narendran R (~narendran)", + "created_on": "09 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-better-python-microservices-using-grpc~e9jJa/", + "title": "Building better Python microservices using GRPC" + }, + "81": { + "Content URLs": "I will upload slides soon", + "Description": "Object-Relational Mapper (ORM) is one of the powerful feature of Django. It allows us to interact with database without writing long complex SQL queries. The contents that will be covered in the discussion are as follows. Introduction to ORM, How it works ? What is queryset ? how it works ? Explaining use of values, values_list, only and defer to run ORM query efficiently How to use select_related and prefetch_related to optimize queries Some examples to show, how to query very complex data using only ORM What not to do while using ORM to avoid slow performance", + "Last Updated": "09 Jun, 2018", + "Prerequisites": " Basic knowledge of Python and Python web framework (Django) Some experience in quering relational databases", + "Section": "Web development", + "Speaker Info": "My name is Hiren Patel. I am working at Aubergine solutions pvt ltd and I have been doing full stack web development there from last 2.5 years. While working on some web projects, I have always focused on learning django in more detail and try to optimize APIs to return response faster", + "Speaker Links": " Github: https://github.com/hirenalken LinkedIn: https://www.linkedin.com/in/hiren-patel-046672ab/ StackOverFlow: https://stackoverflow.com/users/3553279/hiren-patel?tab=profile Medium: https://medium.com/@hirenpatel_38103 I had presented a talk on this same topic in meetup organised by Ahmedabad based meetup group. here is the link to meetup: lin", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Hiren Patel (~hirenalken)", + "created_on": "09 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/efficient-use-of-django-orm~b8gja/", + "title": "Efficient use of Django ORM" + }, + "82": { + "Description": "This workshop is dedicated to discuss and extrapolate on the core of Object Oriented Programming its finer details and nuances. The objective of the talk is to introduce concepts that will ensure OOP becomes second nature to a programmer. What you will gain after this session Detailed overview of Object Oriented Programming Intuition on the finer nuances of Object Oriented Programming. Tips on keeping the OOP code clean and readable. Expanding your horizon by understanding some lesser known concepts in Python. The session will focus on the following aspects with examples Inheritance and everything about it. Method Resolution Order Method Types Custom Base Object, Collections, and Dict Objects Extending Built-in Types Data Models Meta Classes and where they help Decorator and Class Decorators. Factory Design pattern Singleton Things to remember while writing code Conclusion", + "Last Updated": "09 Jun, 2018", + "Prerequisites": " Basic Python syntax Some understanding of Object Oriented Programming", + "Section": "Core python and Standard library", + "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", + "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Vishnu Kiran (~vishnu25)", + "created_on": "09 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-object-oriented-programming~e7MQb/", + "title": "Advanced Object Oriented Programming" + }, + "83": { + "Content URLs": "Will be sharing soon", + "Description": "Your introduction to concurrent programming in python. This talk is dedicated to a developer to enable him/her get started in asynchronous programming. The contents that will be covered in the discussion are as follows. What is asyncio? Why should we bother? Multi Threading vs Multiprocessing vs asyncio understanding the differences. All about what an event loop is with examples Futures Tasks and coroutines Streams Multiple Coroutines. Scheduling Calls Synchronization primitives Queues Working Example with a few notes on sockets and summary. The talk provides preliminary insight and a simple explanation to programmers who wish to explore asyncio and/or concurrent programming. ", + "Last Updated": "08 Jun, 2018", + "Prerequisites": " Basic understanding of python syntax. Some OS concepts like differences b/w multiprocessing and multithreading. Understanding UNIX (not mandatory).", + "Section": "Core python and Standard library", + "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", + "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Vishnu Kiran (~vishnu25)", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-asyncio~b6MOa/", + "title": "Introduction to Asyncio" + }, + "84": { + "Content URLs": "Part 1 Part 2 Github Rep", + "Description": "Websites and blogs have become a common trend amongst professionals to display not just their resumes but also their daily work items. Static blog generators have gained popularity over the last few years . People who have been using Wordpress, Blogspot or Blogger are now shifting to Pelican , Jekyll etc. One major annoyance was that Wordpress had a huge attack surface. Everytime someone found out a Wordpress exploit, your site was at risk. When comparing Blogger vs Pelican, the Slant community recommends Pelican for most people. In the question \u201cWhat are the best solutions for a personal blog?\u201d Pelican is ranked 10th while Blogger is ranked 14th. Python is becoming more and more popular amongst programmers and so is Pelican . \nPelican is a static blog generator and supports several formats like Markdown , ASCII etc . It turns Markdown and some Jinja templates into the Full Stack Python site. Its beauty lies in its simplicity and even a non programmer can get started with Pelican in just a few lines of code and plain text . Over the past few years people have shifted from Wordpress to Pelican .This is because a static site has basically no attack surface, and can be hosted on free or inexpensive hosts like Github Pages .\nThis talk is focused on introducing a simple static site generator to beginners and even avid bloggers who aren't coders . This talk will cover:- Basic installation of Pelican Writing a blog post with Pelican Changing themes of a blog/site Comparison between Jekyll and Pelican The main aim of this talk is to familiarize people with the concept of edifice . I have met a lot of non coders who have asked me about creating a basic website for personal use . This talk is also targeted to all those you are interested in blogging and everyone out there has something to say and something to blog ", + "Last Updated": "08 Jun, 2018", + "Prerequisites": "Absolutely nothing ", + "Section": "Web development", + "Speaker Info": "Anumeha Agrawal is a Pythonista and an open source enthusiast . She is in her third year of undergraduate program in Information Technology at NITK Surathkal . She is also a Google Summer of Code 2018 student at Systers . In her project at Systers , she has used python to write scripts to retrieve data from GitHub API and use it in her MEAN stack project . She uses python scripts to simplify most of her work like API data collection and web scraping . Python was the first language she was introduced to when she began programming and it is her weapon of choice . Owing to the simplicity of python syntax, she also used python to code her algorithms for her talks and workshops at college . Apart from being a full stack developer ,she is also a Data science enthusiast and employs python for designing most of her Deep Learning models and algorithms ", + "Speaker Links": "Link to Github Link to Linkedin Profile Link to Medium Blog Link to GSoC projec", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Anumeha Agrawal (~anumeha)", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pelican-magic-for-beginner-bloggers~e5MYe/", + "title": "Pelican - Magic for beginner bloggers" + }, + "85": { + "Content URLs": "http://click.pocoo.org (Cool power-point and Github repo coming up", + "Description": "Who hasn't used Git in the terminal? An absolute beast of a tool. But did you ever have an idea to build your own cool Command Line tool for something you believed could simplify life for other devs but you didn't because you were too lazy to research? Worry not! I present to you Click! Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It\u2019s the \u201cCommand Line Interface Creation Kit\u201d . It\u2019s highly configurable but comes with sensible defaults out of the box. In this talk, I'll go through the process of designing a simple (or complex) Command Line Interface called thanos which tells you whether you survived the SNAP or not. I'll be taking you through the process of designing, building and publishing our thanos package. We'll then upload it to the Python Package index so that you can do pip install thanos from any system worldwide and find out if you perished or not. Outline What is a CLI ? Building our own CLI called Thanos , to find out whether you survived the snap or not. >>thanos snap\n You didn't make the snap. Creating complex commands using beautifully decorated code. Exploring arguments, flags and options within the CLI. What's PyPI, and why do we need it? Uploading your new Thanos package to Python Package Index. QA", + "Last Updated": "08 Jun, 2018", + "Prerequisites": " Should have seen or used a terminal before. (Mandatory) Basic Python knowledge preferred.", + "Section": "Developer tools and Automation", + "Speaker Info": " Adarsh is a visionary who strives to build amazing tools for people. He is currently pursuing bachelors in CSE. Currently he is Google Summer of Code Intern at CloudCV , an organisation which works on making reproducible AI research, where he is building a versatile CLI for EvalAI project. He was one of the youngest speakers at FOSSASIA International Summit 2018 in Singapore for his work on Python based NLP POSTagger. Worships Open Source software and have contributed to multiple organisations like FOSSASIA, Zulip where he was also a mentor for Google Code-In 2016 .", + "Speaker Links": "https://www.youtube.com/watch?v=TzIr9THCUJg https://2018.fossasia.org/event/schedule.html#s-4267 https://github.com/isht3/ https://www.linkedin.com/in/guyandtheworld", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "isht3", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-your-own-command-line-application-and-upload-it-to-pypi~b427e/", + "title": "Build your own Command Line Application and upload it to PyPI!" + }, + "86": { + "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", + "Description": "In today's Era, the IT sector is moving more and more towards automation. Now every company is trying to provide its users with the facility to perform their task without the need for any human intervention.\nIn this talk, we are addressing a similar problem of automating the vehicle parking systems. Problem description: Automated license plate recognition(ALPR) is a well-known problem where we try to extract the license number from a cars number plate using machine learning algorithms. The scope of its real-world application ranges from highway toll plaza to automated parking and charging of future electric cars.\nThis problem has been targeted with a variety of algorithms like traditional template matching to advance deep learning algorithms like YOLO . Here we will be presenting a combination of little template matching clubbed with some deep learning to solve this problem in the most simplistic way", + "Last Updated": "08 Jun, 2018", + "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations", + "Section": "Developer tools and Automation", + "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", + "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Saqhas", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-license-number-recognition-in-python~e33Ae/", + "title": "Automated License number recognition in python" + }, + "87": { + "Content URLs": "Would update soon after feedback", + "Description": "Most machine learning algorithms require feature vectors as inputs. In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object (image, text, sound). Feature engineering, the practice of extraction of features from objects is a combination of art and science; it requires the experimentation of multiple possibilities and automated techniques with the intuition and knowledge of the domain expert. Automating this process is called \"feature learning,\" where a machine learns the features itself. One way to obtain features is to use the 'Bag-of-Features' model, the idea behind which is to simplify object representation as a collection of its subparts. Originally used for representing text data, the \"Bag-of-Words\" methodology can be extended to different types of objects resulting in models such as \"Bag-of-Visual-Words,\" \"Bag-of-Audio-Words.\" The significance of these models in the age of self-learning deep networks still holds because of their ability to work with limited data. The contents of the talk are: Introduction to Feature Engineering Working with Text Data Understanding 'Bag-of-Words' Example: Text Classification Working with Image Data Introduction to 'Bag-of-Visual-Words' Example: Image Classification Comparing the performance to CNN Overview of 'Bag-of-Audio-Words' Generalizing 'Bag-of-Features' This talk primarily discusses Bag-of-Words, Bag-of-Visual-Words through an example of text classification and image classification respectively. It also covers the concepts that generalize to models other than Bag-of-Features. The goal is to acquaint the audience who have previously worked on numeric data with some ideas to get started with text and multimedia data", + "Last Updated": "08 Jun, 2018", + "Prerequisites": " Intermediate knowledge of Python Familiarity with classification problems Familiarity with basic NLP/CV is helpful (but not necessary)", + "Section": "Data science", + "Speaker Info": "I'm a fresh graduate in Computer Science & Engineering. I am passionate about Data Science, and I spent most of my time learning about skills required to excel in the domain. Outside of my professional interests, I am fond of rock music and reading", + "Speaker Links": " Blog: https://pranavsuri.com GitHub: https://github.com/pranavsuri LinkedIn: https://linkedin.com/in/suripranav Twitter: https://twitter.com/pranav_suri", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Pranav Suri (~pranavsuri)", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bag-of-features-representing-text-image-data-as-numerical-vectors~b2XMe/", + "title": "Bag-of-Features: Representing Text & Image Data as Numerical Vectors" + }, + "88": { + "Content URLs": "https://github.com/Laneone/askfm-pytho", + "Description": "Hey everybody! Ever tried to webscrape? Ever faced a \"No robots allowed! No web scraping allowed!\" message from a favorite site? This talk is for meant for you. Usually when you're done building a fancy web scraper and begin running the homebrew'd tool on your favorite site there's chances you'll face a block on your IP address preventing your computer from accessing more resources and therefore downloading the contents of the website. Your tool maybe fast, it might be scalable, it might be the best written scraper out there, but with just one IP address under your belt, it's easy for giants to block your ip address and prevent you from getting that precious data, especially if you've built a threadsafe and multi-node webscraper. Enter The Onion Router, The ToR project, allows you to use the the internet vis-a-vis a proxy and visit the same website under a different endpoint ip address, but that's just for one instance of ToR. What if you ran, say 200? at once? 200 ip addresses > 1 ip address. With 200 endpoints and the latest update to the requests library, you can now use your multi-threaded and resource hungry webscraper and it can(not) be stopped! Whatever your rate of data collection, you can 200x it! The stack is simple, you open a SOCKS5 proxy per ToR endpoint, connect it to a request with it's own port number and you're good for that one request, same for multiple requests. You can build a task scheduler to orchestrate the url to scrape and the port number the tor endpoint is on and have the entire application running on a cloud service provider to ensure you face no bandwidth issues. The demo centered around the talk will attempt to rapidly and quickly scrape users from the famous social network Ask.fm which is known to restrict users from retreiving from their site if you attempt to download more than 4 users in under a second, but with the hack in place, you'll be retrieving close to maximum efficiency on a DigitalOcean droplet , but this can be applied to virtually any website and any cloud provider. Never pay for webscraping again! Thanks and see you at PyCon! \n-Lokesh Poovaraga", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Basic concepts of web scraping, Regex, Task scheduler, ports and proxies", + "Section": "Developer tools and Automation", + "Speaker Info": "Hi I'm Loki! (Lokesh Poovaragan) A full-stack developer from Dayananda Sagar, Bangalore, and I love to code in python! In my free time I love to web scrape and gather good amounts of public data and encompass them into json format for data(sentiment) analysis. I also build prototypes of interesting combinations of technology to solve unique problem statements. I love exploring new and interesting areas of work and I love to play with code", + "Speaker Links": "Blog: http://laneoneblog.blogspot.in GitHub: http://github.com/Laneon", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Laneone (~Laneone)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-intermediates-guide-to-theoretically-unlimited-webscraping-with-python-using-requests-lxml-tor~e1MZe/", + "title": "A Intermediate's Guide to (theoretically unlimited) WebScraping with Python using Requests & lxml & ToR" + }, + "89": { + "Content URLs": "This one is the essence of it but closed source and in java: https://lifehacker.com/how-to-build-your-own-amazon-echo-with-a-raspberry-pi-1787726931", + "Description": "Voice is the new touch. It's not going to be too long before the likes of Alexa or Google Home take over our day to day life like the Internet and the mobile phones have. There are countless tutorials on how to hook up a home automation system using a Raspberry Pi like here and here . Pair that up with voice capabilities and you can basically tell your lights to turn themselves off or the TV to change the channel. In this talk I'll cover the following: Hook up a microphone to a raspberry pi and be able to capture wav files on python. Use an online API like Google's Speech API to convert the wav to text. Give a background on what intents and entities (slots) are. Installing open source software like Snips Encoding our intents and example sentences and training the open sources software Calling a functions to do particular activities At the end there'll be a cool demo", + "Last Updated": "07 Jun, 2018", + "Prerequisites": " Knowledge of what a Raspberry Pi and Python is. And maybe played with an Alexa, Siri or Google Home. Yup, low barrier of entry", + "Section": "Embedded python", + "Speaker Info": "I am Ved. I have a masters in Computer Science/Data Science from IIIT-Bangalore and I work on NLP/Linguistics at Slang Labs. My goal in life is to sit down and have a conversation with a computer at a bar coffee shop. Maybe we won't get there soon, but at least maybe I can make it reserve my seat for me", + "Speaker Links": " vedmathai.com https://github.com/vedmathai/ https://www.linkedin.com/in/vedmathai/", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Ved Mathai (~ved47)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/create-a-voice-conversational-agent-for-your-raspberry-pi-home-automation-system~eZgQa/", + "title": "Create a voice conversational agent for your raspberry pi home automation system" + }, + "90": { + "Content URLs": "Shall be updated soon", + "Description": "Here, We will talk about how you can make a bot to help you automate your life and make your very personal Assistant, and maybe you will end up making something better than Google Assistant or Siri. We will be using modules to perform a task, so you can keep making them as you go and your assistance will keep becoming more powerful and yes all this will be done in python. In this talk: - We will start with setting up project creating simple python GUI. - Making some modules to perform a simple task. ~ Composing email with speach ~ Some other cool modules - Explaining what else we can achieve with this. ~ Let's make, its personality using tensorflow for talking stuff - Showing my work and explaining how it works Here, Is in early development phase Then we will end with some questions and how they can continue with this project", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Basic Understanding of Python", + "Section": "Developer tools and Automation", + "Speaker Info": "He is a student, a self-taught programmer loves to dig deep and know more about the computers. Fell in love with python and now loves to Automated things with python. He is GSoC aspirant. He is an active volunteer at PyDelhi and ALiAS . When he is not automating things he loves to contribute to open-source and closing issues", + "Speaker Links": "Website: omkar.site Github: @omi1085", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "omkar yadav (~omkar10)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/superpybot-your-personal-assistant~bYZAd/", + "title": "SuperPyBot: Your Personal Assistant" + }, + "91": { + "Content URLs": "https://www.artima.com/weblogs/viewpost.jsp?thread=214235 http://www.dabeaz.com/python/GIL.pdf -slides tb", + "Description": "Python is an amazing language, known for its vast standard library and use in rapid prototyping. When we were trying to build a robotics system that is primarily modular and upgradeable, we ended up using Python to power the brain of the project. In this talk, we'll discuss how we designed the event loop, responsible for controlling the mechanical actions and state of a robot snake. Animating multiple motors concurrently at different speeds to different positions. Foreground and background tasks. Interrupting ongoing tasks. We will discuss best practices when performing asynchronous actions in Python, and how to ensure actions are completed within a bounded time.\nFinally we touch one of the lesser known 'features' of Python, the Global Interpreter Lock. GIL is a mutex that protects access to Python objects, preventing multiple threads from executing at once. Two threads calling a function may take twice as much time as a single thread calling the function twice. We'll discuss some of the real world implications of the GIL, along with some considerations that must be taken while writing highly synchronous Python code", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Knowledge of common Python syntax would be great", + "Section": "Core python and Standard library", + "Speaker Info": "Hi, I'm Pranith, a final year undergrad student at NMIT, Bangalore. I'm a robotics enthusiast with a passion for cypherpunk, virtual reality, and generally, the future. Apart from the usual frameworks, I've used Python across the field, ranging from web technologies implemented on raw CGI to microPython on the ESP8266. I try to apply Python in odd ways to bridge various layers of the stack, and as a result have a fair amount of experience breaking it", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Pranith Hengavalli (~prnthh)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/robot-snakes-and-the-global-interpreter-lock~eXPve/", + "title": "Robot Snakes and the Global Interpreter Lock" + }, + "92": { + "Content URLs": "Slides : Coming soo", + "Description": "Large Python codebases can be hard to maintain. If we make it easier to understand our code bases, we make everyone more productive and help each other write fewer bugs. Static typing is one of remedies that can improve readability and maintainability of the code. That's why Python now features optional static typing as described in PEP-484 , implemented as Mypy . Mypy is an experimental variant of Python that let's you add optional type annotations to type check your Python code. And it works great on both Python 2.7 and 3.3+. Adopting static typing is easier that you think, you can start on a small set of code and move on to bigger pieces. In this talk I'll share about, PEP-484 and Introduction of type annotations in Python 3.5 Use cases of Mypy and how to use it with Python 2 and 3 Project typeshed and how to leverage it Lessons I learned by type hinting the project Twine We\u2019ll also discuss how to make it a seamless part of your project; what order to approach things in; and some powerful new packages that make it even easier today to add static types to your Python codebase than ever before", + "Last Updated": "07 Jun, 2018", + "Prerequisites": " Knowledge of Python Difference between dynamic and statically typed languages", + "Section": "Core python and Standard library", + "Speaker Info": "Wasim is a Senior Software Engineer at Zemoso Labs, Hyderabad. He's an open source fanatic who loves to create meaningful software and contribute to open source projects. Some of his contributions are included in projects like Sendgrid, Warehouse, Twine and Hazelcast. Apart from programming he also tweets . You can find him interesting on his GitHub profile ", + "Speaker Links": "Article on Medium about Mypy Open source contributions can be found at my GitHub profile ", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Wasim Thabraze (~waseem18)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mypy-optional-static-typing-for-python~bW1Ee/", + "title": "Mypy: Optional Static Typing for Python" + }, + "93": { + "Description": "In Data Science, Garbage In = Garbage Out. Feature engineering is one of most of the important yet most neglected step in life cycle of Machine learning projects. Kaggle competitions have showed us that top Kagglers spend more than half of their time in feature engineering. Through various experiments, its also proved again & again that better features with simple model triumphs even advance models. In this talk I am planning to discuss basic as well advance feature engineering techniques which can be used by everyone in their projects Outline What is Feature Engineering ? Techniques for Numerical Variables Techniques for Categorical Variables Techniques for Textual data Advance techniques Feature Selection & Dimensionality reduction QA", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Basic knowledge of Python & Machine learning", + "Section": "Data science", + "Speaker Info": " Sudarshan Gadhave is a Data Science ,Data Engineering & Data\n Integration professional with over 8 years of experience working on\n Machine Learning , Data Engineering , Data Visualization and Data\n Warehousing Projects. Currently he is working as a Specialist Data Scientist in Analytics R&D team of\n Nice Actimize ( Nice Systems) working on developing Anomaly & Fraud detection models. Earlier experience of working in Advance Analytics & Data Warehousing\n teams of NEC, Japan & John Deere (Deere & Company). Pythonista & expert in Python Machine learning stack (Numpy,Pandas,\n Scikit-Learn, Matplotlib) Active & Core member of Python Pune meetup group.Presented several\n talks on Python & machine learning in meetups, conferences and\n colleges all over Pune.", + "Speaker Links": " Github:- https://github.com/sudarshan1413 Linkedin:- https://www.linkedin.com/in/sudarshan-gadhave-73567b23/", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "sudarshan1413", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/art-of-feature-engineering-for-machine-learning~eVWza/", + "title": "Art of Feature Engineering for Machine Learning" + }, + "94": { + "Content URLs": "A few topics I will be covering, I would not be covering everything in detail, but hope to highlight important aspects from these links over the talk session: http://openmusictheory.com/ https://in-thread.sonic-pi.net/ https://github.com/gkvoelkl/python-sonic http://www.daveconservatoire.org/course/introduction-to-sonic-pi By the end of this talk, I aim to instil a much better idea about Live Coding and Programming Musi", + "Description": "Sonic Pi: An open-source live coding platform developed by Dr Sam Aaron aims to explore and teach programming concepts based primarily on the process of creating new sound.\nWe will venture deeper into the live coding platform and produced different genres/styles on music while coding live and dwell further into performing algorithmic music on a wider scale. I have tinkered with different styles of tones and sounds in sonic-pi and Python and re-created a rendition of popular 21st century music, only through algorithmic-generation, and seek to promote appreciation about open-source software such as sonic-pi and aim to demonstrate it's applications, along with the use of Python over the course of a thirty minute-talk and demo, in the rendition of producing Algorithmic-Music Live , during the course of the talk. By the end of the session, I aim to establish a better understanding of Live-coding, Programming Music and Intelligent-dance music Artists such as Aphex Twin. The flow of the talk will be as follows: Self Introduction Introduction to Music-theory and Sound Generation Introduction to Live Coding and Python-sonic Understanding the algorithmic workflow Diving beyond: Guitars, drums and Piano Produce an algorithmic-track! End of talk Q&A Session We shall also fiddle with a physical midi-controller if we find time, and demonstrate various interesting forms and styles of music; \nWe will also be producing a popular 21st century track from scratch ", + "Last Updated": "07 Jun, 2018", + "Prerequisites": " A curiosity for algorithmically-produced music, Python and open-source software. Basic Music theory knowledge is appreciated, but anything relevant will be covered during the talk.", + "Section": "Others", + "Speaker Info": "My name is Sushen Kumar. I am a currently pursuing a Bachelor of Engineering in Computer Science at Sir M Visvesvaraya Institute Of Technology, Bangalore. Over the course of my academia I have dabbled into a few open-source projects, as well as contributed to open-source organisations on GitHub: Attended several hackathons around India: (Winner-ValuePitch Hack, Runners' up- IESA Makeathon) Given talks and held beginner sessions on Creative Coding in Python and sonic-pi. Completed three grades in hindustani-classical music-theory, with 8+ years of experience in playing the Guitar and Harmonium. Received 3 Honours and Awards (National level). I absolutely love Music and Coding, and aim to merge this passion and demonstrate the applications of Python and open-source frameworks in Music Production by means of this talk :)", + "Speaker Links": " https://github.com/nehsus https://www.linkedin.com/in/sushenk/", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Nehsus (~nehsus)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-algorithmic-music-and-melodies-with-python-sonic~dRXVa/", + "title": "Generating Algorithmic Music and Melodies with Python-sonic" + }, + "95": { + "Description": "Data Wrangling involves detection, correction, removal, or otherwise dealing with inaccurate and corrupted data. The most common file formats in which data can be stored are CSV, JSON, and XML. However, many times, the data is not available in the desired format and rather is available in some unconventional file formats like PDF or PPT. Parsing PDFs may seem like a daunting task to many as it is quite an unpredictable format. Simply stated, PDF is a hard-to-parse format. This workshop will help you understand the concept of Wrangling PDFs in an easy and fun way. Following will be the flow of this workshop: Self Introduction Brief Introduction to Data Wrangling Why prefer CSV, JSON, or XML? Why avoid using PDFs? Basics of RegEx based Pattern Matching Parsing PDFs Programmatically using \"slate\" and \"pdfminer\": Getting hands-on Inefficient Parsing? Consider Data Cleaning Exploring PDF Wrangling with \"pdftables\" Where to go from here? Question and Answers Session The End :) Key Takeaways: Gain confidence in Data Wrangling using Python. Get familiar with the daunting PDF Parsing task. Get hands-on with popular PDF Wrangling libraries in Python: \"slate\", \"pdfminer\", and \"pdftables\". Understand the concept and importance of Data Cleaning.", + "Last Updated": "06 Jun, 2018", + "Prerequisites": " Basic knowledge of programming in Python language. Familiarity with wrangling CSV, JSON, or XML files will be good but is not necessary.", + "Section": "Core python and Standard library", + "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", + "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "greatdevaks", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/wrangling-unconventional-file-formats-with-python-playing-with-pdfs~aQXGe/", + "title": "Wrangling Unconventional File Formats with Python: Playing with PDFs" + }, + "96": { + "Content URLs": "I delivered a talk on Recurrent Neural Networks at GeoPython 2018, Switzerland. The proposed talk will be enhanced version of my previous talk. This time, I will be covering more topics to make it a more detailed talk.\nLink to my previous talk: https://github.com/greatdevaks/GeoPython_Basel_201", + "Description": "Recurrent Neural Networks (RNNs) have become famous over time due to their property of retaining internal memory. These neural nets are widely used in recognizing patterns in sequences of data, like numerical timer series data, images, handwritten text, spoken words, genome sequences, and much more. Since these nets possess memory, there is a certain analogy that we can make to the human brain in order to learn how RNNs work. RNNs can be thought of as a network of neurons with feedback connections, unlike feedforward connections which exist in other types of Artificial Neural Networks. The flow of the talk will be as follows: Self Introduction Introduction to Deep Learning Artificial Neural Networks (ANNs) Diving DEEP into Recurrent Neural Networks (RNNs) Comparing Feedforward Networks with Feedback Networks Quick walkthrough: Implementing RNNs using Python (Keras) Understanding Backpropagation Through Time (BPTT) and Vanishing Gradient Problem Towards more sophisticated RNNs: Gated Recurrent Units (GRUs)/Long Short-Term Memory (LSTMs) End of talk Questions and Answers Session", + "Last Updated": "06 Jun, 2018", + "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras or TensorFlow will be good but not necessary.", + "Section": "Data science", + "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", + "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "greatdevaks", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-recurrent-neural-networks-using-python~dPGAb/", + "title": "Understanding and Implementing Recurrent Neural Networks using Python" + }, + "97": { + "Description": "Considering the fact that businesses these days make a lot of money by recommending customers the things that match their likes, knowing how to build a Recommendation System would be of great use to many aspiring Deep Learning enthusiasts. This workshop is all about understanding and implementing Auto-Encoders. Auto-Encoders are the Unsupervised Deep Learning Models which are widely used for Dimensionality Reduction and Feature Discovery. New types of Auto-Encoders have enabled us to build very nice Recommendation Systems. The talk will focus on understanding Auto-Encoders, their types, and building a Recommender System that Predicts Rating (1 - 5) using PyTorch. The flow of the workshop will be as follows: Self Introduction Introduction to Unsupervised Deep Learning Diving DEEP into Auto-Encoders (Theory, Architecture, and Working) Introduction to Sparse Auto-Encoders Introduction to Denoising Auto-Encoders Introduction to Contractive Auto-Encoders Introduction to Stacked Auto-Encoders Understanding the Deep Auto-Encoders Training Auto-Encoders Building a Recommender System that Predicts Ratings (1 - 5) Understanding the Problem of Overcomplete Hidden Layers End of talk Questions and Answers Session", + "Last Updated": "06 Jun, 2018", + "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras, TensorFlow, or PyTorch will be good but not necessary.", + "Section": "Data science", + "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", + "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "greatdevaks", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-auto-encoders-using-python~aOGRa/", + "title": "Understanding and Implementing Auto-Encoders Using Python" + }, + "98": { + "Content URLs": "Will share the code, slides, and resources as a GitHub repository after the talk", + "Description": "Automatic Visual Speech Recognition comes very handily in scenarios that have noisy audio signals. A video image of a person talking is analyzed and shapes made by the lips are examined which are then turned into sounds by comparing to a dictionary to create matches to the words being spoken. In this talk, we will use a VGG+GRU network which is based on CNN+LSTM layers to predict the text spoken by the speaker and classify it into 20 classes from audio-less videos, consisting of 10 words and 10 phrases. This will be done on the audiovisual MIRACL-VC1 dataset. The talk will cover how a CNN+LSTM can be used to recognize a sequence of shapes formed by the mouth and then match it to a specific word or sequence of words spoken from Visual Feed. It will include data-preprocessing, creation of CNN and LSTM layers using Python and applying them on the dataset", + "Last Updated": "06 Jun, 2018", + "Prerequisites": "Basics of Python Syntax, Tensorflow, Keras, Neural Network", + "Section": "Data science", + "Speaker Info": "Kanika Modi holds a Bachelor's in Computer Engineering from Netaji Subhas Institute of Technology, University of Delhi. Having finished her coursework, she will join Amazon as a Software Development Engineer(SDE). She is an open source enthusiast and has contributed to organizations such as Systers, Fossasia, etc. She is also a Google Summer of Code'18 mentor at Systers, a GirlScript Summer of Code'18 mentor and mentor at RightApprise. Her interests also extend to the fields of artificial intelligence and machine learning. She prefers Python as her weapon of choice", + "Speaker Links": "Link to LinkedIn Link to GitHub Link to Twitte", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "kanika_96", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-lip-reading-system-to-recognise-visual-speech-using-python~dNG2e/", + "title": "Building A Lip Reading System To Recognise Visual Speech Using Python" + }, + "99": { + "Content URLs": "Brief content is here: https://github.com/yashug/Pandas Actual workshop will cover more inf", + "Description": "The Goal of this workshop is to make you more fluent at pandas to answer data science questions. Python has long been great for data munging and preparation, but less so for data analysis and modelling. pandas help fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R", + "Last Updated": "04 Jun, 2018", + "Prerequisites": " Laptop with Anaconda installed Basics of Python", + "Section": "Data science", + "Speaker Info": "Yaswanth is a Senior Software Engineer, currently working in ZeMoSo Technologies and Graduated from IIT Guwahati. Free and open source software enthusiast, and passionate about Python and Machine Learning", + "Speaker Links": "Linkedin | Githu", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Gosula Yaswanth (~yashug)", + "created_on": "04 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-pandas-for-better-data-science~aKGGa/", + "title": "Using Pandas for Better Data Science" + }, + "100": { + "Description": "The Jupyter ecosystem of tools lets you interleave code and stories for a literate computing experience, where you can visualize your data as html, plain text, svg and images. You could also view the same rich displays in multiple environments - on the web, on your desktop, in your shell or even your IDE . But how is this possible without duplicating logic, re-inventing the wheel multiple times? How do visualization libraries like Bokeh, Plotly work across frontends - like jupyter notebook, jupyterlab and nteract? This talk explores Jupyter's display system and how it handles multiple display formats in multiple environments. We will see how this idea is applied in some open visualization libraries. After this talk, you will know how to integrate your python objects better with the notebook. You will also get an idea of how to create a visualization library that works across the Jupyter ecosystem of tools. Duration 45 mins (Content can be modified to fit into 30-minute slot too) Outline - Setting some terminology for the rest of the talk (what is a frontend, kernel, displayhooks) (5 mins) - How to use Jupyter's display hooks for your python objects with the notebook (10 mins) - The Jupyter messaging protocol - specifically, the display_data and update_data messages (5 mins) - Custom mime-types (and this is the secret to Jupyter's display system!) - separating what to display from how to display it (10 mins) - Examples of custom mime-types in the wild (a look at altair , vdom , plotly and more) (10 mins) Additional notes This proposal might seem to overlap with another - Jupyter Notebooks: Internals and Extension - which explores how jupyter works under the hood and how to create alternative frontends. My talk's focus will be different, and will dive into a very specific part of Jupyter - the display system - in depth", + "Last Updated": "04 Jun, 2018", + "Prerequisites": "Some experience using either the jupyter notebook or jupyterlab ", + "Section": "Others", + "Speaker Info": "I am a software developer at D.E.Shaw, Hyderabad. I've occasionally contributed to projects in the jupyter ecosystem - the notebook, ipywidgets, hydrogen, nteract", + "Speaker Links": "Github Twitte", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Madhumitha psg (~madhumitha)", + "created_on": "04 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyters-rich-display-system~dJ1Kb/", + "title": "Jupyter's Rich Display System" + }, + "101": { + "Description": "With the advent of Tableau and languages like Python and R, converting raw data into meaningful insights is much easier and convenient than before. Tableau is a tool used to visually represent data and is powerful enough to analyze the given data at any required level. At an industry perspective, the tool comes handy in finding the trends in marketing and sales with a click of a button. Introducing Python to Tableau using TabPy can help define calculated fields in Python, thereby giving it the power to leverage a large number of Machine-learning libraries right from the visualizations. This widens the scope of its applications to any field that deals with big data and its analytics. Optimisation and cross-sharing of data models facilitated by TabPy immensely enhance the efficiency and usability of the tool. With just a few lines of code, we can churn out predictive models and increase the accuracy of future predictions. The talk will primarily focus on: An introduction to data manipulation and visualization using Tableau. An overview of the steps to leverage TabPy in Tableau. The impact and advantages of Tableau-TabPy combination in the real world.", + "Last Updated": "03 Jun, 2018", + "Prerequisites": "A rudimentary understanding of Data Science and Python scripting", + "Section": "Data science", + "Speaker Info": "I am a sophomore undergrad in computer science from Amrita School of Engineering, India of which I am a part of an intra-college FOSS initiative called FOSS@Amrita. Developing small but useful things that improve lives of the common and affects the open-source community has always been my passion. I believe that with the right technology applied, it can do wonders for the lives of people. Furthermore, I have completed the Google Summer of Code\u201917 with The Wikimedia Foundation and was also a Google Code-In mentor for the same community. Worked on the project that aimed at the improvement and enhancement of the ProofreadPage Extension and Wikisource , through important bug fixes that are left as backlog and implementation of significant features that would make it more user-friendly. This was done so that the extension and Wikisource become easier to use and are raised to the contemporary Mediawiki standards. Apart from this, I'd love to \u200bexpress\u200b \u200bviews\u200b on\u200b \u200bcontemporary\u200b \u200bworld issues,\u200b \u200bget\u200b to know\u200b \u200bthe\u200b \u200bdifferent dimensions\u200b of\u200b \u200bit and analyze the\u200b \u200bmultiple\u200b\u200b ways\u200b \u200bin\u200b\u200b which\u200b \u200bthe\u200b \u200bproblems\u200b \u200bcould be rectified", + "Speaker Links": "Linkedin Blog Gerrit GitHu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Amrit Sreekumar (~amrit95)", + "created_on": "03 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-leveraging-python-in-tableau~dGAKa/", + "title": "Data Analysis: Leveraging Python in Tableau" + }, + "102": { + "Content URLs": "We will share the Github repository for the workshop here couple of weeks before the conference", + "Description": "\"Our Business Is Our Business None Of Your Business\u2026\" Yes, they wish, but we want to know everything about Bollywood! Who is more popular, Katrina Kaif or Deepika Padukone ? When budget is not a problem, do producers prefer Shah Rukh Khan or Salman Khan ? Which city in India is home of the most active actresses and actors? What movie is the most similar to PK ? And lots of other questions. Do you want to know the answers? And even better, would you like to discover them yourself by using Python and popular libraries such as pandas, Gensim and scikit-learn? And cutting-edge data science techniques? Join us for a workshop full of insights where you will be able to answer your own questions while learning the most advanced Python libraries and algorithms. The workshop is designed for Python programmers new to data science. Everybody is welcome, but data analysts and people experienced with pandas will find some parts quite basic. What will we cover? Loading, merging, cleaning and analysing your data with pandas Advanced data visualisation with Bokeh Embeddings and natural language processing with Gensim Forecasting with statsmodel Basic machine learning with scikit-learn All this while answering the questions above, and letting you answer your own questions", + "Last Updated": "02 Jun, 2018", + "Prerequisites": " Laptop with Anaconda3 installed Clone of the workshop repository Knowledge of Python Good knowledge of Bollywood desirable :)", + "Section": "Data science", + "Speaker Info": "Himanshu is the organiser of Kanpur Python and PyData Kanpur. Free and open source software enthusiast, and passionate about Python and data analysis, He is currently working for KanpurFOSS organization which organize free technical workshops in India. Yai Workshop\u2026 Data Analysis Ke Workshop Hai\u2026 Kisi Ke Data Analysis sikha kar He Khatam Hoge... Marc (known online as datapythonista) is a data scientist from London. Pythonista since 2006, pandas contributor, and organiser of the London Python Sprints group. Worked for companies like Bank of America, Tesco, Unilever or NTT Communications. Regular speaker at PyCon and PyData conferences. His favourite actor is Aamir Khan, but wouldn't mind teaching Python to Asin", + "Speaker Links": "Himanshu : https://twitter.com/IHackPY | https://www.slideshare.net/HimanshuAwasthi14/ | https://speakerdeck.com/johim9493 Marc : https://twitter.com/datapythonista | https://www.linkedin.com/in/datapythonista/ | http://datapythonista.github.io", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Marc Garcia (~marc)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decoding-bollywood-with-python-and-data-science~eEyWe/", + "title": "Decoding Bollywood with Python and data science" + }, + "103": { + "Content URLs": "PyCon India 201", + "Description": "What's a good way to Set up many development version(s) ? Developers need consistent isolated development environment, running exact same container(s) as what runs in production , automated test tools, package, ship & deliver. Let's touch features of docker to make it run for Python programs/web apps. Outlines First 5 minutes, I'll be talking about current developers need and present solution. Next 5 minutes, what is docker and how it can solve these problems. Next 10 minutes, I'll be demonstrating, how I use docker for in my Python development tasks (Python library, Python web app). After 20 minutes I will have delivered the enough knowledge for the docker, and next 5 minutes I will let the audience know about the some advance features in docker that they can learn from various resources, to get the maximum power of docker. Q/A along with this. Detail description Basic terms of docker Docker Container Docker Image Dockerfile Docker Compose Docker Repository and Docker Hub Docker Daemon, Docker Client and Docker Engine Docker Swarm Docker Machine Docker for Developers Reproducibility and Developer teams Isolation Security Environment Management Continuous Integration Creating Custom Images and Containerizing Your Application Sample Dockerfile to build an image of an small python program. We will run the image and play with this container. Using Docker Compose in development adds an important constraint: your services are not on the same machine anymore. Container Logs Learn how you can see or capture the logs of the container(s) and services. Docker for Python developers In this section I will demonstrate, how you can setup a development version of real world software.\nI will setup the development version. After creating an image and running it in a container, I will show volume sharing techniques as well. Audience will understand how I have created an consistent isolated container, integrated CI which is easy and fast to ship. Docker for Python Web applications Django and Flask web app will be run under the docker container, different environments in one system. We will learn how to use microservices and advantages of making services using docker-compose. Advance and new features of docker Now audience have understood the docker and they can learn many more powerful features of docker. I will share some good resources and let them know about docker swarm, docker machine, Dealing with Logs, etc ", + "Last Updated": "02 Jun, 2018", + "Prerequisites": "Prior experience with docker is not a necessity but having some exposure to Python development, version control system, Unix System is recommended. At the starting talk basic developers need, basic docker features will be covered. So starting point, anyone (entry/intermediate) can understand the docker concepts. Slowly moving to docker for developers, expert Python developers will get ideas to use docker in their development system and how they can solve most of the development conflicts because of using having multiple environments", + "Section": "Developer tools and Automation", + "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", + "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Shekhar Prasad Rajak (~Shekharrajak)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/containerizing-your-application-is-the-solution~dBvQd/", + "title": "Containerizing Your Application is the solution" + }, + "104": { + "Content URLs": "Slides will be updated soon. Django2 release note", + "Description": "Django is one of the most used Python framework in the world of Python and is even used more than Tensorflow(Stack Overflow 2018 Developer Survey). Django is an excellent web-application framework to build scalable, extensible and high-performance web applications that can serve hundreds of thousands of requests per second -- while keeping the development cycle optimal and maintaining the sanity of developer mind-space. The latest version of Django 2.0 has been just released this year. The new Django 2.0 begins a new era without any backward incompatible changes except the removal of Python2.7 in latest version and it aims to completely remove Python2 support for Django environment when LTS Django 1.11 expires in 2020 with Python2 . This release also starts the Django using the loose form of semantic versioning. Django 2 has introduced a lot of major changes like : SImplified URL routing syntax Performance optimisation and improvements Mobile Friendly Admin site Newer functions like Windows and more modified aggregate functions More stricter schema Made Mysql isolation as read committed Talk Outlines What is Django and why use Django? Django design patterns - MTV kind of MVC How does Django works? Simplified URL routing syntax in Django2 Other new features in Django2 When should you move your old project to Django2 and Django release Cycle Tips on converting your legacy code to Django2 This talk aims to provide some general insights on Django and latest Django2 version. Apart from being a talk focussed exclusively on Django, the talk aims to give be an introduction to what server side programming is and in general to Web Development ", + "Last Updated": "02 Jun, 2018", + "Prerequisites": " Python Django (preferable) After all this is a Hitchhiker\u2019s guide, this talk will focus on a general introduction to Django and don\u2019t be afraid all the noobs in Python and Django will welcomed and be accommodated in this talk", + "Section": "Web development", + "Speaker Info": "Kurian is currently in his sophomore year, pursuing an undergraduate degree in Computer Science from Govt. Model Engineering College, Kochi. He has interned in multiple startups like Entri.me, WiM as a product intern developing products using Python and web frameworks like Django. He is also a Open source Enthusiast and have contributed to multiple organisation like Zulip , FOSS Asia. He is an active member of FOSS club in his college(FOSSMEC) and of Kochi Python Club(Python Meetup Group of Kerala)", + "Speaker Links": "Github LinkedIn Medium Twitte", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kurian Benoy (~kurianbenoy)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-hitchhikers-guide-to-django-2~aAr9b/", + "title": "The Hitchhiker\u2019s Guide to Django 2" + }, + "105": { + "Description": "The goal of this talk is to explain this quote : \u201cYou shall know a \u2018word\u2019 by the company it keeps!\u201d In this talk, we will go through as to how to build a model for text summarisation (from scratch) and its possible applications in the real world scenario. An intuitive explanation will be provided (the talk would not be all mathematical!) as to how to do the data preprocessing for a large dataset and provide a reasoning as to why we choose a specific model for training. We will also talk about how certain Python libraries make it easier to structure a machine learning pipeline. We will also walk through the best practices and various caveats while building these kinds of complex models and how to circumvent these", + "Last Updated": "02 Jun, 2018", + "Prerequisites": "The prospective audience should have a basic understanding of neural networks and natural language processing", + "Section": "Data science", + "Speaker Info": "Harshdeep is currently a student at the University of Manchester pursuing his Bachelors in Artificial Intelligence and is interested in Natural Language Processing. My experience with Python started at IBM Bristol where I worked for a year developing the compliance automation tool. After that, I worked on my final year research project using Python which was based on finding summaries and sentiment of news articles. I have previously spoken at PyCon APAC in Malaysia last year in August which was a talk about the basics of Neural Networks. After university, I will be working with some early stage startups in India related to AI and Aviation", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Harshdeep Harshdeep (~harshdeep)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/text-summarisation-made-fun~azAqe/", + "title": "Text summarisation made fun!" + }, + "106": { + "Content URLs": " Initial version of slides (will update regularly and mark it complete once done)", + "Description": "Abstract Being one of the most used collaboration tools used by software engineers and data scientists, \"Jupyter Notebooks\" are transforming the way \"data science\" is happening in the industry. Started as a smart Python interpreter, the Jupyter project has grown into a common platform that supports the development of data science and scientific computing tools across multiple programming languages. This talk is aimed at understanding the technical internals of Jupyter project. Agenda A brief introduction to Jupyter How is it different from IPython Component architecture Kernel Frontend Communication protocol used between a frontend and kernel How does a kernel work Magic commands How to create one Let's create a Jupyter frontend Wait! What if you can use Slack as a Jupyter notebook? Jupyter, Interactive computing, and possibilities What will you learn Process that powers an interactive Jupyter session Do you know how does the tab-completion work? Extending the capabilities offered by Jupyter ecosystem for a custom use-case We will learn how to create magic commands and frontend Black magic", + "Last Updated": "02 Jun, 2018", + "Prerequisites": " Basic understanding of Python, comfortable with functions/classes Experience working with Jupyter/IPython notebooks (Optional) Interested in knowing how stuff works", + "Section": "Data science", + "Speaker Info": " Tech & Product at Vernacular.ai Data-driven journalism practitioner Featured in Tech in Asia and Global Investigative Journalism Network Contributor to Go programming language", + "Speaker Links": " Website GitHub Twitter", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Pravendra Singh (~pravj)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyter-notebooks-internals-and-extension~dyz6e/", + "title": "Jupyter Notebooks: Internals and Extension" + }, + "107": { + "Content URLs": "Programs in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=", + "Description": "Mention of \u201cCancer\u201d evokes words like tumor, chemotherapy, hair loss, vomiting and pain. Interestingly our knowledge and thereby cancer treatment has changed radically in the past few years and is changing rapidly every passing day. In 2003, human genome was sequenced and for the first time we could read entire human DNA from end to end. Interestingly DNA and cancer are deeply connected. Scientists deciphered that always a change in DNA (mutation) led to cancer (oncogenic mutation). Cigarette smoking, alcohol, pollution etc only led to such DNA change (oncogenic mutations). This led to numerous diagnostic companies starting to extract and sequence tumor DNA, to detect the root cause of each patient tumor. While drug companies formulated new drugs that targeted specific DNA change (mutation). These were called targeted therapies which were very different from chemotherapy in being very precise, less toxic, less side effects and they could be taken orally just like any regular pill. Thus, an oncologist (cancer doctor) could treat a cancer tumor effectively if s/he knew the precise location of mutation in the entire patient tumor DNA and the drug that targeted it. Suddenly oncologists in India and elsewhere, found themselves struggling to comprehend tumor DNA and the technology around it. Already burdened with tomes of ever changing patient treatment guidelines, now they were needed to integrate tumor DNA information to make accurate treatment decisions. For eg. NCCN (National Comprehensive Cancer Network, USA) which publishes treatment guidelines for all cancer for oncologists across the world, published lung cancer guidelines that is 271 pages long. To this, add the complex data of patient\u2019s tumor DNA, various mutation databases, clinical trials and research papers. Modern day oncologist are often overwhelmed. They need tools to simplify and hasten their decision making. I am a molecular biologist who understands the tumor DNA and the technologies around it. As Chief Scientist (molecular oncology) of Neuberg diagnostic lab, I also write patient DNA reports that guide oncologists to take treatment decisions. While meeting various oncologists and marketing them different DNA tests for different type of cancers, I got acutely aware of the problems oncologists faced. To simplify their decision making, I created algorithms that combined patient\u2019s clinical history, histo-pathology data, molecular test decisions, mutational databases and NCCN guidelines. Subsequently I coded these integrated and complex decision algorithms as Python programs that can be executed from a browser. They are available for free and oncologists are/can use it.\nPrograms in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=0 \nMy article on need of Python programing for cancer treatment: https://sites.google.com/view/molecularpathology/programming/is-it-time-for-precision-medicine-app?authuser=", + "Last Updated": "01 Jun, 2018", + "Prerequisites": "Interest in using programing to resolve healthcare problems in India", + "Section": "Others", + "Speaker Info": "I am a PhD in Biochemistry with significant research experience at the University of North Carolina at Chapel Hill, in the areas of molecular oncology, cardiovascular biology and biology of infectious diseases. Currently, I prepare molecular diagnostic reports for cancer patients as Chief Scientist (Molecular Oncology), Neuberg Center of Genomic Medicine, Ahmedabad", + "Speaker Links": " Molecular pathology of cancer: https://sites.google.com/view/molecularpathology/home?authuser=0 The DNA Labs: https://sites.google.com/site/thednalab/ , https://www.facebook.com/TheDNALab , https://www.youtube.com/channel/UCf2HKt1vgjhe8MXbvMSwELg/feed", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "siddharth srivastava (~siddharth40)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/helping-oncologists-to-take-complex-decisions-in-treating-cancer~axylb/", + "title": "Helping oncologists to take complex decisions in treating cancer." + }, + "108": { + "Content URLs": "share here soon", + "Description": "Flutter is Google\u2019s mobile app SDK for crafting high-quality native interfaces on iOS and Android in record time. So lets create web services for Flutter app using python/Flask framework", + "Last Updated": "01 Jun, 2018", + "Prerequisites": " Basic of Python Knowledge of Webservices REST and JSON Hello world Knowledge of Mobile App. Familiar with Android Studio and Pycharm", + "Section": "Web development", + "Speaker Info": "I am opensource lover. I love to explore opensource technologies for mankind. I am organiser of \"Arduino and IoT ,Kanpur\" . I teach kids under coderdojo program", + "Speaker Links": " https://twitter.com/vivdroid https://github.com/vivekaris", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/write-python-web-services-for-flutter-app~avw8b/", + "title": "Write Python Web services for Flutter App" + }, + "109": { + "Content URLs": "https://github.com/vivekaris/firebase-io", + "Description": "Now Days Internet of Things are Trending technology for every makers. Lets Build Python based Automation controller for any Hardware (tested on Raspberry Pi and Node MCU).\nWe will use firebase as a data storage and Action handling.\nWith the help of Firebase Realtime Database ,we can control hardware from any geographical location", + "Last Updated": "01 Jun, 2018", + "Prerequisites": " Keen to learn Basic of Python Knowledge of PIP Knowledge JSON Basic Knowledge of C for Arduino(Node MCU Programming) Laptop with Linux/Mac/Win 7 onwards. Node MCU v3 2 LED with 4 Jumper Wire Internet Connectivity Google Account enter code her", + "Section": "Web development", + "Speaker Info": "I am opensource tech lover", + "Speaker Links": " https://github.com/vivekaris https://twitter.com/vivdroid http://makerspacekanpur.com/blog/", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-firebase-build-amazing-iot-application~erp2b/", + "title": "\"Python and Firebase\" Build Amazing IoT Application" + }, + "110": { + "Content URLs": "Kubernetes Docker Azure Kubernetes Service aka AK", + "Description": "Kubernetes is considered as the new Kernel of the Cloud. It's a distributed computing platform letting users not have to care about infra and helping them concentrate mainly on business logic. By having your web app deployed on a kubernetes cluster you can make sure your app is highly available, and can fail-over when there's a problem. One of the main goals of the Kubernetes project is to democratize distributed computing. With Kubernetes being open source, Companies do not have to redo the mundane task of writing a distributed computing platform to achieve high availability, automated deployment, scaling and management of your applications. Kuberentes will take care of that for you. Kubernetes is also considered as a container orchestrator, as it manages containers to achieve the above said goals. In this talk: We will first write a basic python web app. Next, We will go through what a container is Containers are becoming the de-facto way of deploying applications as they remove the complexities of dependency management,etc. Running apps on Individual Containers provide the isolation almost to that of a Virtual Machine without having the overhead of having individual Kernels as they all share the host kernel. Isolation is provided by using kernel level features like cgroups and namespaces. We will containerize the application using docker and push it to a Container Registry. Once we have the image deployed to a registry, this image will be used to create instances i.e containers of the web app. We will next create a kubernetes cluster on Azure, all along going through what a Kubernetes cluster is, and its components. We will then deploy our python web app onto the cluster. Now As we have our python web app up and running, We can then do some experiments on how Kubernetes self-heals the application when a node goes down,etc. After that I will run down some points on where Kubernetes is being\n used, its impact. To Finally answer the question, Is Containers and Kubernetes worth all the Hype ? This talk will be demo focused, But before going to a demo we will have some slides explaining the overview of the components and how they work. By the end of the talk, Audience will have a brief overview of what containers and kubernetes are, and how to deploy a web app on Kubernetes. From this overview, Audience can start digging deeper online and know more", + "Last Updated": "01 Jun, 2018", + "Prerequisites": "Understanding of Python. Basic Understanding of Deployment of a web app. It's good if you already have some basic understanding on what containers and kubernetes are", + "Section": "Developer tools and Automation", + "Speaker Info": "Tarun Pothulapati is currently pursuing his B.Tech in Computer Science and Engineering in Hyderabad.\nHe is a Tech Enthusiast and codes mostly in Python and C#. He is very much interested in distributed computing platforms like Kubernetes and Microsoft's Service Fabric which are trying to democratize \nthe technology which was before only a privilege of the Big-Tech firms.\nHe spends most of the time learning about it and trying to contribute to their repositories. He is also very enthusiastic about sharing the knowledge about these cutting edge technologies.\nTarun has also worked on many projects on chatbots, Web apps etc and have won some\nhackathons held by IEEE, IBM & Amazon and he was one of India's 40 finalists of AICTE's \nStartup Contest 2017", + "Speaker Links": "Twitter Github Linkedin Websit", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Tarun Pothulapati (~Pothulapati)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deploying-a-python-web-app-onto-a-kubernetes-cluster~bqo7e/", + "title": "Deploying a Python web app onto a Kubernetes Cluster" + }, + "111": { + "Content URLs": "---In progress, will be ready to share by July last week can make it to July first week if urgent--", + "Description": "Signal processing is a fundamental part of ECE and is also used in many other fields. Students for years have been using expensive Matlab for learning this skill. The talk/workshop/interactive session can be used by students to get a better understanding of signal processing and implementing it with python. The use of python language in signal processing is preferred as it is portable, easily available and fast to deploy Topics covered include but are not limited to Sound and Signals Noise Fourier Transform Filtering Modulation Sampling LTI Systems The talk will be at a simple level so that even a high school student can understand signal processing and implement it. If time allows another session on using python to solve electrical networks and visualizing them can also be implemented", + "Last Updated": "31 May, 2018", + "Prerequisites": "Basic knowledge of python and Signals and systems (WikiPedia knowledge is enough.) NumPy (Used for array manipulation ) SciPy (For computation) matplotlib (For plotting various signals etc.)", + "Section": "Others", + "Speaker Info": " Speaker is a 3rd year ECE student with experience in python for numerical computations, web development and most importantly signal processing , and electrical networks Interested in using python in modern electronics like the pyboard and raspberry pi and advocates the use of python over expensive software. An avid python user, always tries to find a way to implement given task in python and believes that where there is a task to be done there is a suitable python library.", + "Speaker Links": "LinkedIn Faceboo", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Abel Joseph John (~abel91)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/digital-signal-processing-with-python-and-applications-in-audio~epnQb/", + "title": "Digital Signal Processing with Python and Applications in Audio" + }, + "112": { + "Content URLs": "https://www.py4e.com/\nhttps://www.coursera.org/specializations/pytho", + "Description": "This session will take a look at the \u201cPython for Everybody\u201d series of courses on the Coursera platform. This course has impacted over 1.3 million students over the last five years. We will look a the history and goals of the course and how the course works to create a learning community. We will show how the free open educational resources (OERs) and book associated with the course have been used by teachers, students, and courses around the world to form a network of educational activities centered around Python. We will also cover briefly the Tsugi (www.tsugi.org) software that is used to build the learning assessments and distribute the OER materials in a way that enables maximum reusability of the materials for other teachers", + "Last Updated": "31 May, 2018", + "Prerequisites": "No pre-requisite", + "Section": "Core python and Standard library", + "Speaker Info": "http://www.dr-chuck.com/\nhttps://www.si.umich.edu/people/charles-severance\nhttps://twitter.com/drchuck/\nhttps://github.com/csev\nhttps://www.sakaiproject.org\nhttps://www.tsugi.org\nhttps://www.slideshare.net/cse", + "Speaker Links": "http://www.dr-chuck.com/dr-chuck/resume/index.htm Charles is a Clinical Professor and teaches in the School of Information at the University of Michigan. He is the Chair of the Sakai Project Magament Committee (PMC). Previously he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project and worked with the IMS Global Learning Consortium promoting and developing standards for teaching and learning technology. Charles teaches ten popular MOOCs and two specializations to students worldwide on the Coursera platform: Internet History, Technology, and Security, Web Applications for Everybody, and Python for Everybody and is a long-time advocate of open educational resources to empower teachers. Charles was the editor of the Computing Conversations column in IEEE Computer magazine from 2011-2017 that features a monthly article and video interview of a computing pioneer. Charles is the author of several books including: Python for Everybody, Sakai: Building an Open Source Community\", \"Using Google App Engine\", from O'Reilly and Associates and the O'Reilly book titled, \"High Performance Computing\". Charles has a background in standards including serving as the vice-chair for the IEEE Posix P1003 standards effort and edited the Standards Column in IEEE Computer Magazine from 1995-1999. Charles is active in media as a hobby, he has co-hosted several television shows including \"Nothin but Net\" produced by MediaOne and a nationally televised program about the Internet called \"Internet:TCI\". Charles appeared for over 10 years as an expert on Internet and Technology as a co-host of a live call-in radio program on the local Public Radio affiliate (www.wkar.org). Chuck's hobbies include off-road motorcycle riding, karaoke and playing hockey. Charles has a B.S., M.S., and Ph.D. in Computer Science from Michigan State University", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Charles Severance (~charles)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/inside-the-worlds-largest-python-course-on-coursera~bomYe/", + "title": "Inside the World's Largest Python Course on Coursera" + }, + "113": { + "Content URLs": "Slides: https://docs.google.com/presentation/d/1z-pWhSOERi-vl_wPLVsdCNpl54G3IA0D8K7ve13HFZI/htmlpresent Source code for the examples: https://github.com/minhajuddin/collaborative-canvas-demo", + "Description": "Outline/structure of the Session\n1. An introduction to Elixir\n2. An introduction to Phoenix\n3. Outline and design overview of our canvas app\n4. Implementing our app\n5. Deploying it to a server\n6. Q&A Learning Outcome\nLearn how easy it is to use Elixir and Phoenix to create real time applications at a massive scale", + "Last Updated": "31 May, 2018", + "Prerequisites": "Basic understanding of the web applications", + "Section": "Web development", + "Speaker Info": "I am a very passionate programmer. I am also the CEO of a Micro ISV, Cosmicvent Software. I have been in the software industry for 10 years.I love writing code and have worked with Elixir, Golang, Ruby, .NET and Javascript among other technologies", + "Speaker Links": "Follow me on twitter https://twitter.com/minhajuddin Follow me on GitHub https://github.com/minhajuddin/ My Blog: https://minhajuddin.com/ Previous presentation: https://www.youtube.com/watch?v=WabGxSZhPE", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Khaja Minhajuddin (~minhajuddin)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-collaborative-canvas-using-elixir-and-phoenix~enl5b/", + "title": "Building a collaborative canvas using Elixir and Phoenix" + }, + "114": { + "Content URLs": " Postman Jmeter Burp", + "Description": "API testing is fun! For a small team of 7 (Dev + QA), having dedicated resources to do functional, Security and Performance of the APIs is close to impossible.\nHence, We came up with a framework which automates the process of API testing covering the basic functionality, Security, and Performance so that we don't miss out testing any of these layers. I would cover up the basics of Postman, Burp and JMeter components used for the framework", + "Last Updated": "31 May, 2018", + "Prerequisites": " Interest in automating the Webservices testing :)", + "Section": "Developer tools and Automation", + "Speaker Info": "A tech enthusiast who has 7+ years of experience in the Software Testing in Startups. I love to explore new technologies and automate mostly everything which takes more time. A strong believer in processes. Love testing Webservices. Would love to share the experience we had in building the framework for API testing", + "Speaker Links": "https://www.linkedin.com/in/sarala-v-620b0b1a/ https://twitter.com/saralaVeerann", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Sarala V (~sarala)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-rest-api-testing-for-functional-security-and-performance-testing~bmkRe/", + "title": "Automating REST API testing for functional, security and performance testing" + }, + "115": { + "Content URLs": "https://github.com/radhikascs/cryptography-pytho", + "Description": "This talk is meant for the end users who aspire to learn basics of cryptography and its implementation in real world projects. \nThis tutorial is also useful for networking professionals as well as hackers who want to implement new frameworks instead of following traditional approach", + "Last Updated": "31 May, 2018", + "Prerequisites": "It is expected that the end user should know basics of cryptography and algorithms. The knowledge of cryptography algorithms becomes a cakewalk for a user who reads this tutorial", + "Section": "Core python and Standard library", + "Speaker Info": "A pinch of optimism with a blend of hard work and focus defines Radhika Subramanian. She works as an Academic Writer and Tutor with various organizations. She has completed MSc(CA) from Symbiosis International University. She also includes a passion for research work in Artificial Neural networks and it's technologies. She is currently working as an Author with BPB Publications and Apress Media LLC", + "Speaker Links": "https://www.linkedin.com/in/radhika-subramanian-486a771a/ https://www.unanth.com/tutor/radhika-subramanian-14135", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Radhika Subramanian (~radhika14)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cryptography-and-python~elkjd/", + "title": "Cryptography and Python" + }, + "116": { + "Content URLs": "To get a feel of Numba see - first step", + "Description": "Thinking parallel is an art, applying it is another. While applying it, the first hurdle for us is to move to another language like C or C++ to get performance gains. \nWhat if we write simple python code and someone magically helps us gain C like performance? Sounds like a dream, it ain't ! . Enter Numba :) In this workshop you will - Witness how Numba help you get insane performance gains to your code without changing a line of it. Learn to harness the power of your GPU/CPU for performing math intensive computations. See how it compares to other libraries like Numpy , etc. and how they can complement it. Use Numba to parallelize the very famous Particle Swarm Optimization Algorithm Flow of the workshop - Where to use Numba in your code - (time profiling, small examples) The wow of Numba in my life, a small example of how it helped in my research Introduction to jit complier, internals of Numba Introduction to the Particle Swarm Optimization (this is where the fun starts :) ) Code up basic PSO Profile PSO to find pain areas Try to speed up the pain areas using Numba Kick up a hierarchical swarm (just for fun, if time permits) QA Session", + "Last Updated": "31 May, 2018", + "Prerequisites": "numpy, matplotlib, jupyter, ipython, numba, line_profiler , llvmlite. A more specific description is available her", + "Section": "Others", + "Speaker Info": "Hi, I am Shubham Bhardwaj. I am currently a Research Intern at Jio CoE for AI/ML and a final year undergrad at VIT University, Vellore. I am a die-hard pythonista. \nMy daily work involves developing and implementing algorithms for interesting problems in AI. Apart from this I am also an organizer at GDGVIT, I love dev :) and contribute to various open source organisations, organise workshops, promote python whenever I can", + "Speaker Links": " LinkedIn Github", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Shubham Bhardwaj (~shubham0704)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/leveraging-the-power-of-your-gpucpu-for-math-intensive-computations-with-python~bkjJa/", + "title": "Leveraging the power of your GPU/CPU for math intensive computations with python" + }, + "117": { + "Content URLs": "The Magenta Project Music Composition using Recurrent Neural Network", + "Description": "Music is mainly an artistic act of inspired creation and is unlike some of the traditional math problems. But, a sequence of specific chords and notes can be observed when we listen to music. With the recent advancements of the AI tech, sequence models are used invariably in innumerous fields, one such sequence model, LSTM( Long Short Term Memory Networks) can be used to generate melodies and beats. So, this talk is about how deep learning models, specifically LSTMs were used to produce music - catering particularly to the Electronic Dance Music Industry. CONTENTS AND ORDER OF THE TALK Learning how LSTMs help in generating music, and the concepts behind it. Preprocessing the MIDI data for the melodies and beats using MIDI packages created by the Python community. Building the LSTM network using Keras with Tensorflow as backend and understanding it. Train the network with the melodical data to create the LSTM network for melodies and same thing for beats. Generating melodies and beats(using pretrained model) and combining the two to create different type of genres of music. I am including a piece of music generated by an MIT alumnus, but I will be explaining the steps from scratch . Generated Techno Beat", + "Last Updated": "30 May, 2018", + "Prerequisites": "Tensorflow, Keras, Recurrent Networks and a Good taste in music ;", + "Section": "Others", + "Speaker Info": "I am Kumar Abhijeet, a sophomore from RV College of Engineering, Bengaluru and an AI enthusiast. I am a budding EDM producer and a python programmer as well(no doubt in that). I have worked with small AI startups in building their frameworks. I am an open source contributor and a GSOC aspirant. I have always loved the idea of mixing technology with regular phenomena, which I will be doing with music. I love going to meetups and meet different kinds of communities to learn from them", + "Speaker Links": "LinkedIn ID Github Lin", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kumar Abhijeet (~kumar80)", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-beats-and-melodies-with-lstms-using-python-and-tensorflow~ejgya/", + "title": "Generating beats and melodies with LSTMs using Python and Tensorflow" + }, + "118": { + "Content URLs": " https://www.djangoproject.com/ http://www.celeryproject.org/ https://sensu.io/", + "Description": "Monitoring is a key aspect for any business. It enables us to find and be notified about the problem way ahead our customer notices it, which enables us to keep our businesses running and making customers happy. I will be talking about how we SREs at Opentable Inc, tries to solve the good old monitoring problem, sensu with puppet, using Django, Sensu and Celery. If you are fed up with the limitations of what current monitoring tools offer, this is the talk you wanna look out. At the end of talk, audience would have an alternative approach for monitoring using python. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce monitoring and how we use currently at Opentable Inc. Describe limitations we have with our previous monitoring stack. Alternate new generation monitoring architecture using python tools Django and Celery, keeping sensu intact. How we developed a site using Django, which help us to maintain the checks and add new check definition. How we used Celery distribution system to run checks on multiple worker nodes and send results to sensu. I will talk about how we scaled celery worker nodes by setting up different queues, and prioritising the tasks and by using Flower.", + "Last Updated": "30 May, 2018", + "Prerequisites": " Basic knowledge of Sensu. Basic knowledge of Django and Celery. Will to learn", + "Section": "Developer tools and Automation", + "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", + "Speaker Links": "https://www.linkedin.com/in/hari95kishore", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "hari95kishore", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-infrastructure-and-application-using-django-sensu-and-celery~e0o5d/", + "title": "Monitoring infrastructure and application using Django, Sensu and Celery." + }, + "119": { + "Content URLs": " https://github.com/errbotio/errbot http://errbot.io/en/latest/", + "Description": "The wikipedia definition of ChatOps is, a collaborative, conversation-centric way of working that brings people, discussions, bots, tools and files together in one central location: the workplace messaging app. That's it! That's what exactly I am gonna talk about. I am gonna talk about Chatops bot, Errbot which is written in python and can be used across various messaging apps like Hipchat, Slack, telegram, skype, etc. Using chatops one can automate the tedious, boring tasks and let the bot do the work for you. It also enables various engineering teams to collaborate and exchange information easily at one place: their official messaging app. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce chatops - culture, uses, possibilities. I will talk about the possible scenarios where we could use chatops in our daily tasks. I will then introduce Errbot and its plugin architecture. Tell audience about various features of errbot and its builtin plugins. Demonstrate errbot to audience by creating a command and using it in Slack. How to set up a alternate storage for errbot. I will conclude the talk explaining the ACLs(Access control List) in errbot.", + "Last Updated": "30 May, 2018", + "Prerequisites": " Basic Python Passion for automation Will to learn", + "Section": "Developer tools and Automation", + "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", + "Speaker Links": "https://www.linkedin.com/in/hari95kishore", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "hari95kishore", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatops-using-python-bringing-developers-and-operations-together-making-tasks-easier~e9AJe/", + "title": "Chatops using Python - Bringing developers and operations together, making tasks easier!" + }, + "120": { + "Content URLs": "https://github.com/aj-jeste", + "Description": "Google Cloud Platform Deployment Manager (GCP DM) allows you to codify your infrastructure with minimal setup, just need to download the gcloud library and you're off to the races. While its simple to get started with GCP DM, its a whole 'nother ball game to write extensible and reusable DM code. In this talk I will show you how to scaffold your code into two distinct groups: configs and templates. By separating these out you can reuse the same templates across multiple deployments with different configs and make your codebase a little bit smaller. How to write a basic DM deployment. Convert the basic DM deployment into a template. Launch multiple deployments with different configs but same template. Create custom helper functions in DM Best practices when using DM", + "Last Updated": "30 May, 2018", + "Prerequisites": "Understanding of Google Cloud Platfor", + "Section": "Developer tools and Automation", + "Speaker Info": "As a freelance Site Reliability Engineer and Cloud Architect, AJ has traveled all over the world helping startups setup and manage Cloud infrastructure. He has also architected and deployed large Hybrid on-prem/cloud infrastructure for existing well established companies that wanted a taste of the cloud but needed to keep their physical data-centers as well. This is his 11th year as a SRE/CA and has automated, scaled and monitored infrastructure anywhere from 150 to 3500+ nodes, both physical and virtual. Currently he is looking for his next challenge, perhaps its this pycon talk. Brought up and currently lives in New York City but travels all over the world in search of the best train journeys and awesome foods which seems to bring him back to India again and again", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "aj", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-cloud-platform-deployment-manager-scaffolding~b8zje/", + "title": "Google Cloud Platform Deployment Manager Scaffolding" + }, + "121": { + "Content URLs": "I will share the slides after my talk as a Github repository", + "Description": "If you are working in the field of research than you might be wondering about symbolic solutions which must be needed while working in such arduous fields like Mechanical Engineering or Computer Science or Quantum Mechanics. Sympy is the solution for that. Sympy deals with the computation of mathematical objects symbolically. This means that the mathematical objects are represented exactly, not approximately, and mathematical expressions with unevaluated variables are left in symbolic form. This talk will cover Introduction and Uses of Sympy Library", + "Last Updated": "30 May, 2018", + "Prerequisites": "Basics of Python is good. \nDon't know Python? It's still okay. You will definitely find something new", + "Section": "Core python and Standard library", + "Speaker Info": "Nikunj Parmar is a Sophomore year student at Nirma University. His major field is Flexible Robotics. He has been working with Python for last 2 Years as a Researcher. As a Junior Undergraduate student, He has worked on many projects focused on Robotics, Machine Learning, and Core OS Programming. His interests lie in the fields of Robotics, Design and Control Engineering, Computational Engineering, and its applications in a broad range of circumstances", + "Speaker Links": "https://www.linkedin.com/in/nikunj-parmar-b87739138/ https://github.com/nikunjparmar82", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Nikunj Parmar (~nikunjparmar828)", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sympy-symbolic-computation-with-python~b6xOe/", + "title": "Sympy : Symbolic Computation with Python" + }, + "122": { + "Content URLs": "https://docs.google.com/presentation/d/1PZ56AYSH6GZ8s-V8rfxHuZ16UCmDg03Y1L2EiTCBiUs/edit#slide=id.p \n(Subjected to changes, not final one)", + "Description": "Talk is about how python is useful in web development, what are the most powerful and popular python frameworks used i.e., Django, Pyramid, Flask and how they are used in making web applications. My talk covers : What a web framework means Why to choose python frameworks over the normal other frameworks Explanation on Django, Pyramid, Flask. Which framework should be chosen based on dependencies. Starting Web development with python. Django, Pyramid, Flask will be explained in short with the help of small code snippets. Examples of organizations using these frameworks will be given. Uses of one framework over the other will be told in detail", + "Last Updated": "29 May, 2018", + "Prerequisites": "No prerequisite is required. Desire to learn is enough to attend this talk", + "Section": "Web development", + "Speaker Info": "About Me I am Jameer, a third year Computer Science and Engineering undergrad at Amrita Vishwa Vidyapeetham, Kerala, India. I love to code in Python. So, I started my open source career by contributing to Coala organisation. Due to my open source enthusiasm, I started learning how python is useful in Web development and using Django, Flask etc., I am also an OSFY author and published an article related to how Hadoop is being used in Big Data Analysis. I am also a ACM-ICPC Regional participant at Amritapuri. I also have a keen interest in Chatbots", + "Speaker Links": "https://github.com/JameerBabu https://www.linkedin.com/in/jameer-babu-0199a2137", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Jameer", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-web-development~e5wYb/", + "title": "Python - Web Development" + }, + "123": { + "Content URLs": " https://fasttext.cc/ https://github.com/PacktPublishing/Learn-fastText https://github.com/facebookresearch/fastText/tree/master/python", + "Description": "FastText has been open-sourced by Facebook in 2016 and with its release, it became the fastest and most cutting edge library in Python for text classification and word representation. It is to be seen as a substitute for gensim package's word2vec. It includes the implementation of two extremely important methodologies in NLP i.e Continuous Bag of Words and Skip-gram model. Fasttext performs exceptionally well with supervised as well as unsupervised learning. The tutorial will be divided in following four segments : 0-10 minutes: The talk will begin with explaining common paradigms that are present right now. Are deep learning really necessary? 10-15 mins: what are word representations 15-25 minutes: The code will be shown and explained line by line for both the models (CBOW and Skip-gram) on a standard textual labelled dataset. Showing how you can do fast prototyping with minimal code. 25-30: How to use the pre-trained word embeddings released by FastText on various languages and where to use them. Why python3 is the best language for multi-language support and a note on general deep learning using fasttext. 30-40 minutes: For QA session. ", + "Last Updated": "29 May, 2018", + "Prerequisites": " Basic python knowledge. Some Knowledge on common NLP techniques.", + "Section": "Data science", + "Speaker Info": "Joydeep is a machine learning engineer/python developer and is a Principal Engineer at Nineleaps. 5 years back he saw the Zen of Python, fell in love with Python and has been in love with it since then. Apart from his day to day work is involved in blogging and podcasting on medium and flawcode. Teaching is another passion of his and he is a python/ML trainer at tecmax", + "Speaker Links": " Medium: https://medium.com/@joydeepubuntu/latest Github : https://github.com/infinite-Joy LinkedIn : https://www.linkedin.com/in/joydeep-bhattacharjee-934a1157/ Machine Learning Podcast: https://flawcode.com/episode/show/12 twitter: https://flawcode.com/episode/show/12", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Joydeep Bhattacharjee (~infinite-Joy)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cutting-edge-nlp-classifiers-in-one-hour-with-python-and-fasttext~b4v7e/", + "title": "Cutting edge NLP classifiers in one hour with Python and fastText" + }, + "124": { + "Content URLs": "I'll be sharing the slides after my talk as a Github repository. Soon will be sharing a gist", + "Description": "Abstract One of the feature people love about Python is how it\u2019s dynamically typed. A lot of people are very reluctant on hearing this idea of static typing, they will come back bashing on what's the use of Python then when we introduce static typing in it. With the torch bearers of Python in the industry like Google, Quora, Instagram, and a lot of others retaining their stack on Python and introducing static checking there have to be some non-superficial benefits, which are worth discussing. This is Python class Employee(NamedTuple):\n name: str\n id: int = 3\n\ndef fib(n: int) -> Iterator[int]:\n a, b = 0, 1\n while a < n:\n yield a\n a, b = b, a+b Contents of the talk What's static typing Need of static typing Static typing in Python 3.6 Type checkers Demo mypy vs pytype Pros and Cons QnA and discussion", + "Last Updated": "29 May, 2018", + "Prerequisites": "Basic Python knowledge and a little overview of what is dynamic and statically typed languages", + "Section": "Core python and Standard library", + "Speaker Info": "Harshil Rastogi is working as a backend software engineer @Innovaccer, previously he has worked as an NLP Scientist @Evalueserve", + "Speaker Links": "Find me on github , ohh you like QnA forums stackoverflow . Oops were you looking for a professional platform? Okay, LinkedIn it's", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Harshil Rastogi (~harshil9968)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/static-typing-with-python-what-why-and-why-not-to~e3rAd/", + "title": "Static typing with Python. What? Why? and Why not to." + }, + "125": { + "Content URLs": "Content will be shared on github after the workshop. I will share detailed plan for the workshop in a while for the review", + "Description": "Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero ( https://deepmind.com/blog/alphago-zero-learning-scratch/ ). \nOpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms. In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding. Content Introduction to Reinforcement Learning (~ 15 mins) Introduction to Reinforcement Learning algorithms (~ 15 mins) Setting up OpenAI Gym and other dependencies Implementing simple algorithm using one of the atari games from OpenAI Gym (~ 1 Hr 15 mins) Quick overview of deep reinforcement learning and important papers in the area (~ 15 mins)", + "Last Updated": "29 May, 2018", + "Prerequisites": "Participants must be well versed with python. Some exposure to analytics libraries in python such as numpy, pandas, keras, tensorflow, pytorch would help", + "Section": "Data science", + "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company. I have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures. Since past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", + "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "saurabh1deshpande", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-reinforcement-learning-using-openai-gym~b2qMa/", + "title": "Introduction to reinforcement learning using OpenAI Gym" + }, + "126": { + "Content URLs": "https://github.com/hasura/gitkub", + "Description": "Gitkube is an open-source project that brings the developer experience of Heroku, on your own kubernetes vendor within 60 seconds . This means that you can take your python app, deploy it with a git push & scale it massively all on infrastructure you own at a fraction of the cost on Heroku. After a brief introduction, this talk will be a live-coding demo + tutorial. \nAudience members are encouraged to bring their own laptops with python apps and follow along in the talk to deploy their app. Permitting time, the talk will cover how gitkube works and how developers can contribute", + "Last Updated": "29 May, 2018", + "Prerequisites": "Python\nGi", + "Section": "Developer tools and Automation", + "Speaker Info": "Tanmai runs a startup, Hasura, where they're building tools to make it easier for developers to move to GraphQL and Kubernetes. \nThey were early adopters in the container ecosystem (pre-1.0 adopters for both Docker and Kubernetes) and have grown and contributed to the ecosystem as a company especially in India. Before this, Tanmai ran a consulting firm where their work included everything from MVPs for startups to helping one of the largest banks in the world migrate from legacy monoliths to containerised microservices. Tanmai has been building applications for over 8 years with a variety of frameworks. He is a firm advocate of democratising the power to develop applications and is the proud teacher of one of the largest tech MOOCs in India, imad.tech", + "Speaker Links": "Kubecon talk on gitkube: https://www.youtube.com/watch?v=gDGT4Gf_4JM Hasura: https://hasura.io LinkedIn: https://www.linkedin.com/in/tanmaig/ Twitter: https://twitter.com/tanmaig", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Tanmai Gopal (~tanmai)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demo-tutorial-git-push-to-deploy-your-python-app-to-kubernetes-heroku-style~e1pZd/", + "title": "Demo + tutorial: Git push to deploy your python app to kubernetes - heroku style!" + }, + "127": { + "Content URLs": "Slides Repositor", + "Description": "I'll be sharing how Python has been of help in my transformation from a hobby developer to a researcher.\nCoding and in particular, simulations are used extensively in the field of research to verify results and sometimes serve as experiments when it is physically not feasible. I'll describe step by step, how to design a real-time simulator using the example of an aerial swarm of drones in a survivor rescue scenario with the help of common Python libraries", + "Last Updated": "29 May, 2018", + "Prerequisites": " Basic understanding of Python classes and objects Enthusiasm to learn something new Love for Python", + "Section": "Core python and Standard library", + "Speaker Info": "Aniq Ur Rahman, Final year undergraduate student from NIT Durgapur. Summer '18 Research Intern at CERN GSoC '17 Intern at RoboComp Summer '17 Research Intern at SWAN Labs, IIT Kharagpur", + "Speaker Links": "Linked In Blo", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Aniq Ur Rahman (~Aniq55)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-research~eZGQa/", + "title": "Python and Research" + }, + "128": { + "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", + "Description": "Artificial Intelligence is spreading in the modern world and it has changed the face of technologies in past several years, especially Information technology. Today we are much engaged with using and developing so-called intelligent computing systems and devices. This paradigm has evolved in many sub-areas likewise Machine Learning, Deep Learning & Neural Networks. These sub-areas of AI have a greater role in solving Vision problems( e.g. image recognition, object & activity detection etc.), Speech problems( e.g. ASR, trigger word detection, language translation etc.) and many more complex problem domains with help of robust algorithms & models. this talk will be focused on Sequence Neural Models used for solving the Speech and text problems and we will be introduced to real-world applications. topics covered during the talk Introduction Recurrent Neural Networks Word embeddings Attention Models(Trigger word detection) Real World Applications", + "Last Updated": "29 May, 2018", + "Prerequisites": "Machine Learning\nBasics of Neural Networks\nPython Programming Machine Learning( Basics) Basics of Neural Networks Python", + "Section": "Data science", + "Speaker Info": "The speaker, Prashant Kumar Rai, is a final year M.C.A. student at Department of Computer Science (Pondicherry University, Puducherry) who has been working on Machine Learning and data science for quite a while. he pivoted from C to Python in his first year of Master's and currently using this for his projects. He used to blog at his leisure time. Prashant is also a course mentor for 'Sequence Models' part of Prof. Andrew Ng' s Deep Learning Specialization on Coursera, where he helps learners who need in-course assistance and feedback to successfully complete a course", + "Speaker Links": "Github Twitter Quora LinkedIn Mediu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "PRASHANT KUMAR RAI (~pkraison)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/follow-the-sequence-in-deep-way-introducing-sequence-models~bYYAb/", + "title": "Follow the Sequence in Deep way - Introducing Sequence Models" + }, + "129": { + "Content URLs": "https://docs.microsoft.com/en-us/python/api/overview/azure/?view=azure-pytho", + "Description": "Python SDK for Azure is natively available. We would explore how this SDK can be used for automation and management of Azure. Python makes it easier for IT Pros and Developers to build a rock solid DevOps pipeline with simple script", + "Last Updated": "28 May, 2018", + "Prerequisites": "Basic understanding of Azure or any cloud\nBasic Python knowledg", + "Section": "Developer tools and Automation", + "Speaker Info": "Wriju works for Microsoft as Cloud Solution Architect. He is with Microsoft for more than 13 years and total of 17 years of industry experience. He is one of the first to play with Azure in its very early stage back in 2008. His day to day job is to help a big Oil and Gas Enterprise to adopt cloud as the strategic platform. His key area of focus is to help customer migrate their line of business applications to Microsoft Azure. Application modernization is another aspect. This involves designing and implementing Serverless workflow and Microservices. He helps Architects to design and implement the solutions which are cloud scale", + "Speaker Links": "Twitter handle: @wrijugh\nBlog: https://blogs.technet.microsoft.com/wriju\nLinkedIn: https://www.linkedin.com/in/wrijughosh", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Wriju Ghosh (~wriju)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-and-automating-azure-with-python~eXXve/", + "title": "Managing and Automating Azure with Python" + }, + "130": { + "Content URLs": "I will share the slides on my github repo for the evaluation by the team in some days.\nOther content will be shared on github after the talk", + "Description": "Training a machine learning / deep learning model is one thing and deploying it to a production is completely different beast. Not only you have to deploy it to a production, but you will have to retrain the model every now and then and redeploy the updates. With many machine learning / deep learning projects / POCs running in parallel with multiple environments such as dev, test prod, managing model life cycle from training to deployment can quickly become overwhelming.\nIn this talk, I will discuss an approach to handle this complexity using Docker and Python.\nRough outline of the talk is, Introduction to the topic Problem statement Quick introduction to Docker Discussing the proposed architecture Alternative architecture using AWS infrastructure Demo", + "Last Updated": "28 May, 2018", + "Prerequisites": " Basic Python Basic Docker", + "Section": "Developer tools and Automation", + "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company.\nI have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures.\nSince past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", + "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "saurabh1deshpande", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-devops-and-ab-testing-using-docker-and-python~bWKEb/", + "title": "Machine Learning DevOps and A/B testing using docker and python" + }, + "131": { + "Content URLs": "https://speakerdeck.com/aravindputrevu/introduction-to-application-performance-monitorin", + "Description": "Often late, the time to debug that particular bug/issue occurring in production with respect to your application is increasing. It might also cause business disruption and affect your organization financially. In this talk, I'd explain how you could use Application Performance Monitoring to understand your application. Application Performance Monitoring (APM) is a solution built on Elastic Stack. APM helps you to build/store data points in Elasticsearch and visualize. It automatically collects information from your python application/service. This talk mainly targets at introducing the solution, why it is needed and what you can do with data. It ends with once data is stored within Elasticsearch, what else you can use the same data for (ex. Infrastructure Monitoring, Machine Learning)? Agenda What is APM?\nWhy APM?\nWhat it can do to your Application?\nDem", + "Last Updated": "28 May, 2018", + "Section": "Developer tools and Automation", + "Speaker Info": "Aravind is a loquacious person, who has something to talk about everything. He is passionate about evangelising technology, meeting developers and helping in solving their problems. He is a backend developer and has six years of development experience. Currently, he works as a Developer Advocate At Elastic and interact with developer community in South East Asia and India. He has deep interest in Machine Learning, Security Incident Analysis and IoT tech. In his free time, he plays around Raspi or a Arduino", + "Speaker Links": "https://aravindputrevu.in will have links to all my social accounts. I have been doing community work for last 3 years. Presenting the same talk at PyCon Bangkok on June 16-17. https://th.pycon.org/talks/#monitoring-your-python-applicatio", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Aravind Putrevu (~aravind34)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-your-python-application~eV2ze/", + "title": "Monitoring your Python Application" + }, + "132": { + "Content URLs": "https://tools.ietf.org/html/rfc7047\nhttps://github.com/openstack/ovsdbapp\nhttp://www.openvswitch.org/support/dist-docs/ovsdb-server.1.htm", + "Description": "OpenvSwitch is an OpenFlow virtual switch implementation. It has its own database implementation based on JSON-RPC (https://tools.ietf.org/html/rfc7047) to store its internal state and data.\nThis session gives an overview of this database implementation and how it used in OVN, an SDN controller from the OpenvSwitch community and in OpenStack networking. This session will look\ninto how it is different from other traditional SQL databases and the python clients available to interact with the OVSDB server and the APIs it provides to carryout the CRUD operations with the OVSDB server", + "Last Updated": "28 May, 2018", + "Prerequisites": "A basic understanding of databases", + "Section": "Core python and Standard library", + "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", + "Speaker Links": " https://numans.blog/about http://stackalytics.com/?metric=commits&release=all&user_id=numansiddique https://github.com/openvswitch/ovs/commits?author=numansiddique", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Numan Siddique (~numan)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/openvswitch-database-based-on-json-rpc~dRKVe/", + "title": "OpenvSwitch Database based on JSON-RPC" + }, + "133": { + "Content URLs": "https://en.wikipedia.org/wiki/OpenFlow\nhttps://www.openvswitch.org/\nhttps://3vf60mmveq1g8vzn48q2o71a-wpengine.netdna-ssl.com/wp-content/uploads/2014/10/openflow-switch-v1.5.1.pd", + "Description": "Networking is a key aspect of any cloud infrastructure solution. All the VMs and containers\nspawned in a cloud deployment should have seemless layer 2 and layer 3 connectivity. All this is\npossible because of virtual switching and virtual routing. This session talks about what is OpenFlow specification, OpenvSwitch (which implements OpenFlow)\nand how it is used as an important SDN layer in cloud infrastructure solutions (taking OpenStack and OVN as an example)", + "Last Updated": "28 May, 2018", + "Prerequisites": "A basic understanding of networking", + "Section": "Networking and Security", + "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", + "Speaker Links": "https://numans.blog/about/\nhttp://stackalytics.com/?metric=commits&release=all&user_id=numansiddique\nhttps://github.com/openvswitch/ovs/commits?author=numansiddiqu", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Numan Siddique (~numan)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-introduction-to-openflow-and-openvswitch~aQKGd/", + "title": "An introduction to OpenFlow and OpenvSwitch" + }, + "134": { + "Content URLs": "The repository where I have implemented concepts related to this talk https://github.com/tanayseven/http_quiz Contents for the presentation for the talk https://github.com/tanayseven/pycon_2018_python_web_app_tes", + "Description": "Abstract One of the first projects that I worked in the industry was in Flask . This talk is based on my experiences in the project with respect to the test suite and different things that I learnt in that. On the bases of those learnings, I started my own open source project on Github and enhanced on those ideas on how all the things necessary for testing are done. This is based on Flask as the web framework and all the ideas are implemented in it. The topics it covers are those things that you can do to achieve a robust set of tests in your code. Outline of the talk Pushing for 100% code coverage Making your test execution fast! The evil of \u2018over mocking\u2019 The necessity of using dependency injection Test Pyramid or Test Cone? TDDing while making changes Layers that make the web app architecture How does this map to UI testing", + "Last Updated": "27 May, 2018", + "Prerequisites": "Although most of the things are implemented in Flask, it is not necessary to know it, although it is very much recommended to know some web framework or having some knowledge of web app programming", + "Section": "Web development", + "Speaker Info": "A passionate developer with Python as his primary language. Have worked with Flask in the industry in the past. Passionate about testing and writing the code in a way that is very clean and maintainable. A strong believer in TDD and massive test coverage", + "Speaker Links": "https://tanayseven.com https://github.com/tanayseven https://www.linkedin.com/in/tanay-prabhudesai/ https://twitter.com/tanayseve", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Tanay PrabhuDesai (~tanay)", + "created_on": "27 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/having-a-robust-test-suite-for-your-python-web-app~dPKAb/", + "title": "Having a robust test suite for your Python web app" + }, + "135": { + "Content URLs": " Github reposistories: Keras_aud Audio-Vision Drive links: Content link : (Slides to be uploaded soon)", + "Description": "In this workshop, we will try to teach how to understand Deep Learning, various paths to follow, Domains to explore and the most important part- how to start with the paper selection and implementation. We will also learn how to deploy a simple model into production. This workshop aims at providing the attendees of all level a foundation of research and further prospectives in deep learning. Contents Paths and prospects in Industry and Academia (10 minutes) Difference between AI, ML, and DL. (5 minutes) Introduction to Deep Learning frameworks (Hands-on) (5 minutes) Paper selection (10 minutes) Implementation (Hands-on) (60 minutes) Understanding the dataset Feature Extraction Model Selection Data Formatting Comparison Demonstration of our work (General Overview) Audio Tagging Acoustic scene classification Visual Question Answering Publish/Deploy (Hands-on) (30 minutes) Stay Motivated Opportunites to explore The participants should have interest in Research. Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first-time learner\u2019s of AI to comprehend", + "Last Updated": "27 May, 2018", + "Prerequisites": "Preferred Basic Python concepts Basic knowledge about Machine Learning Algorithms. Preferred (but not necessary) Interest in working on Research problems Installed libraries: Keras Theano or Tensorflow", + "Section": "Data science", + "Speaker Info": "Aditya Arora and Akshita Gupta are currently final year semester exchange students at Indian Institute of Technology, Roorkee. They have been working on research problems using deep learning specifically in Audio processing and visual Q&A. Aditya is a member of various open source societies such as rust-community while Akshita has experience in Academia research and is a selected as an Outreachy intern at Mozilla 2018. They have been working in python for the past 4 years and have been moving forward working on Computer Vision and Audio processing problems", + "Speaker Links": " Twitter : https://twitter.com/imaarora Twitter : https://twitter.com/akshitac8 Linkeldn: https://linkedin.com/in/aditya-arora145/ Linkeldn: https://www.linkedin.com/in/akshita-gupta152/ Github : https://github.com/channelcs Blog : http://channelcs.github.io/", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Akshita Gupta (~akshitac8)", + "created_on": "27 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-into-the-world-of-deep-learning~aOXRb/", + "title": "Deep Dive into the world of Deep Learning" + }, + "136": { + "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", + "Description": "The era of Artificial Intelligence is moving quite rapidly across the globe. It's being used in almost every application we know , from medical diagnosis to self driving cars and it's use is still growing exponentially. But should we blindly trust AI ? Is this technology robust enough? Are we capable enough to handle it's power? In this talk we will step back for a moment and look forward about the security issues and robustness of this technology. I'll be discussing the problems we can face , the precautions we have to take, etc. with the help of a famous problem, known as One Pixel Attack ", + "Last Updated": "25 May, 2018", + "Prerequisites": " A bit of Python Some knowledge of Machine Learning And a broader perspective ", + "Section": "Data science", + "Speaker Info": "The speaker, Srajan Kant Jha, is a final year B.E. student who has been working on Machine Learning and Data Science from quite a while now. Nonetheless, he pivoted from C/C++ to Python and during the transition, has also developed some projects on the same. He used to blog at his leisure time and is still on a venture to provide the knowledge of ML and Data Science to enthusiasts through a project site. Srajan is also the City Ambassador (and one of the speakers) of AI-Saturdays, which is a community of over 5000+ students(over 100+ cities) that helps people try their hands on Deep Learning and Artificial Intelligence, free of cost. Inspite of this, he still has a lot to discover in this growing industry. (Follow him on social media to know more", + "Speaker Links": " LinkedIn : https://www.linkedin.com/in/srajan-jha Github : http://github.com/srajan23 (not much updated) Facebook : https://www.facebook.com/srajan23", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Srajan Jha (~srajan)", + "created_on": "25 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-robust-is-artificial-intelligence-ai-using-python~dNK2e/", + "title": "How ROBUST is Artificial Intelligence ? ~ AI using Python" + }, + "137": { + "Content URLs": "Fo now, I just have a gist: But I will create a proper package before the event: https://gist.github.com/dhilipsiva/3d7586e7bb941919f28afa70ccc39dd", + "Description": "Microservices are fun. But what would make them even more fun to work with, is if we can avoid duplicating the data layer across your micro-services. Django ORM is amazing. Let's share the joy of Django ORM with other languages. I have written a tool to automatically expose Django ORM to other languages and which can also generate respective client libraries in other languages. I heavily rely on Protobuf and gRPC and a lot of AST parsing", + "Last Updated": "25 May, 2018", + "Prerequisites": "You will need to know basics of: Django ORM Protobuf gRPC (or cap'n proto or any other RPC framework) Microservices", + "Section": "Developer tools and Automation", + "Speaker Info": "Wannabe Astrophysicist. Full Stack + DevOps. I code for fun and profit. Mostly in Python. FOSS. Dad of 2. Environmentalist. Atheist. Story Teller", + "Speaker Links": " http://dhilipsiva.com/ https://twitter.com/dhilipsiva https://github.com/dhilipsiva/", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "dhilipsiva Dhilip (~dhilipsiva)", + "created_on": "25 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automagically-exposing-djagno-orm-over-grpc-for-microservices-written-in-other-languages~aMKmd/", + "title": "Automagically Exposing Djagno ORM over gRPC for microservices written in other languages" + }, + "138": { + "Content URLs": "will be sharing the slides after my talk as a Github repositor", + "Description": "AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment. CloudFormation allows you to use a simple JSON or YAML file to model and provision, in an automated and secure manner, all the resources needed for your applications across all regions and accounts. This file serves as the single source of truth for your cloud environment. In this talk, I will be using Python to generate the JSON and YAML files with which AWS CloudFormation can be done. During this talk I will be covering the below points What is AWS CloudFormation? Library in Python for AWS CloudFormation. What are S3 and EC2 AWS services. Creating basic S3(Simple Storage Service) and EC2(Elastic Compute Cloud) instance using Python. Installing MySQL in the EC2 instance.", + "Last Updated": "25 May, 2018", + "Prerequisites": "Basic Understanding of Python and how to use Libraries", + "Section": "Developer tools and Automation", + "Speaker Info": "I am Mohan currently working as a Software Engineer at Amzur InfoTech Visakhapatnam.I have been in to Python Programming for the past 1 year. I have 2 years of experience as a Developer. I had worked on Data Migration. I am currently working on Data Science,MicroGrids Automation and AWS", + "Speaker Links": "www.linkedin.com/in/mohan-pavan-kumar-bailapudi-5628a296 https://github.com/MohanBailapud", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Mohan Bailapudi (~mohan57)", + "created_on": "25 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-cloudformation-with-python~dL1De/", + "title": "AWS CloudFormation with Python" + }, + "139": { + "Content URLs": "I'll share my slides after my talk as a GitHub repository", + "Description": "This talk is for Python enthusiasts who are interested in building test automation framework and test suites for REST API functional testing. It would throw a light on how to write useful, business-oriented and maintainable functional API test suites in Python on top of existing test frameworks like lemoncheesecake . Contents: About myself REST API and it's testing - A quick introduction Choosing a test framework to write your tests on Making API requests from Python Writing suite configuration and teardown code Introduction to the \"component-tests\" model for structuring the test code JSON parsing, use of matchers, asserts for writing test case validation criteria Importance of logging and reporting - How logs and readable reports can ease the job of debugging bugs found using tests Bringing everything together", + "Last Updated": "24 May, 2018", + "Prerequisites": " Python basics REST API basics Basics of test frameworks like pytest Passion for test automation", + "Section": "Developer tools and Automation", + "Speaker Info": "I'm currently working as a SDET Lead with AgroStar, India's largest agri-tech platform for the Indian farmer. I'm passionate about technology and automation, I'm willing to contribute in building robust software test frameworks accompanied with some of the best industry practices like CI/CD that would help ensuring the best possible software quality from time-to-time. The \u201calways exploring and learning\u201d attitude is something that keeps me going", + "Speaker Links": " LinkedIn Facebook Twitter", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Akshay Maldhure (~akshay61)", + "created_on": "24 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rest-api-functional-testing-with-python~aK7Ga/", + "title": "REST API functional testing with Python" + }, + "140": { + "Description": "The Talk will focus on the importance of satellite image processing with main focus on the utilisation of GDAL library to conduct various operations on satellite data. Datasets will include Optical imagery and Synthetic Aperture Radar Imagery. The power of GDAL library alongwith numpy and matplotlib will be demonstrated. Brief analysis of satellite images using python will be given", + "Last Updated": "23 May, 2018", + "Prerequisites": "Basic Knowledge of numpy and matplotlib libraries", + "Section": "Data science", + "Speaker Info": "Shubham Sharma is a Junior Research fellow currently working on a collaborative project with Calibration and Validation Division of Space Applications Centre, ISRO, Ahmedabad. He has a rich experience in handling and processing of Synthetic Aperture Radar Images. Also, he has experience in building software tools in python for satellite Image analysis", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "shubham_thb", + "created_on": "23 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/satellite-image-processing-with-python~dJKKe/", + "title": "Satellite Image Processing with Python" + }, + "141": { + "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", + "Description": "Python is a versatile, powerful, and general purpose language, its easy and clear syntax makes it very popular for the beginner as well as the advanced programmer. Malware is one of the top threats to today's digital society. Due to heavy financial loss along with other infrastructure losses, the software industry is investing hue money for malware research and at the same time due to the wide need of effective and efficient anti-malware solution, the anti-virus industry is emphasizing on malware research.\nThis talk will focus on the array of python resources (script, modules, library, frameworks etc.) available for various dimensions of malware research. During the talk, I will share my experience with various tasks or problems related to malware research and how with the use of Python, those were solved. This talk will try to draw a parallel connection with various tasks related to malware research and suitable Python resources available for achieving those tasks. The talk will be supplemented with the brief explanation of concepts and python snippets for the same. \nSome of the modules and topics that I will touch upon are: yara Accessing VirusTotal API with Python Cuckoo-sandbox Androguard pefile pyew file type filtration ClamAV and pyClamd etc.", + "Last Updated": "23 May, 2018", + "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general", + "Section": "Networking and Security", + "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", + "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "urwithajit9", + "created_on": "23 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-arsenal-for-malware-research~dGXKe/", + "title": "Python Arsenal for Malware Research" + }, + "142": { + "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", + "Description": "Malware is a serious threat to all kind of Cyberinfrastructure. Since the first known malware (formerly or generally known as Virus) there have been malware detection techniques. There is the arms race between new incoming of Malware and defense against it. Traditionally, anti-virus software uses signature-based techniques to detect malware and protect the underlying system. Due to some critical limitations of signature-based techniques, anti-virus, and security agency looking for alternative techniques and investing in machine learning based techniques for malware detection.\nThis workshop aimed to train the participants through various steps involved in building malware classifier based on machine learning algorithms. Python is very suitable for the task due to its large number of useful modules suitable for each and every step. During this workshop, following topics will be explained with proper hands-on using Python. Explanation of the topic and draw out the various required steps. Data collection: How to collect Malware and Benign samples for the experiment. Pre-processing: How to carry out various pre-processing tasks\n (duplicate removal, file type identification etc.) to prepare the suitable dataset for the experiment. Labeling: How to label the sample i.e. malware v/s benign. (Required\n for supervised learning.) Feature extraction: How to extract features from the sample and\n build the proper representation of features to be used with various\n Machine learning algorithms. (We will restrict to static features\n for this workshop). Model training and Testing: How to train various machine learning\n algorithms and test their performance to select the best model. Making model persistence: How to make the selected model persistence\n to further use. ", + "Last Updated": "23 May, 2018", + "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general. Required module/library:\n1. pefile\n2. androguard\n3. scikit-learn\n4. CS", + "Section": "Networking and Security", + "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", + "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "urwithajit9", + "created_on": "23 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-malware-classifier-from-sample-collection-to-persistance-model-using-python~eEXWd/", + "title": "Building Malware Classifier: From Sample Collection to Persistance Model using Python" + }, + "143": { + "Content URLs": " The main sunpy website - SunPy.org The code repository - sunpy My Experience with working on the SunPy project - Blog SunPy Gallery - Examples My Contributions to the SunPy Project - Code + Examples Contribution", + "Description": "There is plenty much research going on locating sunspot regions or potential regions of high solar density from the solar data collected from observatories like AIA or SDO. Solar Physicists mainly use IDL as a programming language for analyzing such solar data, but using IDL has its demerits due to its less popularity and complexity. So how using python we can benefit the astrophysics and helio-physics community to query solar data and analyze them much more efficiently and produce much more insightful results ? In this talk we will be discussing how we can analyze sunspots and solar flares through image-processing tools using a python package called sunpy . A small example Locating Solar Spikes in the solar Map Original observed AIA image After locating such region", + "Last Updated": "22 May, 2018", + "Prerequisites": " Knowledge of Python (Beginner/ Intermediate) Little bit knowledge about the sunpy package (not mandatory) Python modules like scipy and matplotlib since there is heavy use of this two modules. A lot of excitement and passion for open science", + "Section": "Data science", + "Speaker Info": "Prateek has been an open source enthusiast for the past 2 years with a deep love in the field of astronomy and helio-physics . He is currently an undergraduate in computer science also a GitHub Campus Expert working directly with GitHub Education to build open source communities and support them on campus. He is a core contributor to the SunPy project which is lead by researchers at the NASA Goddard Space Flight Center. He has worked with the community for past 1 year and has his name published for more than 10 releases along with researchers at NASA and others in the community", + "Speaker Links": " GitHub Profile - prateekiiest Twitter - prateekiiest Website - prateekiiest,github.io GitHub Campus Expert - prateekiiest @campus_expert Blog - Medium", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Prateek Chanda (~prateekiiest)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/predicting-sunspots-and-solar-flares-with-a-tinge-of-python~dBXQa/", + "title": "Predicting Sunspots and Solar Flares with a tinge of Python" + }, + "144": { + "Content URLs": " I'll be sharing the slides after my talk as a Github repository", + "Description": "RabbitMQ is a powerful messaging broker based on the Advanced Message Queueing Protocol (AMQP). Microservices do what they say on the tin. They\u2019re small, isolated services that represent an equally small portion of your business domain. Recently there's a trend to build an application using Microservices which place an emphasis on small processes. As an increase in Microservices, we need to a mechanism where we could use some channel(Pub-Sub) to talk between these Services. Contents 1) Introduction to RabbitMQ and Its Terminology 2) Microservices using Pub-Sub 3) Sample Execution At the end of this session, participants will be able to use the rabbitMQ for there application(Could be ETL's/ MicroServices etc", + "Last Updated": "22 May, 2018", + "Prerequisites": "1) Basic Pytho", + "Section": "Others", + "Speaker Info": "My name is Jigar Shah. I have completed my BTech from Walchand College of Engg Sangli. I am currently working as a Software Developer @Browserstack. Interests: Building Backend Architecture, System Design, Data Structures, Algorithms More Inf", + "Speaker Links": "Github Linkedl", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Jigar Shah (~jigarshahindia)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rabbitmq-in-python-for-event-based-communication-between-microservices~az4qd/", + "title": "RabbitMQ in Python for event-based communication between MicroServices" + }, + "145": { + "Content URLs": " Will share my slides after my talk as a Github repository.", + "Description": " Abstract This talk is for Python web developers interested in learning what are\nthe core ideas behind microservices, what problems they try to solve,\nand what are the viable options to implement them in Python, both from\ntechnical and teamwork point of views. Some of the topics that will be\ndiscussed include the role of APIs, the improvements microservices\nbring to application scalability, upgrades, and maintenance, and the\nchallenges in breaking up a monolithic application. Contents of the talk About me - Basic introduction of myself. What are Microservices? Monolithic Python Web Application. Problems with Monoliths. Microservice Example. Advantages of Microservices. Disadvantages of Microservices. How to refactor a monolithic application into microservices? ", + "Last Updated": "22 May, 2018", + "Prerequisites": " Basic Python", + "Section": "Core python and Standard library", + "Speaker Info": " My name is Kasam Sharif (Passionate Programmer | Startup Enthusiast |\nProblem Solver). I am currently Software Engineer at Agrostar, Pune.\nPreviously was working at Symantec having 3 year of experience in IT\nindustry. In free time love to learn new things.", + "Speaker Links": " Linkedln : https://www.linkedin.com/in/kasam-sharif-2027628b/ Twitter: https://twitter.com/kasam_sharif94 Github: https://github.com/kasamsharif", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Kasam Sharif (~kasamsharif)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-microservices~dyA6d/", + "title": "Python Microservices" + }, + "146": { + "Description": "Many at times, we need to encapsulate our core logic in order to protect it from being reverse engineered and being exploited. Having a strong IP may not be the only protection. Once the code is open for the analysts, they can easily implement a modified version to achieve their goals. Some areas where the code obfuscation plays an important role are financial domain, security, web/mobile. Many times developers / teams fail to achieve the right level of code obfuscation which in turn fails to provide the level of protection to their code. We will be walking through the existing code obfuscation techniques in python and the level of protection they offer. I will be sharing my experiments and learnings during the journey to achieve a better obfuscation mechanism for python code", + "Last Updated": "22 May, 2018", + "Prerequisites": "Required : None. As we will be covering the required basic for code obfuscation in the talk it self. Good to have : Understanding the python run time process and how the code gets converted to executable binaries can be helpful", + "Section": "Core python and Standard library", + "Speaker Info": "I am Kailash, currently working as a Senior Software Engineer in Visa. I have been into python programming for the past 6 years now. I had worked on multiple levels of python projects ranging from scripting and automation, DevOps, Machine Learning, Computer Vision, Algorithmic Trading, Website Backends", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Venkata Naga Kailash Anantha (~avnkailash)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/effective-code-obfuscation-protecting-your-python-code-from-being-copied-reverse-engineered~axzld/", + "title": "Effective Code Obfuscation : Protecting your python code from being copied / reverse-engineered" + }, + "147": { + "Content URLs": "wikipedia article on the brain computer interface Text Summarizer neural network model code is in the following lin", + "Description": "Brain Mapping Using Python: Over the past few years, machine learning and artificial intelligence has been making headlines and advancing quickly by creating products that can make optimistic decisions. Now this machine learning technology can be implemented in making a machine which can perform complex actions just like in brain which can make human life easier. Now the real challenge is can we create a neural network model which can perform complex\nactions like human brain? How Python can be used to accomplish this task and how far we can achieve this feat?\nThis talk will be focusing on the methods approached by brain to generate conclusions or make decisions which can be replicated in computers and generate results. Contents of the talk About me - Basic introduction of myself. What is Brain Mapping? Functionalities of Human Brain. Neural Networks Using Python. Types of Data Summarisation techniques in Python. How Computers can make decisions. What can we expect from Brain Mapping in future.", + "Last Updated": "21 May, 2018", + "Prerequisites": " basic syntax knowledge of python basic machine learning terminology neural network models functionality", + "Section": "Data science", + "Speaker Info": " ROHITH PUDARI Rohith is a B Tech student who is passionate about integrating the most complex organ known to human which is brain with computers. He is winner of the Hyderabad best coder championship conducted by JNTUH. He is one of the few persons in India who is selected for the google Udacity scholarship. He is always interested in decreasing the interaction gap between computers and humans and started his research in creating an interface which will allow humans to interact with computers in a more natural way. He created a neural network model which generates a summary of a given essay which won the title \"Best innovative idea\" at IIT Kanpur", + "Speaker Links": "you can see the projects and previous work of Rohith in the following link to his github profile. and linkedIn profile Rohith contributed to the following open source projects: Atom- open source code Editor OpenWISP- software platform that implements a complete Wi-Fi service Sugar Labs- desktop environment and learning platform Sustainable Computing Research Group (SCoRe)", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "dvlpr_rohith", + "created_on": "21 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/brain-mapping-with-python~bonYa/", + "title": "Brain Mapping with Python" + }, + "148": { + "Description": "In this talk the main aim is to demystify data science and introduce the audience with the concepts of data science and machine learning in python. Goals : What is Data Science ? What is Machine Learning ? Why Python for Data Science ? How to solve a Real world problem with data science ?", + "Last Updated": "21 May, 2018", + "Prerequisites": "No Prerequisite", + "Section": "Data science", + "Speaker Info": "Jatin Ahuja is a self taught data scientist and machine learning practitioner. He's currently working in Data Science domain . He's the core team member (designated as PR Director) and city ambassador of AI Saturdays which is a community of over 5000+ students(over 100+ cities) to spread the knowledge of AI free of cost. He actively blogs about machine learning in his personal blog site named as everythingai . He mentors the aspirants in their journey to become a successful data scientist , machine learning engineer or deep learning engineer at MentorCruise.com ", + "Speaker Links": " Website ; https://everythingai.co.in Github : https://github.com/A-Jatin LinkedIn : https://linkedin.com/in/jatin-ahuja-89677614a/ ", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "JATIN AHUJA (~jatin)", + "created_on": "21 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-science-with-python~enm5d/", + "title": "Data Science with python" + }, + "149": { + "Content URLs": "https://github.com/atulsinghphd/NL", + "Description": "In this hands-on course using Python, we will learn how to use machine learning for Natural Language Processing (NLP) through interactive notebooks. Natural Language Processing (NLP) is a field that covers computer understanding and manipulation of human language. Machine learning is a branch of Artificial Intelligence that focuses on the ability to automatically learn from existing information. Language processing uses models that attempt to understand and represent the information at various levels that includes morphology, syntax, semantics, pragmatics and discourse. In this training, we will learn how to use machine learning to build these models. This training includes the following topics: Representing text as a vector using count, TF-IDF and co-occurrence matrix Detecting similar documents Sentiment Analysis Identifying the themes in a set of documents Extracting the entities and the relationship between the entities (stretch goal depending on time) The course will introduce the participants to NLP libraries such as nltk, gensim and Spacy", + "Last Updated": "21 May, 2018", + "Prerequisites": "This is an advanced machine learning course. To benefit from this course the participants are expected to have:\n1. Understanding of supervised and unsupervised machine learning \n2. Knowledge of python, or a high-level programming language like Java or C#.\n3. Using jupyter Python notebook environmen", + "Section": "Data science", + "Speaker Info": "Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), geo-spatial analytics, and reinforcement learning. Sasidhar Donaparthi I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company", + "Speaker Links": "Linkedin Profiles https://www.linkedin.com/in/sasidonaparthi https://www.linkedin.com/in/atulsinghphd/ Twitter Profiles @sdonapa", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Atul Singh (~atul98)", + "created_on": "21 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deciphering-human-language-using-machine-learning~bm0Ra/", + "title": "Deciphering human language using Machine Learning" + }, + "150": { + "Content URLs": "I will post presentation and Relevant codes soon on github. For reference please find the code here :\nhttp://magneplane.readthedocs.io/en/latest/index.htm", + "Description": "Content of My talk will have : Hyperloop : An Introduction How Python plays an Important role? Python Applications in the Project: Project Management, \nScripting the repeating processes, \nPython - ML in CFD, \nRaspberry Pi in Communications.", + "Last Updated": "20 May, 2018", + "Prerequisites": "An intermediate level knowledge of Python Knowledge of a Python and basic Math", + "Section": "Others", + "Speaker Info": "Suyash Singh is post graduate Student of Indian Institute of Technology, Madras Chennai. He is Head of Team Avishkar Hyperloop More Details about Avishkar Hyperloop : http://avishkarhyperloop.com/ He carries 4 years of work experience in Big Data and Data Science. Later his interest in fifth mode of transportation took him to IIT Madras. He has been pure pythonist. He has been a adviser to two small scale startups based out of Indore which deals with data science. He has a vision of transforming Transportation making it more efficient. He thinks Python will be an important tool to make it possible", + "Speaker Links": "LinkedIn Profile: https://linkedin.com/in/suyashao", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Suyash Singh (~suyash_singh)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hyperloop-how-python-helps-building-fifth-mode-of-transportation~el6jb/", + "title": "Hyperloop : How Python helps Building fifth mode of Transportation?" + }, + "151": { + "Content URLs": " Slides on Introduction to NLP : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction%20to%20NLP%20%26%20Spacy.pdf Jupyter Notebook : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction.ipynb Note : The above slides are not complete and are suited for a quick introduction to NLP in 20 mins I will be introducing the following Libraries (and use them to create chatbots) NLTK : https://www.nltk.org/ SpaCy : https://spacy.io/ I will be developing a bot on the following Chat Platforms with emphasis on Messenger: Messenger : https://developers.facebook.com/docs/messenger-platform/ Slack : https://api.slack.com/ Telegram : https://core.telegram.org/bots", + "Description": "Introduction to NLP Natural Language Processing is a prominent field in Artificial Intelligence that deals with parsing and understand Natural language, (an ordinary language such as English is any language that has evolved naturally in humans through use). NLP lies at the core of Google Duplex and other smart assistants that respond to questions in English and natural languages. I will be explaining the following : Corpus and Datasets Processing and tokenizing Text Tagging, Stemming and Lemmatizing Words WordNet Introduction to libraries NLTK Spacy Sentiment Analysis Word Embedding using BOW and word2vec Developing Chatbots With rising need for customer support, Chatbot are one of the most common applications of NLP. These are applications that are trained conversation with a human by answering some preset list of questions. I will be developing a chatbot on three platforms : Messenger (Facebook) Slack Telegram These will be deployed locally using Django with ngrok for tunneling. Additionally, due to the immense popularity of Messenger, I'll be also explaining the different message templates and other features that Messenger has. If you'd like to see me cover another platform such as Discord, Skype, Google Assistant or Alexa, feel free to drop a commen", + "Last Updated": "20 May, 2018", + "Prerequisites": "Basic knowledge of Python, English Grammar and HTTP Requests", + "Section": "Others", + "Speaker Info": "About me Hello world. I\u2019m Vishal Gupta, a 3rd yr CSE undergrad at SSN, Chennai, India. \nWhile most people generally pick up a topic, or a concept (like say Computer Vision, Big Data, or just Algorithms), understand it and aspire to excel at it\u2026 I fell in love with a language, Python. As someone who has started out by learning C++ in school, learning Python was as easy as surprising. The speed at which I could translate ideas to code was amazing, and oh boy, all I wanted to do was make things, write simple scripts to automate everyday tasks. And hence I continued to explore Python, the countless modules and possibilities with Python. I went to Hackathons, won some but more importantly made something that others could use. Chatbots and me UI/UX has never been my strong suit but Chatbots made it simple to use serve any application in a conversational manner. Over the last 2 years, I have developed over a dozen chatbot for a variety of purposes, from fetching torrent links to code education to keeping track of events. One of my best messenger chatbots is still functional with nearly ~500 subscriptions. PyGeon , scrapes a number of sites everyday for developer events such as meetups, hackathons and contests in 7 indian cities. Newly added events are sent to users every day. Experience : Chatbot intern at GoBumpr , Chennai CV intern at XR Labs , Chennai NLP intern at BicycleAI Google Summer of Code participant with Debian", + "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Vishal Gupta (~vishal11)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-nlp-and-chatbots~bkMJe/", + "title": "Introduction to NLP and Chatbots" + }, + "152": { + "Content URLs": " I'll be sharing the slides after my talk as a Github repository", + "Description": "Abstract In this talk, I would be telling people how to write better and faster Python. I've been developing Python programs, scripts and softwares for over 2 years now and I come across people who have a problem of Python being slow. \nWhenever someone has to write a faster python code they are left with one option of just shifting their entire code from Python to C or C++. This talk will clear that misconception. People can actually write faster codes in Python, the only missing fact is how? . And this is exactly why I am interested to give this talk. Contents of the talk The talk will start with a basic introduction of myself as a Python developer. I will then talk about the misconception about shifting the code to C or C++. Then I will proceed onto some basic usage of Python Programming Language. Introduction to optimization techniques in Python. Then I will talk about when and why should one optimize their application. I will introduce the basic concepts of optimization in Python. Tell people about the available/built-in functions that can come in handy. Then I will proceed onto giving a demonstration on 'Writing better functions'. The talk will conclude with some examples of optimized code that performs better than conventional approaches. The talk will be open to questions, to make it more interactive and fun. The slides will be shared to the audience after the talk", + "Last Updated": "20 May, 2018", + "Prerequisites": " Basic Python Will to learn See, It does not require much", + "Section": "Core python and Standard library", + "Speaker Info": "My name is Manish Devgan . I am a second year Information Technology student at Netaji Subhas Institute of Technology, Delhi . I am an Open Source Contributor and a learner . I have contributed to various different open source projects and won many hackathons . I was FOSSASIA Codeheat 2017 - Grand Prize Winner and Google Code-In 2017- Mentor . Currently I am a GSoC 2018 Student under FOSSASIA and RGSoC 2018 - Coach . I have contributed to Python's ChatterBot Machine Learning Engine , variety of FOSSASIA's Projects , and a wide variety of OSS projects like Github Linguist etc. Python is my favourite programming language . From writing small scripts to building small Machine Learning libraries , I've tried a lot :", + "Speaker Links": " https://github.com/gabru-md https://twitter.com/gabru_md https://facebook.com/gabrumd https://www.linkedin.com/in/gabru-md/", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Manish Devgan (~gabru-md)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-faster-python-optimizing-your-code~ejJye/", + "title": "Writing Faster Python : Optimizing your code" + }, + "153": { + "Content URLs": "Few resources that I will be using in the workshop. https://github.com/koshikraj/proof-of-ownership https://github.com/koshikraj/neo-python-contracts", + "Description": "Bitcoin has been gaining popularity in the recent years due to its market value. But more importantly, the underlying technology is gaining the attention among the developers. Many developer communities inspired by bitcoin have created their own platform to use the underlying technology widely known as \"blockchain\" to achieve decentralization. Ethereum is one such platform that has created a blockchain platform which allows developers to develop their own decentralized applications (dApps) in the ethereum network by coding the logic in the execulatable contracts called \"smart contracts\" . Although ethereum has gained a huge fame due to its smart contract implementation to create decentralized applications, it imposes developer to write the logic in an ethereum's domain-specific language called Solidity. In addition to coding in a new language, it mandates the developer to set up a new develop environment. NEO blockchain platform provides a convenient way to develop smart contracts in general purpose programming language. NEO achieves this by providing compilers to compile code written in most of the languages to bytecode that can be executed in NEO virtual machine. Currently, NEO allows compilation of python smart contracts through neo-python project. This is the first blockchain project to provide such a freedom to the developer. NEO project provides plenty of benefits over other blockchain platforms out there. \nIt plans to achieve smart economy by creating a strong digital identity. It achieves faster transaction rate which is the key to scale any platform. NEO is being referred to as the \"New Ethereum\" due to its increasing popularity. I plan on conducting a workshop to create a decentralized application by developing and deploying smart contract using neo-python. Following would be the agenda of the workshop. Introduction to Bitcoin, Blockchain, and consensus to achieve decentralization. (30 mins) Introduction to NEO and Setting up a NEO platform (30 mins) Creating and deploying Hello World contract using Python (15 mins) Creating a Proof of Ownership system (30 mins) Creating a user interface to create a complete Proof of Ownership DApp. (20 mins) Creating an Initial Coin Offering (ICO) using an existing template and Q&A (25 mins) ** This is a rough estimation of time and topics as of now. I will try to fit more topics if possible. An attendee will be able to create an asset management DApp such as document ownership system or launch a basic ICO after attending the workshop", + "Last Updated": "20 May, 2018", + "Prerequisites": " Novice level experience in python programming. Basic knowledge of how bitcoin or blockchain technology is\n implemented would help to grasp the topic pretty well. Although I will be using Ubuntu Linux distribution for the demo, Attendees can use any platform which has python 3.6 installed. Windows users might have to install a docker container manager as installation might create some issues.", + "Section": "Networking and Security", + "Speaker Info": " I completed my masters in Computer science and Information Security after getting fascinated by the security and cryptography field. I have a demonstrated history of working in the computer and network security industry (RSA Security) where I had worked for more than a year. I worked as a senior fullstack developer for a start-up called CoWrks. In the meantime, I got involved in the blockchain and decentralized application. I started devoting my entire time to blockchain and I'm currently writing a research book on the blockchain technology called Foundations of Blockchain", + "Speaker Links": " My Linkedin profile. Few of my opensource contributions. My semi active social profile. Check out my detailed bio at koshikraj.com", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Koshik Raj (~koshikraj)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-decentralized-smart-contracts-using-python~egXra/", + "title": "Creating decentralized smart contracts using Python" + }, + "154": { + "Content URLs": " https://github.com/rahulkumaran/Telegram-Syntaxdb-bot There will be some slides that I'll prepare too but most of it is going to be an explanation from the GitHub repo and my talk https://github.com/python-telegram-bot/python-telegram-bot https://syntaxdb.com https://syntaxdb.com/api/v1 https://core.telegram.org/api", + "Description": "In this particular topic, I'll basically be telling people about how easy it is to create a Telegram Bot. The reason I'm interested in taking this up is because there are people who develop beautiful things and might want to let people to use it even on a mobile interface. The problem is not everyone's good with app development. So in such cases, deploying the beautiful things in the form of a bot would be a great idea. Bots can be of 2 types : Conversational Command based I'll be taking up the command based bot to help people get a feeling of this topic. Also, through the example I'll be giving, I'll try to make people understand as to what APIs are and how to use existing one. Later I'll show them how to create your own Python APIs because APIs make lives easier for programmers and it's always a good practise to know how to create an API as you never know when someone else might need it. CONTENTS AND ORDER OF THE TALK I'll be starting off with an introduction about myself and then I'll move on to what are bots. I'll then be explaining about why we could probably use these bots on Telegram, Discord, Slack and so on. Thereafter I'll be talking about the Telegram API for Python to help you interact with the bot and telling you how to use it. Before this, I'll show them how to prepare a bot on Telegram and get the Token. After this, I'll be talking about the importance of an API and utilizing existing ones as it makes your job much simpler. Slowly, I'll shift my focus on to how to build an API. I'll be explaining this using an example. Then using the Telegram Bot API and the API we build for Syntaxdb.com, we'll be creating a Telegram bot. Lastly, I'll summarise and entire talk and will take up a couple of questions. The entire talk will be based on a GitHub repository. The code links will be given to everyone for future reference", + "Last Updated": "20 May, 2018", + "Prerequisites": " Basic Python Usage of libraries in Python", + "Section": "Others", + "Speaker Info": "The speaker, in this case is me, Rahul Arulkumaran . I'm an engineering undergrad currently going into my 3rd year. I'm also the Founder of the startup Free Flow . We still haven't registered it yet though. I started learning how to code when I came into engineering and Python was the first language I learnt. I never really developed anything until last year. It was after creating my first application that I got the interest to develop more using Python. From then to now, I've learnt a lot. I might not be an expert but yes, for my age, I think I'm better than most others. I'm also the President of the Computer Science Club, Enigma in my college Mahindra Ecole Centrale . I'm a Python developer and an open source enthusiast . I also am a Contributing and Managing member of PSF . I work on a lot of open source projects I love learning anything and everything related to coding. I'm also a Machine Learning and Data Science enthusiast ", + "Speaker Links": " https://rahulkumaran.github.io https://github.com/rahulkumaran https://www.linkedin.com/in/rahul-arulkumaran-101a63127", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Rahul Arulkumaran (~rahulkumaran)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-and-working-with-apis-to-develop-a-telegram-bot~dwgXd/", + "title": "Creating and working with APIs to develop a Telegram Bot" + }, + "155": { + "Content URLs": "(Slides to be uploaded soon", + "Description": "In computer vision, object detection is scanning and searching for an object in an image or a video (which is just sequence of images). Whereas, object tracking is like you are spying on someone and following it. Done in motion images like in animated gifs or videos, we want to track how an object is moving, where is it going, or its speed. Although it has been studied for dozens of years, object detection and tracking remains an open research problem . The difficulty level of this problem highly depends on how you define the object to be detected and tracked. If only a few visual features, such as a specific color, are used as representation of an object, it is fairly easy to identify all pixels with same color as the object. On the other extremity, the face of a specific person, which full of perceptual details and interfering information such as different poses and illumination, is very hard to be accurately detected, recognized and tracked. Thus, I believe it is important to address such challenges via a comparative study of object tracking and object detection in python. Here, I aim to present my own experience in tackling the problems while I tested different algorithms for the same", + "Last Updated": "19 May, 2018", + "Prerequisites": "Basic understanding of pytho", + "Section": "Data science", + "Speaker Info": "Anand Zutshi is currently pursuing his undergraduate B.E. degree from Netaji Subhas Institute Of Technology, Delhi. He has experience in developing and testing basic as well as advanced algorithms in C, C++. He has experience in developing a Learning Management System which uses dynamically trained neural network for scoring its users, and a LDA based tagging in its queries. He has in depth knowledge of Natural Language Processing, mainly with emphasis on word sense disambiguation and language models. His recent work of interest primarily focusses on object detection and object tracking in Python and sound classification and recognition. Currently, he is working on testing a biometric database management system along with predicting self and non-self processes in Operating system using Neural Networks", + "Speaker Links": "https://github.com/zutshianan", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "anand zutshi (~anand09)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-tracking-vs-object-detection-a-comparative-analysis~avJna/", + "title": "Object tracking vs Object detection- a comparative analysis" + }, + "156": { + "Content URLs": " https://pytorch.org/docs/stable/index.html Slides (to be uploaded soon)", + "Description": "Talk Abstract This talk aims to introduce Facebook's Deep Learning library - PyTorch. PyTorch is increasing becoming popular due to it's powerful features and shallow learning curve, making it accessible and easy to use to a larger community. This talk discusses about the 'Autograd' package, which is central to all neural networks in PyTorch. It also entails details about the different features and functionalities of PyTorch as well as equip the audience on how to create simple and complex Neural Networks in PyTorch. PyTorch helps to create dynamic computation graphs that allow you to change how the network behaves on the fly unlike static computation graphs. It offers modularity which enhances the ability to debug or see within the network. Outline of the Talk The talk will be broadly divided into 3 broad parts. Part 1 will be an Introduction to PyTorch. This part will focus on the use and need for PyTorch as a deep learning framework. This will be followed by instructions on how to setup PyTorch and a look at the basic building blocks behind the framework. Part 2 will dive more into the features of PyTorch, mainly it's AutoGrad package which lies at the heart of all Neural Networks created in PyTorch and PyTorch's ability to create dynamic computational graphs as opposed to the static computational graphs offered by some of it's counterparts (such as TensorFlow and Caffe). Part 3 will be a more 'hands on' part where the talk will focus on how to create and build simple as well as complex neural networks (such as Convolutional Neural Networks) with the framework", + "Last Updated": "19 May, 2018", + "Prerequisites": " A basic understanding of how Neural Networks work would be beneficial. Some knowledge about Numpy.", + "Section": "Data science", + "Speaker Info": "I am Rahul Baboota, a 3rd Year Undergraduate in India studying Computer Science and Engineering. I have an avid interest in the domain of Data Science, Machine Learning and Deep Learning. I have worked at various Data Science and Machine Learning based startups and labs. In my freshmen year, I worked at a data journalism startup to create and analyze smart data stories. I was also a part of a project funded by the Government of India for the development of a social media based analytics tool for the analysis of healthcare and nutrition in India. I am currently working at the Center for Artificial Intelligence at IIITD in the Autonomous Vehicle Lab 'Swarath'", + "Speaker Links": " https://www.linkedin.com/in/rahulbaboota/ https://github.com/RahulBaboota", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "rahul baboota (~rahul93)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/throwing-light-on-pytorch~er7La/", + "title": "Throwing Light on PyTorch" + }, + "157": { + "Content URLs": "This talk is going to be based on a series of blog posts I have written about the same topic - Python Project Workflows - Part 1 Python Project Workflows - Part 2 (Pipenv) Python Project Workflows - Part 3 (pylint)", + "Description": " Have conflicting dependencies (unpleasantly) surprised you? (Darn: It worked on my laptop!) Do deterministic builds matter? What about those run-time errors, which were a typo while accessing an attribute of a class? Has the codebase already started smelling a bit? Unit tests and what about Dockerization? Typically, when your Python project grows beyond a few modules and your team size is more than a couple of developers, having the right tools built into your project development workflow saves one from a lot of surprises (and perhaps late night calls). In this talk, we start with challenges typically seen in Python Projects and look at ways of overcoming them, so that the velocity of code deployment increases. Specifically we are going to be looking at tools that are out there that allow you to - Properly track dependencies ( pip , virtualenv and the new Pipenv ) Have a separate Dev and Production environment - so that dependencies in Dev environment don't spill into Production environment. Ensure that the builds are deterministic (across developer/build machines and time.) Enforce certain coding guidelines and capture the potential 'run-time' errors right during the development ( pylint ) and Eventually Dockerize your application.", + "Last Updated": "19 May, 2018", + "Prerequisites": "It's an intermediate level talk where you have already done some Python development and are at a point where you want to package, distribute or deploy your pet Project. If you are a beginner in Python, but have been involved in build/release of packages in any other languages, likely this talk is for you. If you do an equivalent of sudo pip install or sudo apt-get install when you want to download and use package foo , chances are you will benefit from this talk quite a bit", + "Section": "Developer tools and Automation", + "Speaker Info": "Running a Consulting Company 'hyphenOs Software Labs' in Pune, India. Python/Go programmer - Mostly for things that pay the bills and ideas that I want to try out. Datacenter Networking Enthusiast (hacking a yet another Container Networking technology, borrowing ideas from different Projects) Eternally grateful to whoever wrote tcpdump and the new Wireshark . Number of problems solved using these tools could run into triple digits. Hates trailing white spaces in a file.", + "Speaker Links": " Stack Overflow Github LinkedIn", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Abhijit Gadgil (~gabhijit)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-project-workflows-continuous-deployment-friendly~bq8ya/", + "title": "Python Project Workflows - Continuous Deployment Friendly" + }, + "158": { + "Content URLs": ">>> import thi", + "Description": "Tim Peters preached and we memorized that Explicit is better than implicit, but how many understood the deeper meaning enough to imbibe the essence of the zen? In this 20 min talk, we shall go through the zen and look at live examples where the golden words make a programmer's life easy", + "Last Updated": "19 May, 2018", + "Prerequisites": "Familiarity with the syntax of Python", + "Section": "Core python and Standard library", + "Speaker Info": "Anuvrat has spent countless hours wading through utterly un-pythonic, non-modular codebases that contain > 8000 lines in one file and >500 in one function, with nested try-except statements and has almost mastered the skill of keeping his calm and understanding even that", + "Speaker Links": "https://anuvrat.i", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Anuvrat Parashar (~bhanuvrat)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-python-with-real-life-examples~epVyb/", + "title": "The Zen Of Python: with real life examples" + }, + "159": { + "Content URLs": "Slides: https://docs.google.com/presentation/d/1aE0QmLDffyGRvChqhxaSUWEtBkDqZH5NR3in5FBOPlc/edit?usp=sharing Most of the snippets and concepts to be discussed are taken from various resources I came across during my 6 months long research about Python. I have collected such snippets in a project called \"What the f*ck Python!\". Here's the source: https://github.com/satwikkansal/wtfpytho", + "Description": "Do you know that, 'a'[0][0][0][0][0] is a semantically valid statement in Python. print(r\"\\ some string\") is a valid statement, but print(r\"\\ some string \\\") raises a SyntaxError . print('wtfpython''') is valid but print(\"wtfpython\"\"\") raises SyntaxError . Do you know why, >>> a = \"some_string\"\n>>> id(a)\n140420665652016\n>>> id(\"some\" + \"_\" + \"string\")\n140420665652016 the id of both the objects in above snippet is same? And do you know why, >>> timeit.timeit(\"s1 = s1 + s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.25748300552368164\n# using \"+=\", three strings:\n>>> timeit.timeit(\"s1 += s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.012188911437988281 s1 = s1 + s2 + s3 is much slower than s1 += s2 + s3 . And finally, >>> 'a' * 20 is 'aaaaaaaaaaaaaaaaaaaa'\nTrue\n>>> 'a' * 21 is 'aaaaaaaaaaaaaaaaaaaaa'\nFalse\n\n# one last attack!\n>>> a = \"wtf\"\n>>> b = \"wtf\"\n>>> a is b\nTrue\n\n>>> a = \"wtf!\"\n>>> b = \"wtf!\"\n>>> a is b\nFalse\n\n>>> a, b = \"wtf!\", \"wtf!\"\n>>> a is b\nTrue Do you know the reason behind all the above-discussed facts and snippets? Some of them are really puzzling, right? I felt the same when I first came across all these intricacies. But don't worry, such behaviors, are mostly the consequences of strings being [immutable] [sequences] in Python. In this talk we'll be going through the concepts behind such snippets in detail, so that next time when you see such examples, the answer seems natural to you. Finally, we'll try to answer some interesting questions like, How does string concatenation work? What's the best way of building large strings in Python? (It may actually depend on your use-case) What happens when you multiply a string by a boolean? How strings in Python differ from strings in other languages like JavaScript, C++? and many more", + "Last Updated": "18 May, 2018", + "Prerequisites": "Basic familiarity with programming. Prior experience with Python would make the talk more interesting for the attendee", + "Section": "Core python and Standard library", + "Speaker Info": "I'm a Software Developer experienced with Decentralized Applications and Data Science. In my leisure time, I love doing pointless things with programming. Currently on a quest to learn as much as I could about Computer Science. And lastly, I prefer all things Python! (A humble brag ", + "Speaker Links": "Website | Github | Archives Past Speaking Experience PyCon India 2017 (Speaker for a DevSprint ) EuroPython 2017 ( Invited as a Speaker for a workshop , unable to attend though) IWD-Delhi 2018 ( Speaker ) OSS DTU (Instructor and moderator)", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Satwik Kansal (~satwik)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/do-you-really-think-you-know-strings-in-python~boJLa/", + "title": "Do you really think you know strings in Python?" + }, + "160": { + "Content URLs": " https://docs.julialang.org/en/release-0.4/ https://julialang.org/ Ppt (soon)", + "Description": "Julia Programming Language The Julia programming language is proving to be a new paradigm shift in the data science community due to it's easy to pick up syntax like python but and execution speed equivalent to C , this is possible due to flexible types and JIT compiler. The speed and user-friendliness are only some of its good parts. This talk delves deeper into understanding, how can Julia be the next language on your learning list. Outcomes of the talk What is Julia? How can I get it into my daily workflow What Julia offers that Python does not Understanding benefits of shifting to Julia How can a python-ista shift to Julia", + "Last Updated": "18 May, 2018", + "Prerequisites": " Laptop with Julia up and running", + "Section": "Others", + "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a recently born Julia-n, I do a lot of code in Julia and move back and forth from Julia to Python to C. I'm a deep learning practitioner and loves Astronomy. I recently got selected into Google Summer of Code under OpenAstronomy org and my project's fundamental language is Julia. I'm a computer science by day and dancer by night. Currently, I'm fiddling with Julia and it's awesomeness and I'll offer you nothing less than awesome", + "Speaker Links": " http://prsr.me https://linkedin.com/in/prakharcode https://github.com/prakharcode", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "prakhar srivastava (~prakhar91)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/julia-an-upgrade-to-python-programming-language~enJpe/", + "title": "Julia. An upgrade to Python Programming Language" + }, + "161": { + "Content URLs": "Coming up soon (related to this workshop", + "Description": "Convolution Networks - Framework = Vision in vanilla python. This workshop aims at providing the attendees an experience of implementing convolution neural from scratch without any big framework working in the backend supplementing the need for computation. This would give the attendees an overall understanding of what are Convolution Neural Networks and why do they work so exceedingly well! One does not simply code in vanilla python. What can you expect from this workshop! You'll understand what are convolution neural networks Why they work so well on image data? All the different implementation of Convolution network and how they improve the vanilla network What are the best ways to implement convolution network on a given data What this workshop is not! Just another workshop telling you to use frameworks Maths will not be looked over. (It's important) This workshop is not any other university lecture where you'll not understand anything. I find this image to be so apt given all the abstraction provided by frameworks", + "Last Updated": "18 May, 2018", + "Prerequisites": " Command over Python Familiarity with Numpy and basic math packages Intermediate Mathematics Familiarity with algorithms common in machine learning", + "Section": "Data science", + "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a deep learning enthusiast who loves mathematics and astronomy. I've been exploring machine learning/deep learning for about 2 years now and fiddling with the basic mathematics and scratch implementations always excite me. I'm currently mentor of deep learning in a Delhi based startup Greatech Soft Solutions and interning at Startup labs and a Google Summer of Code '18 student under the organization OpenAstronomy", + "Speaker Links": " http://prsr.me https://www.linkedin.com/in/prakharcode https://github.com/prakharcode", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "prakhar srivastava (~prakhar91)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/convolution-neural-networks-without-any-frameworks~bmX3a/", + "title": "Convolution Neural Networks without any frameworks" + }, + "162": { + "Description": "Sometimes it can be a laborious task for developers to build android apps using Java. Though Java supports Android apps in a powerful way but it also increases the code complexity for a high end app. Now, if you are a python enthusiast and also want to develop Android apps then Kivy comes to your rescue. Kivy is an open source python library for rapid development of cross platform apps. Using the Kv design language and the Kivy framework for Python, you can build amazing interactive multi-touch apps in just a matter of minutes. Kivy framework solves the complexity problem any android developer face while writing complex codes. It also serves the advantage of being cross platform which saves a great amount of time for any app developer. If you love Python, you will also love Kivy", + "Last Updated": "18 May, 2018", + "Prerequisites": "Python Basic Knowledge of Androi", + "Section": "Web development", + "Speaker Info": "The speaker goes by the name amanraj209 all over the web. I've been interested in learning new technologies since high school and I've been developing apps using Python, Javascript, Java, Go since the last 3 years. I've also done some small projects in Machine Learning. Being a developer gives me a great sense of feel to build apps for the users and contribute to the community. It has always been my passion to dive into the technology and contribute to the community something useful", + "Speaker Links": "Github: https://github.com/amanraj209 LinkedIn: https://www.linkedin.com/in/amanraj209 Facebook: https://www.facebook.com/amanraj20", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Aman Raj (~amanraj209)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/developing-android-apps-using-kivy~el61b/", + "title": "Developing Android apps using Kivy" + }, + "163": { + "Content URLs": "Shall be updated soon", + "Description": "You have got this super awesome REST API served through Django/DRF based project and suddenly these requirements come in: We need to have a local support for Chinese language! In case, you've not written your application with localization and internationalization in mind, then \"Boy! You're in danger! You should better start praying to almighty to give you strength and endurance to support yet another language in your app\". In this talk, we'll see how do we support localization and serve our app in different languages, based on what language the client wants to communicate in. As a backend, we should be language agnostic and allow all clients to communicate with us in one of the languages we support. We'll see how to support translation for static data (using makemessages / compilemessages) and dynamic data, using various third-party services such as django-translations and transifex. Here, static data is translations for all the fields, error messages etc. that the app already has and dynamic data is the custom data input by the user in the app. This would enable you to have your admin panel, as well as RESTful APIs, served in different languages", + "Last Updated": "18 May, 2018", + "Prerequisites": "Basic knowledge of Python and Django", + "Section": "Web development", + "Speaker Info": "Why do you want this person to speak? Sanyam is a self-taught programmer with a \"can-do\" attitude who developed his interest in Computer Science and Software Development over the years. He mostly goes by CuriousLearner all over the web and you might run into him at various Python Conferences and local meetups. In his free time he contributes to FOSS. Some of his noticeable contributions are in Gecko Engine from Mozilla and CPython. You can read about his latest hacking CPython and other projects at http://www.SanyamKhurana.com/blog & http://medium.com/@CuriousLearner Highlights : Goes by CuriousLearner all over the web. Bug Triager and contributor to CPython (bugs.python.org) GSoC 2018 Mentor for Debian RGSoC 2016 Mentor Mozilla Reps Mentor and contributor to Mozilla's GeckoEngine, Add-ons ecosystem, and other few projects. Core-organizer for PyCon India 2016 & PyCon India 2017 Volunteer for PyCon India 2015.", + "Speaker Links": "Blog: http://www.SanyamKhurana.com/blog Website: http://www.SanyamKhurana.com Github: https://github.com/CuriousLearne", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Sanyam Khurana (~CuriousLearner)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-multilingual-superhero-in-django~bkMve/", + "title": "Becoming a Multilingual SuperHero in Django" + }, + "164": { + "Content URLs": " http://haridas.in https://github.com/haridas", + "Description": "Data-science mainly involves understanding your data and identify suitable models based on the data. Mastering the standard tools like pandas and seaborn will be key to gain insights about ML problems. This tutorial coverers, Basics of pandas and seaborn Different plotting patterns using seaborn for your data. Plotting Single and bivariate distributions, categorical plots with distribution. Understand two variable behaviour using regression plots. One usecase:- How I decided to buy a petrol car instead of diesel car by analysing my fuel spending.", + "Last Updated": "17 May, 2018", + "Prerequisites": "Lapatop with following packages installed. pip install seaborn pand", + "Section": "Data science", + "Speaker Info": "Haridas is a Principal Engineer in Pramati Technologies, part of Labs team. He has 8+ years of experience in multiple domains like, Web development, SOA, ML, Devops. He has been working extensively in different ML use-cases and applying them in real scenarios", + "Speaker Links": " http://haridas.in Twitter @haridas_n", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "haridas n (~haridas)", + "created_on": "17 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/find-patterns-in-your-data-using-seaborn-and-pandas~ejJ4e/", + "title": "Find patterns in your data using Seaborn and Pandas" + }, + "165": { + "Description": "DevOps is gaining momentum and we at Microsoft want our users to have great CI/CD story for any language targeting any platform. In this session, we will be talking about how easy is to get started on Cloud and DevOps for Python developer in this new generation of Microsoft We're going to start from scratch and before we're done we will use Visual Studio Team Services (VSTS) to setup Continuous Delivery for Python Applications on Cloud and demonstrate the DevOps strategy in action. The solution grows up to the most demanding needs of a modern software developers powered by VSTS. Whether you are starting new, bringing your own tool chain or inter-operating with existing tools and assets, you can accelerate your delivery of value with Azure and VSTS", + "Last Updated": "16 May, 2018", + "Prerequisites": "N", + "Section": "Developer tools and Automation", + "Speaker Info": "Alok Agrawal is Product Manager for Microsoft Visual Studio Team Services where he and his team are building next generation cloud based developer tools. He has been with Microsoft for over 7 years. Previously he has worked with Windows Application Compatibility and Azure Application team. Alok has Bachelor's degree in Computer Science and completed his business management from IIM Calcutta", + "Speaker Links": "http://www.imalokagrawal.com https://twitter.com/imalokagrawal https://github.com/imalokagrawa", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Alok Agrawal (~imalokagrawal)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-plumber-building-deployment-pipeline-in-minutes~e03Nd/", + "title": "Becoming a Plumber: Building deployment pipeline in minutes" + }, + "166": { + "Content URLs": "Workshop Content: https://github.com/openfaas/workshop OpenFaas Docs: https://docs.openfaas.com/ OpenFaas Website: https://www.openfaas.com", + "Description": "OpenFaaS makes Serverless Functions simple with any programming language through the use of Docker containers. The project can be hosted on any cloud, or on your own hardware - even your laptop. Learn how to build Serverless functions with OpenFaaS and Python in this self-paced workshop lead by the community behind the project. Start by deploying OpenFaaS to your laptops with Docker for Mac or Windows and then learn how to build, deploy and invoke serverless functions in Python. Topics will include: Managing dependencies with pip, dealing with API tokens through secure secrets, monitoring functions with Prometheus, invoking functions asynchronously and chaining functions together to create applications. We\u2019ll finish by building a GitHub bot that puts all of what we\u2019ve learnt together into a single application. The issue-bot will respond to issues raised by analysing the text and deciding whether to label them positive or for review. The workshop will have following labs: Prepare for OpenFaas Test things out Introduction to functions Go Deeper with functions Create a Gitbot HTML for your functions Asynchronous functions Advanced feature - Timeouts Advanced feature - Auto Scaling Advanced feature - Secrets", + "Last Updated": "16 May, 2018", + "Prerequisites": " Basic knowledge of Docker Functions will be written in Python, so prior programming or scripting experience is preferred. Requirements: Install the recommended code-editor / IDE VSCode MacOS, Windows 10 Pro/Enterprise, Ubuntu Linux For Windows install Git Bash Docker CE for Mac / Windows Edge edition Docker CE for Linux As a last resort if you have an incompatible PC you can run the workshop on https://labs.play-with-docker.com/ . ", + "Section": "Web development", + "Speaker Info": "Vivek Singh: Currently working as Software Engineer - II at Akamai Technologies. Been an active contributor to OpenFaaS project. Loves to code in Python and Golang. Contributes to Open Source projects in free time. Vivek Sridhar: Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", + "Speaker Links": "My contributions: https://github.com/viveksyngh LinkedIn Profile: https://www.linkedin.com/in/viveksyngh/ Twitter: https://twitter.com/viveksyngh Website: https://www.viveksyngh.info Blog: https://www.viveksyngh.info/blog", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Vivek Kumar Singh (~viveksyngh)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-serverless-with-openfaas-and-python~e9Xzd/", + "title": "Hands-On Serverless with OpenFaaS and Python" + }, + "167": { + "Description": "The human voice is becoming an increasingly important way of interacting with devices, but current state of the art solutions are proprietary and strive for user lock-in. Mozilla\u2019s DeepSpeech and Common Voice projects are there to change this. In contrast to classic STT approaches, DeepSpeech features a modern end-to-end deep learning solution. Based on Baidu's Deep Speech research paper, it trains a model by machine learning techniques. This model directly translates raw audio data into text - without any domain specific code in between. To train systems like DeepSpeech, an extremely large amount of voice data is required. Most of the data used by large companies isn\u2019t available to the majority of people. That's why Mozilla launched Common Voice, a project to help make voice recognition open to everyone", + "Last Updated": "16 May, 2018", + "Section": "Data science", + "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune, and a Mozilla TechSpeaker. I am also a decent artist, and love to play the piano in my free time", + "Speaker Links": "Mozilla Research machine learning home page: https://research.mozilla.org/machine-learning/ Speaker's LinedIn: https://www.linkedin.com/in/shaguftagurmukhdas/ Speaker's twitter: https://twitter.com/shaguftamethwa", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mozillas-deepspeech-and-common-voice-projects~e7JBd/", + "title": "Mozilla's DeepSpeech and Common Voice projects" + }, + "168": { + "Description": "You only look once (YOLO) is a state-of-the-art, real-time object detection algorithm. The model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image. It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. This makes it extremely very fast. This talk teaches you to develop your own real-time object detection python application to detect and classify objects in images as well as videos in real-time, which you can use in your next self driving car", + "Last Updated": "16 May, 2018", + "Prerequisites": " Knowledge of basic Python and its syntax Idea/Overview of deep learning as a technology", + "Section": "Data science", + "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune. I'm currently working in HSBC Technology India, as a software developer. I am also a decent artist, and love to play the piano in my free time", + "Speaker Links": " LinkedIn Twitter Recent talk on WebVR", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-object-detection-coz-yolo~b6VNb/", + "title": "Real-time object detection coz YOLO!" + }, + "169": { + "Content URLs": "https://github.com/sdonapar/data_analysis_pytho", + "Description": "Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data. Data Visualisation helps to get hidden insights quickly . Data Visualisation is key for summarising and communicating your insights. This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis and visualisation Following will be covered as part of this session How does data analysis fit in the life cycle of data science project Dealing with numpy arrays - quick overview Reading data using various formats and sources Data scrubbing/cleansing - dealing with missing values, data transformation Introduction to data visualisation and quick overview of libraries available Using visualisation to understand and communicate results Analysing one of the open source data set By the end of the session Audience will have very good understanding of how to apply numpy, pandas to analyse, visualise understand and communicate the results Scrub/Cleanse the data and prepare data set required for machine learning", + "Last Updated": "16 May, 2018", + "Prerequisites": "Hands on exposure with basic python programming language Software requirements: Please install Anaconda ( https://www.anaconda.com/download/) with Python 3.6 Download the git hub repo - https://github.com/sdonapar/data_analysis_pythonwe would be using jupyter notebooks for this worksho", + "Section": "Data science", + "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company. I have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delh", + "Speaker Links": "github link - https://github.com/sdonapar linkedin profile - https://www.linkedin.com/in/sasidonaparthi twitter handle - @sdonapa", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Sasidhar Donaparthi (~sasidhar)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-visualisation-using-python~e50Xd/", + "title": "Data Analysis & Visualisation using Python" + }, + "170": { + "Description": " Understanding Neural Networking using NumPy Implementing CNN using Keras & understanding foundations Using Pretrained models. Transfer training for doing dog breed identification", + "Last Updated": "15 May, 2018", + "Prerequisites": " Python Basics NumPy Machine Learning Basics", + "Section": "Data science", + "Speaker Info": " 10 + Industry Experience. Machine Learning & Deep Learning Trainer/Consultant for more than 20 companies https://www.linkedin.com/in/awantik/ Co-Founder EdYoda & Zekelabs", + "Speaker Links": "https://www.linkedin.com/in/awantik", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Awantik Das (~awantik)", + "created_on": "15 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-using-python-from-scratch-image-classification~b4KJa/", + "title": "Deep Learning using Python from Scratch - Image Classification" + }, + "171": { + "Content URLs": "https://games.renpy.org/category/rpg https://www.renpy.org", + "Description": "Ren'Py is one of the most versatile and easy-to-use frameworks, written in Python, for the development of Visual Novels and smaller Role-playing games. The talk will explore the details about creating your own development environment for development of visual novels, writing a script and developing GUI, porting your game to Android and iOS and how you can get help for issues in development process. The talk will also explore some of the games which have been developed in Ren'Py like Katawa Shoujo, Doki Doki Literature Club, Imre's Curse: The Prologue etc. The talk will be an interactive one and have a very light and humorous note", + "Last Updated": "15 May, 2018", + "Prerequisites": "No prerequisites required. An open mind and familiarity with Python is all what is needed to attend the talk", + "Section": "Others", + "Speaker Info": "I am currently involved with Lernr Project, a startup based in Ahmedabad and have been working with Python for 3+ years, certified as a\nSoftware Carpentry Instructor and one of the organizers of Django Girls Bangalore. Contributor to Biopython, Galaxy Project, bioconda and conda-forge communities. My interests are in the field of Bioinformatics, High-Performance Computing and am working under Prof. V.K. Jayaraman in the field of Proteomics", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Sourav Singh (~sourav)", + "created_on": "15 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/make-your-own-visual-novel-in-renpy~b2JAb/", + "title": "Make your own Visual Novel in Ren'Py" + }, + "172": { + "Content URLs": " Talk at PyCon India 2017 Talk at PyCon Pune 2017 Talk at PyCon India 2013 Django on Steroids -- Slides Lessons from Scale: Django", + "Description": "Take it from someone who has introduced an exorbitantly high number of bugs in empty files for most of his life: debugging is hard indeed. But since the dawn of time, developers have been debugging code: there's no escaping that. Software testing, as the elders would tell you, is one of the greatest weapons in your arsenal against those bugs. It's easy to write tests. It helps you write more robust software. And it really helps you sleep at night: and your on-call ops team would love you! But testing is also deeply mystified, unfortunately. Beginners, and sometimes even seasoned developers, generally have a difficult time just to get started: so they eventually miss out on this easy way to attain peace of mind. This talks aims at removing all the mystery around software testing in Python, and give the attendees a head-start into the easiest way of writing tests for their code. As part of being a Python developer for the past 8 years and leading a team of developers building enterprise-grade software for the past 4 years, I've learnt immensely about the important role of software testing in building scalable, durable software; and also a better, pragmatic way of thinking about testing in Python. This talk aims at providing a distilled version of my learning to the audience: both beginners to Python, and seasoned Pythonistas. The talk would broadly cover these topics: A formal way of thinking about software testing / Why you should even bother about writing tests? Writing the simplest of tests in Python / Brief exploration of unittest and pytest Introduction to mocking in Python / In-depth exploration of mock and how to effectively use it for mocking any type of scenario in your code Writing tests for complex applications / working code examples from real life A few (opinionated) recommendations about testing Apart from providing to the audience an easy-to-grasp framework of thinking about software testing, this talk aims to teach by examples from real world. Complex and not so straightforward concepts would be explained with code samples and tests from production, so it's easy for the audience to truly grasp them. The talk also features anecdotes from my own experience in building software to give the audience better context", + "Last Updated": "15 May, 2018", + "Prerequisites": "This talk is intended for newcomers to Python (who might never have written a test yet), as well as experienced developers (who might not be writing tests effectively). There are no technical pre-requisites for this talk. The key takeaways would be patterns you can directly start using in writing tests for your own code", + "Section": "Developer tools and Automation", + "Speaker Info": "Sanket ( @sanketsaurav ) is co-founder and Chief of Geeks at DoSelect . He\u2019s 50% developer and 50% designer. He\u2019s been dabbling with computers since the age of 10, and had started his first venture at 18. He loves the Web and likes building cool stuff that matter. His languages of choice are Python, Go and JavaScript, and he\u2019s been building production apps using these for the past two years. He\u2019s also spoken at more than 50 events and hackathons across the country on open source technologies including Python, HTML5 and web applications in general. Sanket also contributes extensively to open-source, with contributions to projects like Django, Celery and Docker, and original Python modules like S3Tree and mimelib ", + "Speaker Links": " GitHub Website DoSelect", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Sanket Saurav (~sanket)", + "created_on": "15 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-is-hard-testing-is-easy~e17qb/", + "title": "Debugging is hard, testing is easy!" + }, + "173": { + "Content URLs": "I will soon share presentation, resources, and code soon on GitHub", + "Description": "Abstract Think of wireless internet, but has the wire somewhere. Serverless architecture still has the server behind :P. What serverless actually means that developer should focus on the code rather than thinking about the servers. As a technique, it removes most of the manel parts of an application, so you can actually spend your day coding. This means that you, developers, can quickly create apps that handle production-ready traffic. You do not have to actively manage scaling for your applications. You do not have to provision the server, or to pay for resources that are unused. The serverless movement started with the release of AWS Lambda, a Function-as-a-Service (FaaS) compute service. But serverless is much more than just FaaS Chatbots have been around for quite a long time. But why this sudden surge and interest in chatbots now? Well, there are various reasons. Unlike the earlier days, many AI and NLP capabilities are now available as consumable services. Also, serverless technologies make chatbots easier to build and scale. The question is, how is the backend served? Would you set up a dedicated server (or a cluster of servers)? That\u2019s costly, painful, and time-consuming! or You will deploy it to Heroku, which will eventually sleep (only happens in the free tier) if no one uses your chatbot. Imagine suddenly, traffic increased your chatbot is used by thousands of people at a time. When Heroku free tier is over, the application crashed or you exceeded memory limit. What would you do now? That\u2019s where serverless technology can help. Benefits of serverless No Administration - We can deploy our code without provisioning anything beforehand, or manage anything afterward. There is no concept of a fleet, an instance, or even an operating system. Scalability - One doesn't have to care about auto-scaling, No need to show alerts or write scripts to scale up and down. With serverless, we can handle quick bursts of traffic. Cost - Function-as-a-service (FaaS) compute and managed services charged based on actual usage rather than pre-provisioned capacity. This means one pay the amount we use, so if we use service for 10 sec then we pay for 10 sec. Faster Development - Now loop between having an idea and deploying to production is shortened because no one need to manage anything after deployment, smaller teams can ship more features. It's easier than ever to make your idea live. Easy Integration With Other Services Going serverless allows a seamless integration to various other cloud services from the same provider. For example, if you are using the AWS platform for chatbots, then you can use DynamoDB for the database, write programming logic as Lambda functions, and expose them through the API Gateway. Session key Takeaways The main question is how to write code which is serverless compliant. This is where this session will help you. This talk will help people to move a step ahead of the traditional way of writing code as some of you had already developed chatbot, I will share how can you can write the simple chatbot in python and can take leverage of serverless to deploy and publish. I will cover Serverless Framework principals AWS Lambda, Amazon Lex and API Gateway How to write a chatbot in python and create a Lambda function How to troubleshoot in a serverless world", + "Last Updated": "14 May, 2018", + "Prerequisites": "Basic knowledge of python and development in general", + "Section": "Others", + "Speaker Info": "Vaibhav Singh is an undergrad final year student of BML Munjal University, Gurugram. He had worked with AWS services as a solution architect intern in Amazon and he is also open source enthusiast and contributed to many open source organization like Fossasia, coala, etc. He is now Google Summer Of Code intern with FOSSASIA. Previously, He was the finalist winner in Codeheat competition. I write mostly in python ;). I had written various small scripts to make my life easier :", + "Speaker Links": "Website GitHub Twitter Facebook Linkedin Mai", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Vaibhav Singh (~vaibhavsingh97)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-serverless-framework-build-a-chatbot~eZXgb/", + "title": "The Serverless Framework - Build a Chatbot" + }, + "174": { + "Content URLs": "Sensor Fusion Introduction\nhttps://youtu.be/C7JQ7Rpwn2k Sklearn Quick Tutorial\nhttp://scikit-learn.org/stable/tutorial/basic/tutorial.htm", + "Description": "Abstract The primary purpose of this talk to describe how we are using python and Sklearn to model and analyse time series sensor data. In particular, I will walk through how we use Python to process data from an IoT enabled sensor attached to a cricket bat, build machine learning models on the data, and use open source tools to deploy our models in the sensor device as a smart IoT application. Description With the steep increase in the number of smart-things connected to the internet, the amount of data that is being generated by such devices is increasing exponentially. However, much of that data is not useful and therefore filtering unuseful data is an important task. How do we filter the important part and remove the noise from sensor data streams to generate actionable insights? To demonstrate the problem we are placing a sensor device on a cricket bat. The IoT device is a miniaturised, wireless MEMS inertial measurement unit (IMU). The IMU incorporates three-axis sensing of bat acceleration and angular velocity with a low-power Bluetooth to transmit this data to a mobile. First, we gather event-based data rather than storing the entire stream. This again poses the question: how do we define an event? What makes an event unique from the surrounding \u2018non-event\u2019 context? These are some of the questions that need to be answered in order to define an event. Watching a cricket batter stand and prepare to swing, the human brain continuously filters its visual perception and is able to detect and differentiate a swing from the pre- and post-swing activity. We need to be able to automate that same process. Some data instances can be tagged while other can\u2019t be. This helps in training and evaluating machine learning models later. Secondly, After we have extracted time series data based on the instances, we can start analysing these event-based sets of data to understand the language of sensor data. For this, we are using Jupyter Lab to interactively work with data. How does an accelerometer data depict the real world physical motion? This step helps us find the relation between the real world actions and the sensor data set. Well, the extraction process will be prone to noises. The data comes in CSV files, python seems the right choice for us to read and analyse the data. Pandas and offer data frames that come handy to rapidly form and validate hypothesis interactively in Jupyter notebooks. Any analysis is incomplete without visualisation, that's where Matplotlib helps us understand the data better. We quickly test the machine learning models by using Sklearn, which has most of the standard algorithms already implemented. This keynote will describe some of the analysis (along with python code) to show how we have taken several steps right from forming the hypothesis to implementing a solution in the device level layer. All of this demonstrates how Python and its rich set of libraries are helpful in forming solutions to some of the product related features. Thirdly, we need to automate the task of classifying a particular instance from the stream. For this to happen, we can either feed a machine learning model or create a rule-based algorithm which can classify the events into buckets. Now every step has its own set of challenges, firstly the application we are working on involves using motion sensors attached to the back of a cricket bat. There are network constraints in the field. If a sportsperson wants to know real-time analytics from the device, the segregation needs to happen offline. We have to deploy the models on the miniature sensor devices because sometimes the players don\u2019t even carry their mobile phones to the playing area. Therefore our objective is to enable the devices to remain independent in running machine learning algorithms by themselves", + "Last Updated": "14 May, 2018", + "Prerequisites": "Participants should have an understanding of python basics", + "Section": "Data science", + "Speaker Info": "Sanjiv Soni is a data scientist at Str8bat, Bangalore. He currently an international fellow at University of San Francisco for Deep Learning Programme. Sanjiv has experience with Software and product ecosystem. He has interests in building software devised solutions to problems solved by humans", + "Speaker Links": "https://twitter.com/sanjivsoni7 https://www.linkedin.com/in/sanjiv-soni", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "sanjiv soni (~sanjiv)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/swing-and-a-miss-deploying-machine-learning-models-for-iot-enabled-devices-using-python~bYXYa/", + "title": "Swing and a Miss: Deploying machine learning models for IoT enabled devices using Python" + }, + "175": { + "Content URLs": "https://atad.xyz\n[ Will share the GitHub repo during the talk with sample web crawlers ", + "Description": "Introducing to Web Scraping. A complete walkthrough the below items: Challenges in scraping websites and parsing the data, Introducing Scrapy, a widely used framework to extract data Dos & Don'ts Usage of Proxies & IP Rotation Crawling hundreds of websites, running and scaling them to huge volumes", + "Last Updated": "14 May, 2018", + "Prerequisites": "Laptop with Ubuntu or a similar OS. \nPython and MySql latest versions Basic understanding of Python and MySql\nGood to have knowledge in writing Xpaths and usage of proxie", + "Section": "Data science", + "Speaker Info": "I am Raja Emmela, \nI Run Headrun Technologies, Bangalore - helping clients in Data Scraping and Web Applications We are in this space for the last seven years, extracting data and parsing them. My experience helps do share the challenges we faced with domestic and NA & APAC clients while scraping websites and the don'ts in particular", + "Speaker Links": " LinkedIn Twitter Blog", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "rajaemmela", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-intro-to-web-scraping-dos-donts-and-the-challenges-in-scaling-it-to-huge-volumes~eXVVb/", + "title": "An intro to Web Scraping, dos & don'ts and the challenges in Scaling it to huge volumes" + }, + "176": { + "Content URLs": "https://github.com/devxp", + "Description": "My talk is related to my work on ZProc , a library for doing multiprocessing in python Its provides a high-level wrapper over zeroMQ, the distributed messaging library. I will provide a basic introduction to the ways we can natively implement concurrency/parallelism in our applications and how ZProc is a better way to do multi-tasking", + "Last Updated": "14 May, 2018", + "Prerequisites": " A good knowledge of basic python. Some knowledge about the python Process/Thread interface is appreciated If you ever had your hands on the zguide , I have a hunch you'll like this. ", + "Section": "Developer tools and Automation", + "Speaker Info": "I'm 19 year old python programmer, picked up python when I was around 15. My adventures with multi-tasking applications started when I was 17, trying to build a concurrent youtube downloader. I am since, trying to find ways to make writing concurrent, multi-core applications simpler in python", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Dev Aggarwal (~devxpy)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/zproc-process-on-steroids~bWBoa/", + "title": "ZProc - Process on steroids" + }, + "177": { + "Description": "A lot of budding programmers use print() function or logging module to display the state of the program. However, it soon becomes untenable to reason about the program in a barrage of print statements. At that time, a debugger is a must. Debuggers are a better and structured way to inspect a program. A practical and basic understanding of debuggers will help in locating bugs easily and save developer's time and unnecessary frustration. In this talk, we are going to learn the terminology associated with debugging and explore the most commonly used commands of pdb", + "Last Updated": "14 May, 2018", + "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college students or people who just started programming in Python", + "Section": "Core python and Standard library", + "Speaker Info": "I'm currently a Senior Web Developer and Curriculum Designer at Pesto Tech. I've programmed in Python and Flask since the last 3 years. Open source enthusiast, and frequent blogger", + "Speaker Links": "Medium - https://medium.com/@arfatsalman Twitter - https://twitter.com/salman_arfat GitHub - https://github.com/ArfatSalman LinkedIn - https://www.linkedin.com/in/arfatsalman", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Arfat Salman (~ArfatSalman)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-basics-and-debugging-python-scripts-with-pdb~eVZoe/", + "title": "Debugging basics and debugging python scripts with pdb" + }, + "178": { + "Description": "Millions of visitors visit business websites every day and each one of them takes different set of steps in order to seek the right information/product. Yet most of them leave disappointed or dejected for some reason and very few get to the right page within the website. In this kind of situation, it becomes difficult to find out if the visitor actually got the information that he was looking for? Also, the individual journeys of these visitors can\u2019t be compared to each other since every visitor has done different set of activities. So, how can we know more about these journeys and compare these visitors to each other?\nSequence Embedding is a powerful way that offers us the flexibility to not only compare any two distinct visitors entire journey in terms of similarity but also to predict the probability of visitor\u2019s conversion. Sequence embeddings essentially helps us to move away from using traditional features to make predictions and considers not only the order of the activities of a user but also the average time spent on each of the unique pages to translate into more robust features and used in Supervised Machine Learning across multiple use cases (next possible action prediction, converted vs non-converted, product classification)\u00a0.Using traditional Machine learning models on the advanced features like sequence embeddings, we can achieve tremendous results in terms of prediction accuracy but the real benefit lies in visualizing all these user journeys and observing how distinct are these paths from the ideal ones. This session will unfold the process creating sequence embeddings for each user\u2019s journey in python and use them to build machine learning classification model to predict visitor conversion along with comparing all the user journeys in terms of similarity score", + "Last Updated": "14 May, 2018", + "Prerequisites": "Basic understanding of Machine Learning ,\nPython Basic", + "Section": "Data science", + "Speaker Info": "Co-Founder of DataScienceBridge and currently Sr. Data Scientist at SapientRazorfish core Data Science Team has around 8 years\u2019 experience in the industry, ranging from large scale IT enterprise business development to building complex Machine Learning models by applying state of the art techniques. He has completed his Master\u2019s in Business at Symbiosis International University and certified professional in Machine Learning from IIM-Calcutta.\nHis core expertise involves Machine Learning, Deep Learning, Recommendation Systems using python, spark and Tensorflow for various projects. He is president of Data Science meet up group at SapientRazorfish and conducts multiple webinars on Machine Learning. Along with that he is also a speaker and recently presented a talk at \u201cGreat Indian Developer Summit \u201c(GIDS 2018).\nIn his spare time, he likes to read, code and help aspiring Data Scientists", + "Speaker Links": "https://www.youtube.com/watch?v=Nbpz79v2y5", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Pramod Singh (~pramodchahar)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sequence-embeddings-in-python-classification-user-journey-comparison~dRBwd/", + "title": "Sequence Embeddings in Python: Classification & User journey Comparison" + }, + "179": { + "Content URLs": "For workshop home here and here such as to get sample data, Jupyter notebooks, slides etc For workshop slides pls see her", + "Description": "Geospatial representation are so prevalent in day to day life, such as even in simple travel related conversation to maps, aerial/satellite images etc. In digital era, geospatial data is extensively produced and consumed in ever growing proportion. Python with its free and open source libraries are giving wide variety yet simple and effective set of tools to visualise and analyse geospatial data. The current workshop is directed for beginners of Python programming language, who have basic understanding on computing and data formats. The primary objective of the workshop is to introduce and give hands on training on selected list of FOSS libraries for geospatial analysis. The workshop as a do it yourself fashion tries to solve two real world problems in Geographical Information System (GIS) and its geospatial data sources. The workshop comprised of three components: Component 1 Python environment and work flow setup, an assisted task of setting up the Docker and Jupyter notebook setup. Setting up the Geographical Information System (GIS) environment with extended discussion. Setting up of GIS tools such as FOSS QGIS and Google earth. This component is comprised of four exercises. 1. Introduction to vector data, 2. Introduction to raster data, 3. binary and text file formats of geospatial data, 4. Introduction to tools of GIS, 5. Introduction to literal programming- Jupyter notebook Component 2 Find characteristics of road network(type of road network, length of the type) within a 1X1 km grid. The data source is Open Street Map (OSM) road network data on a city level (60X60km size). This operation is operationally simple such as measure a line feature but computationally intensive as the operation comprised of geometry within operation on dense road network seen in urban setup. Libraries such as Shapely, Fiona, Geopandas and rtree index will be used for the fast processing of this operation. This component comprised of three exercises 1. Find distance between two points 2. Find distance between two points constrained by another vector 3. Find distance between large number of points in for loop Component 3 Find cloud cover percentage over area of interest. The data source is Landsat satellite imagery. Searching cloud free Landsat images over an Area of Interest for a temporal extent of a year or more is manual and time consuming. Applying cloud cover detection algorithm could make this operation automatic. Libraries such as rasterio, Geopandas, Fiona, and libraries related to landsat algorithms will be used for this task. This component comprised of two exercises 1. Convert the imagery in geotiff into numpy arrays 2. Apply the algorithms to find the cloud cover Workshop Plan Introduction and setup- 30 minutes Component 1- 30 minutes Component 2- 45 minutes Component 3- 45 minutes", + "Last Updated": "12 May, 2018", + "Prerequisites": " Laptop 32bit/64 bit Workshop material is tested on 64 bit computer, it is said to be working in 32 bit, lets experiment! A copy of Docker container image from here , file from the link foss-pt-gsa_v3.tar.gz is 2.5 GB in size, will be using this container for DIY Local copy of Docker toolbox from here for windows 64 bit, for 32 bit Windows, follow this link , if any issue, don't worry, we have a session for setting up the docker! Local copy boot2docker.iso from here , we will be following old method of docker toolbox instead of docker native software for Windows.", + "Section": "Data science", + "Speaker Info": "I am a research associate at UrbanEmissions.info . My doctoral study was related to interoperable management of data from air pollution monitors and atmospheric models. I used free and open source libraries of Python for the study, especially on geospatial data compilation, analysis and visualization. Freedom and customization of free and open source languages such as of R and Python were immense. After Conda python package manager came into existence, the world of Python was so easy and I started to use Python for most of computing", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "nishadhka", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/free-and-open-source-libraries-of-python-for-geo-spatial-analysis-and-visualisationmaps-and-satellite-imageries~aQL5e/", + "title": "Free and Open Source libraries of Python for Geo spatial Analysis and Visualisation(Maps and Satellite imageries)" + }, + "180": { + "Content URLs": "https://github.com/bhagvank https://ingeniopythonis.wordpress.co", + "Description": "Video content management, AI, Blockchain and Virtual/Augmented reality technologies are changing the learning management platforms. Customer focused learning systems are emerging in enterprises. Enterprises are structuring their curriculum products to help solve the high value use cases of their customers. Members of the LMS system (python/ Django stack) can tailor their educational experience by choosing courses based on their learning styles. The courses are becoming more effective and helping members retain information. Platforms are differentiating by providing better, faster ways to find relevant content, whenever and wherever learners need it. Modern learning management platform is an end-to-end eLearning solution which has capabilities to create, distribute, edit and manage entire courses from start to finish independent of the content. Educational success and fulfilment are achieved through personalization and optimization of the learner\u2019s path through courses and gaining of competencies. This new class of learning technology vendors is making it possible to augment their systems with cloud-based applications which can be easily integrated with an enterprise-scale technology ecosystem. Enterprises are now tracking and analyzing learning experiences with incredible precision which can be used to improve ongoing program and business outcomes. Tracking and reporting comes in learner-oriented dashboards and reports built for the staff", + "Last Updated": "12 May, 2018", + "Prerequisites": "python, djang", + "Section": "Data science", + "Speaker Info": "Co-Founder of Architect Corner, Bhagvan has around 18 years experience in the industry, ranging from large scale enterprise development to helping incubate software product startups. He has completed a Masters in Industrial Systems Engineering at Georgia Institute of Technology, and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras", + "Speaker Links": "https://www.youtube.com/channel/UChu9J4M85CC7C8hMYp5cgRg/video", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "bhagvank", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-management-next-generation-platform~dPJ6a/", + "title": "Learning Management : Next Generation Platform" + }, + "181": { + "Content URLs": "https://nim-lang.org http://slides.com/akapatkar/nim-for-python-programmer", + "Description": "Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org As Python programmers, we are used to a language which is expressive, intuitive and versatile. Python is widely lauded for its productivity, minimalistic syntax, standard library feature set and is an inspiration to newer languages like Go, Swift, and Julia. However, there are some areas like speed, distribution, and multicore processing where it lacks a good solution. Nim is a statically typed and high-performance garbage-collected language which builds upon Python\u2019s strengths and addresses someone its weakness in an innovative way. This talk introduces Nim to Python programmers by diving into powerful language design, syntax, data and control structures, static analysis, metaprogramming, portability/distribution and standard library features. At the end of this talk, you should have learned enough to a) get started with Nim on a project b) get familiar with Nim\u2019s growing ecosystem c) leverage/extend existing Python skills on a Nim project. Timeline breakdown: 1) Intro to Nim (10mins) 2) Language tour from Python\u2019s point of view (20 mins) 3) Things you can do with Nim + ecosystem (5 mins) 4) Q&A (5mins", + "Last Updated": "12 May, 2018", + "Section": "Others", + "Speaker Info": "I am a language enthusiast and a Python developer at Netflix. I\u2019ve been learning and using Nim for over a year now and I have benefited immensely from its learnings. There is a strong correlation between Nim and Python and I would like to explain that to the audience and show them a way to think problems using Nim\u2019s construct which I am sure will help them improve their Python skills. I am currently using Nim to write an interpreter for \u2018lox language\u2019. More details here https://github.com/cabhishek/nimlo", + "Speaker Links": "International Conference Talks: PyCon Ukraine 2018 https://2018.uapycon.org/#schedule PyCaribbean 2018 http://pycaribbean.com/schedule.html Python San Sebastian 2017 http://pyss17.pyss.org/", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Abhishek Kapatker (~abhishek69)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/nim-for-python-programmers~aO9Ed/", + "title": "Nim for Python Programmers" + }, + "182": { + "Content URLs": "https://github.com/DL4Jets https://docs.google.com/presentation/d/1dDxxsMkfg8vwMi7QDkDaVwCQnxsaXVh9-6xrgrkLvnY/edit?usp=sharin", + "Description": "Ever wondered if you could build your own deep learning framework for hundreds of users? Well, we did build one and turns out it's not as hard as it sounds. With thousands of people working towards democratising artificial intelligence (AI) , we have seen an explosion in the availability of machine learning libraries that make it simpler to build and deploy models for a wide range of tasks. From finance to art, every field has been revolutionised by the introduction of AI. At the European Organisation for Nuclear Research (CERN) we work on understanding the fundamental particles that constitute the universe by performing various experiments in particle physics. Of late, we have experienced a stratospheric rise in deep learning applications to various problems - RNNs, CNNs, and GANs - that have yielded promising results. Like, this stuff is craaazy, dude. It works! We delve into the development of one such project as it evolves from a set of scripts into a full-blown framework with multifarious applications in high-energy physics. In this talk we will detail the evolution on the DeepJet Python environment. Specifically, we will start with the problem(s) we were facing and how we evolved from a set of scripts hastily patched together to a structured, cross-platform framework built on top of Tensorflow and Keras. The library is a WIP so we're shipping updates on a daily basis with the goal of improving usability with focus on documenting our existing code base. Initially envisaged to support the development of the namesake jet-tagger in the CMS Experiment at CERN, it has grown to encompass multiple purposes within the collaboration. It is aimed at outlining how to go from a set of scripts to building a library that is used by hundreds of scientists in the world's largest physics research collaboration. The presentation will describe the major features the environment sports: simple out-of-memory training a with multi-threaded approach to maximally exploit the hardware acceleration, simple and streamlined I/O to help bookkeeping of the developments, and finally Docker image distribution, to simplify the deployment of the whole ecosystem on multiple datacenters. The talk will also cover future development, mainly aimed at improving user experience. ", + "Last Updated": "12 May, 2018", + "Prerequisites": "Preferred (but not necessary): Experience working with virtual environments or anaconda Basic knowledge of concepts in machine learning", + "Section": "Data science", + "Speaker Info": "Swapneel is a computer scientist working at Compact Muon Solenoid (CMS) Experiment at the European Organisation for Nuclear Research where physicists and engineers are probing the fundamental structure of the universe. They use the world's largest and most complex scientific instruments to study the basic constituents of matter \u2013 the fundamental particles. His work at CERN encompasses the creation of a framework that can facilitate the use of deep neural networks and provide a suite of functions to serve multiple use-cases such as jet classification, particle reconstruction, and so on. He is an open-source enthusiast, writing and contributing to various projects in his free time", + "Speaker Links": "https://opensourceforu.com/author/swapneel-mehta/ https://medium.com/@swapneel_mehta http://www.ccdev.in/swapneel-mehta/ https://github.com/swapneel", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Swapneel Mehta (~SwapneelM)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-deep-learning-framework~dN18b/", + "title": "Building a Deep Learning Framework" + }, + "183": { + "Content URLs": "", + "Description": "A short and crisp interactive session for the first time attendees of PyCon India to help them navigate through the conference and make the most of the next 4 days. 2011 was my first PyCon and in hindsight was a major turning point in my professional life. The experiences I had, the people I met and the friends I made during the conference are still shaping the choices I make and the decisions I take even today. PS: This will be a heavily opinionated talk and the attendees will be requested to weigh the advice being shared and adapt the ones that suit them the most. The audience will be implored to introspect and answer the following and more for them Which talks to attend? How to decide which talks to attend. Can I walk out of a talk in the middle? Should I attend every talk? What is the hallway track? Should I talk to strangers at the conference? How to start talking to strangers? Can I volunteer now that the conference is already happening? The volunteers are awesome people will they accept my help? How can I help? Should I help the volunteers? What is the dev-sprint? How to make the most of the dev sprint? I just started learning python, will people make fun of me if I speak? i need a job, what should I do? I need to hire, what can I do?", + "Last Updated": "12 May, 2018", + "Prerequisites": "A ticket to the conference, willingness to learn, un-learn and re-learn", + "Section": "Core python and Standard library", + "Speaker Info": "Anuvrat has been a part of PyCon India since 2011 where he found enlightenment and confidence to take charge of his education and steered his career in a direction that feels like success at least to him. These days, along with his team at https://essentiasoftserv.com he consults for companies that need assistance maintaining, scaling, and sanitizing their python based codebase", + "Speaker Links": "https://anuvrat.i", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Anuvrat Parashar (~bhanuvrat)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-make-the-most-of-pycon-india-2018~dLBva/", + "title": "How to make the most of PyCon India 2018" + }, + "184": { + "Description": "So you started learning python, and you have been able to stitch few lines of code together and it worked, but you do not know why, then this is the talk for you. We will delve into elementary yet obscure concepts that are more often than not skipped by beginners eg why is if _ name_ == _ main_ required in python scripts. et el. In a 3 hour power packed interactive and fully-hands on workshop we shall be learning python from ground up using examples from the real world. Basics of python will be covered with less emphasis on the basics of programming itself. The topics to be covered during the workshop shall include but not be limited to: Hello World Variables Loops and conditionals String Lists, Dictionaries and Tuples. functions File handling classes modules and imports lambda, map and reduce decorators and generators raising and handling exceptions sample exercises for the attendees to work on based on the concepts covered in the first half of the workshop.", + "Last Updated": "12 May, 2018", + "Prerequisites": "The person should be familiar with a *nix based operating system, and the shell should not be alien to them. Attendee should be familiar with the concepts of a hierarchical file system and at least be able to find where their editor saved the file they just created. Knowledge / experience of at least one other programming language will give them an unfair edge", + "Section": "Core python and Standard library", + "Speaker Info": "Anuvrat, along with his team at https://essentiasoftserv.com consults for python based projects which need help in maintaining, sanitizing and scaling to achieve their true potential.\nHe was one of the four who revamped the https://pydelhi.org community and volunteered for over a dozen https://pythonexpress.com workshops", + "Speaker Links": "https://anuvrat.i", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Anuvrat Parashar (~bhanuvrat)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/yet-another-introduction-to-python~aKE8d/", + "title": "Yet another introduction to Python" + }, + "185": { + "Content URLs": "The work in progress repository of all the associated code - fromscratchtoml . The official website of fromscratchtoml . The work in progress python notebooks . The author's github profile ", + "Description": "Each step we take we are closing in into a world of Artificial General Intelligence . All these so called modern inventions ignite a feeling of astonishment among newbie developers across the globe - seeking answers to how these things work from the very basic level. There are myriad resources available on the internet theorising machine learning algorithms. But - what these resources lack is something that can bridge the gap between the theoretical concepts and the actual coding aspects. When a relatively novice developer skim through the code of these libraries he can barely understand what exactly is going on behind the recondite code. In the midst of making the code efficient these libraries often come up with chunks of code which are barely comprehensible. fromscratchtoml The primary goals of this library is - to bridge the gap between the theoretical and coding aspects of machine learning algorithms. To write intuitive blogs as python notebooks so as to juxtapose theory and code . Explaining the fundamentals of the algorithm from the very basics. To minimise the use of external dependencies except the fundamental ones like numpy and matplotlib . To make sure that the developed algorithms are coherent with already existing machine learning frameworks. The library is still in a nascent stage but will take shape in a couple of months. Given that the commit frequency is huge. The audience is requested to be patient. LIME (Local Interpretable Model-Agnostic Explanations) - When you are writing a machine algorithm from scratch you want to make sure that your results are coherent and your model is learning the features it is meant to learn. LIME explains why your model behaved the way it did. I will quote excerpts from their blog below - Imagine we want to explain a classifier that predicts how likely it is for the image to contain a tree frog. We take the image on the left and divide it into interpretable components (contiguous superpixels). As illustrated below, we then generate a data set of perturbed instances by turning some of the interpretable components \u201coff\u201d (in this case, making them gray). For each perturbed instance, we get the probability that a tree frog is in the image according to the model. We then learn a simple (linear) model on this data set, which is locally weighted\u2014that is, we care more about making mistakes in perturbed instances that are more similar to the original image. In the end, we present the superpixels with highest positive weights as an explanation, graying out everything else. Even from a human's perspective these explanations do make sense. BONUS - MrMark (A personal customisable assistant integrated with Google assistant ) - I am going to use Mr. Mark to vocally invoke commands like ' open LIME explanations for RNN , train CNN for face recognition ` etc.. TODO Write timelines. prepare content specific for presenting. DISCLAIMER - All the content related to LIME belongs to their respective owners", + "Last Updated": "11 May, 2018", + "Prerequisites": "Novice level experience of python and development in general. Acquaintance with basic machine learning will be a plus", + "Section": "Data science", + "Speaker Info": "I have graduated from IIT ISM Dhanbad in 2017. In daytime I work for a London based startup - ALIS labs , at night I am a bug buster vigilante working for my organization jellAIfish where I am the author of fromscratchtoml . I am also RaRe's incubator program member - the same organization which looks after the reputed topic modelling library gensim . I will be giving a demo prep-talk for this proposal in Hyderabad Python Meetup group on 2nd June 2018", + "Speaker Links": "Author's open source contribution can be seen at his github profile where it all started. Author's current blog where he discussed a 'bit' about the impact of AI. Author's old blog archive where he talked about random developer stuff. Author's another delusional repository which he has trouble explaining to people. Author sometimes also blogs for RaRe technologies . Author is omnipresent on the web by the handle markroxor ", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Mohit Rathore (~markroxor)", + "created_on": "11 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/from-scratch-to-ml-the-machine-learning-library-you-really-understand-and-explaining-its-predictions-with-lime~dJXya/", + "title": "From scratch to ML - The machine learning library you really understand and explaining its predictions with LIME." + }, + "186": { + "Content URLs": "Repository for the content", + "Description": "Orbital Mechanics/Astrodynamics is one of the most difficult things to understand and take care of! For this simple reason it is called \"Rocket Science\". poliastro is a python package intended to make Astrodynamics Open Source, and easy to understand and visualise. Through the talk, various modules of the poliastro package will be introduced. I will show how we can solve very complex Orbital Mechanics problem in 2 minutes that takes years for a scientist to solve manually! The talk will cover some parts of AstroPy, numba and a bunch of plotting libraries such as matplotlib and plotly", + "Last Updated": "09 May, 2018", + "Prerequisites": "Basic introduction to plotly , matplotlib . Knowledge of some core packages like numpy, etc is beneficial. Knowledge of some of the core Astronomy libraries such as AstroPy is also beneficial", + "Section": "Data science", + "Speaker Info": "I am Shreyas Bapat, half \"Electrical Engineer\" and a passionate developer. I study at Indian Institute of Technology Mandi and constantly contribute to open-source projects. I have contributed to some projects like plotly, dash, poliastro and astroquery. I like Astronomy and related fields a lot and hence keep searching for projects related to that. Also, I am into Deep Learning from quite a time and love tweaking Neural Networks to get amazing results. I am the co-ordinator and maintainer at STAC-IITMandi . I have mentored the Astronomy Code Camp organised by Nehru Planetarium and Astronomical Society of India", + "Speaker Links": "GitHub Profile : shreyasbapat Find my contibutions in Poliastro at #4 : https://github.com/poliastro/poliastro/graphs/contributor", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Shreyas Bapat (~shreyasbapat)", + "created_on": "09 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/through-python-to-the-stars-orbital-mechanics-made-easy-and-open-source~dGK5d/", + "title": "Through Python to the Stars! - Orbital Mechanics Made Easy and Open-Source" + }, + "187": { + "Content URLs": "Github and presentation will be uploaded shortly", + "Description": "Functional programming is an essential part of any programming language. It allows you to harness the language, performing tasks which can replace tens of lines with just one. This is one programming paradigm which enables the programmer to give more importance to functions than classes. Instead of the traditional approach, we shall solve problems by using functions. A ramp up with Collections and a little bit of Object Oriented concepts in python, Functional Programming can be a great curve to harness python's usability and simplicity. At the end of this session, participants will be able to use the collections library in python, list comprehensions , deal with classes , objects and write anonymous functions , lambda expressions and resolve traditional snippets to reduce , map and filters for each of the use case", + "Last Updated": "09 May, 2018", + "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college folks", + "Section": "Core python and Standard library", + "Speaker Info": "Currently working as a Software Development Engineer at Olacabs. http://sameera.me https://www.linkedin.com/in/sameera-sy During my freetime I try the below. https://stackoverflow.com/users/4303216/sameera-sy https://www.hackerrank.com/sameerasy https://leetcode.com/sameerasy https://doselect.com/@sameera.sy", + "Speaker Links": "Below are some of my sample works. https://github.com/sam95 I have also conducted a webinar on JS for JavaScript Meetup Bangalore group. https://github.com/sam95/js-for-newbies-3 https://www.youtube.com/watch?v=JXg1GT6zDGQ", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "sameeras", + "created_on": "09 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/functional-programming-with-python~eEQle/", + "title": "Functional Programming with Python" + }, + "188": { + "Description": "React has been out there for quite some time now and its arguably one of the hottest front end frameworks out there. But MERN architecture hasn't caught up. And that's what I want to teach/discuss in my talk at pycon. How MERN could be the hottest kid on the block in the upcoming days", + "Last Updated": "08 May, 2018", + "Prerequisites": "Javascript\nBeginner level React.\nLittle to no knowledge of Node, Express and Mongo", + "Section": "Web development", + "Speaker Info": "https://himanshuc3.github.io/\nSolving problems bit by bit. After all, computer is just bits. Cracking PJs and living life to not make the most of it but make the most of me", + "Speaker Links": "https://github.com/himanshuc3\nhttps://medium.com/@himan\nhttps://drive.google.com/file/d/1wzhC56jvrriO6XOogapWE2aOMN8Afsiz/view?usp=sharin", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Himanshu Chhabra (~himanshu87)", + "created_on": "08 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mern-could-be-the-buzz-word~bDEkd/", + "title": "MERN could be the buzz word" + }, + "189": { + "Content URLs": "https://github.com/rahulbajaj0509/Automation-with-Ansibl", + "Description": "Ansible is software that automates software provisioning, configuration management, and application deployment. Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications\u2014 automate in a language that approaches plain English, using SSH, with no agents to install on remote systems. This workshop introduces a beginner to basic fundamentals of Ansible with easy to do hands-on exercises. The workshop introduces basic use cases of Ansible followed by an introduction to Ansible Inventory, Playbooks, Modules, Variables, Conditionals, Loops and Roles. Each mentioned topic is accompanied by a set of coding exercises giving the attendees a hands-on experience in developing Ansible Playbooks. Introduction to configuration management [15 mins] What is configuration management?\nAgent vs Agent-less\nPush and Pull configurations.\nImperative vs Declarative DevOps Concepts [10 mins] Infrastructure as code.\nDeterministic Builds/Deployments.\nIdempotency.\nCommunications channels \u2013 Message Queueing vs SSH Introduction to Ansible [30 mins] Requirements\nInstallation\nConfiguration Working with Ansible [100 mins] Ansible Inventory\nPlaybooks\nModules\nVariables\nConditionals\nLoops\nRoles\nAnsible Galaxy Ansible in DevOps environment [20 mins]\nQuestions and Answers [10 mins", + "Last Updated": "07 May, 2018", + "Prerequisites": "Pre-Requisites Basic Linux Administrator Skills\nOpen mind and spirit to learn. Software Requirements We will be using two centos7 vagrant machines for the workshop. Make sure you are using a Linux distribution and have vagrant configured with any of the providers like libvirt, virtual box, etc.\nIf you are unable to install vagrant on your Linux systems, then you might want to install Fedora operating system and come for the workshop, we can do the rest together", + "Section": "Developer tools and Automation", + "Speaker Info": "Rahul is an Associate Software Engineer, Red Hat. He is a part of the official foreman organization(https://github.com/rahulbajaj0509). He contributes mostly to the Foreman project and is a \u2018Red Hat Certified Specialist in Configuration Management\u2019. He is also the organizer of Foreman Pune Meetups", + "Speaker Links": "Blog: https://rahulbajaj05.wordpress.com/\nGithub: https://github.com/rahulbajaj050", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Rahul Bajaj (~rahul56)", + "created_on": "07 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automation-with-ansible-beginner-to-advanced~azY2e/", + "title": "Automation with Ansible: beginner to advanced" + }, + "190": { + "Content URLs": "https://docs.google.com/presentation/d/1DE-_l9N8Scu-M8d_bFxuKQak3TYipEDsGX5HIsB59s0/edit?usp=sharing PS: First Draft, need to organize it better and improve the demos", + "Description": "Dask is a general purpose parallel computing system capable of Celery-like task scheduling, Spark-like big data computing, and Numpy/Pandas/Scikit-learn level complex algorithms, written in Pure Python. Dask has been adopted by the PyData community as a Big Data solution. This talk focuses on the distributed task scheduler that powers Dask when running on a cluster. We will start by comparing Dask with the other solutions that are available for big data ETL and analytics . We will talk about how easily you can parallelize the work loads that you do with your favourite scipy libraries for eg Numpy, Pandas etc. Lastly we will also talk about how you can integrate Dask with your existing code and parallelize it's work load", + "Last Updated": "07 May, 2018", + "Prerequisites": " Good understanding of Python Programming Must have used any scipy library before Nice to have some idea regarding the big data tools available for analytics and ETL", + "Section": "Data science", + "Speaker Info": "I am an enthusiastic developer and aspiring entrepreneur who holds a particular passion for the intersection of web development and emerging technologies. I am constantly exploring innovative ways to solve real world problems and improve existing solutions. I genuinely enjoy working with people, taking risks, and developing new applications. I am currently working at Dubizzle as a Associate Software Engineer. Previously I worked at Corridor Funds as a Technology Architect where I built and Architected a data driven Loan valuation and Portfolio Management tool for retail and institutional lenders. I am open source contributor at Gluster, FOSS Asia, NGUI and GDG. Previously I lead a GDG Chapter in Gujarat. I have also spoken at tech meet ups and conferences like Women techmakers, Google Devfest, Google Cloud Next Extended, Mozilla Gujarat, Local GDGs and Startup Gujarat. In addition to that, I am always experimenting with new and interesting side projects", + "Speaker Links": " Github: http://github.com/smitthakkar96 Linkedin: http://linkedin.com/in/smitthakkar96", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "smit thakkar (~smitthakkar96)", + "created_on": "07 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/dask-distributed-data-science-in-a-pythonic-way~axLPa/", + "title": "Dask: Distributed Data Science in a pythonic way" + }, + "191": { + "Content URLs": "Will be uploading soon", + "Description": "Almost all developers spend countless hours on configuring, tweaking and micro-managing their dotfiles with an obsession to exactly have them like one wants them to be. I do too . Dotfiles are just configuration files like .vimrc and .gitconfig on your OS, that stores the settings you have for applications/environments/tools to make life easier while giving you more portability. Well, do you have to use bash scripts for initial setups of your dotfiles? or do you want to setup your dotfiles but don't want to learn or be limited by Bash? Do you forget to update/maintain your dotfiles periodically? Do you struggle with the installation of applications later on? \n Well, Python could be the answer to all of your problems. With Python, one can easily manage , maintain and do a lot more with their dotfiles. My talk would start with a basic intro of what exactly are Dotfiles? and what is the common way of setting them up? This helps beginners who are new to the topic, get interested and a quick recap of why dotfiles are important for all developers. Building up the momentum by visual queues and comparisons through slides, I would show how exactly Python does the same using Homely as Bash does. Later, work through the more intricate details by talking about the features one can implement using Homely and Python highlighting limitations of bash. Like Automation , Logging , git control , debugging , installation of applications and so much more . Summing up by demonstrating a number of scripts that I will be preparing in-advance to showcase the same features that we just talked about. This helps people grasp the talk, the topic, and \" the why we are doing, what we are doing \" part. Ending the talk , with a round of questions and showing the setup I use after months of searching through dotfiles repositories to leave them open to all the options they can choose from for setting up their dotfiles and pick the best setup from the knowledge they just gained. Sub Category : Developer Tool", + "Last Updated": "07 May, 2018", + "Prerequisites": "A laptop computer running any flavor of Linux. It would help if python 3 is already installed. Coming without a laptop is also fine. The presentation would be enough to understand", + "Section": "Others", + "Speaker Info": "I am a student who also happens to be Linux enthusiast, loves to code in Python, currently, part of Google Summer of Code 2018 under Sugar Labs and an active volunteer at PyDelhi and ALiAS . I friviously collect C&H comic strips because I like to... When I am not busy, I devote my time towards closing issues on GitHub and scooping through my twitter feed. Also, sometimes I like to write my thoughts and the things that I have learned on my blog, Mixster . Check it out", + "Speaker Links": "Professional Profile @ LinkedIn , Contribute @ GitHub , Blog @ Mixster I go by vipulgupta2048 all over the web. Feel free to connect/talk with me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Vipul Gupta (~vipulgupta2048)", + "created_on": "07 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/keeping-your-dotfiles-in-check-with-python~dw7Xd/", + "title": "Keeping your Dotfiles in check with Python" + }, + "192": { + "Description": "DNS is a non-encrypted protocol. DNS responses which are sent over UDP or TCP lack confidentiality, privacy and security. DNS often contains password files, geolocations, email service and fax numbers, certificate identity and pinning for TLS and much more. Parsing DNS without encryption would lead to different vulnerabilities such as eavesdropping and spoofing. DNS over HTTPS(DoH) is a web protocol that argues for sending DNS requests and receiving DNS responses via HTTPS connections, hence providing query confidentiality. DoH provides more than just privacy \u2013 it also helps guarantee the integrity of the response users receives their requests. Because the DNS response is invisible between responder and user, ISPs and others in the end-to-end network chain can't interfere with the responses. Moreover, Responses from the use of recursive resolvers to clients are the most vulnerable to undesired or malicious changes, because generally recursive resolvers do not encrypt any of your queries. Henceforth, we would be discussing the implementation and parsing of DNS over HTTPS. Further, we provided added support for handling IPv4 and IPv6 DNS packets (A + AAAA records) as well as support for EDNS for edns-client-subnet usage. The integration with HTTP provides a transport suitable for traditional DNS clients seeking access to the DNS. In the end, we will discuss how our client will be sending DNS queries and get DNS responses over HTTP using https:// and implies TLS security integrity and confidentiality. Furthermore, I plan to put some light on how DNSSEC validation is getting involved here with DNS resolution through HTTP to provide ultimate privacy and security support for \n the DNS packets", + "Last Updated": "06 May, 2018", + "Section": "Networking and Security", + "Speaker Info": "I\u2019m currently in my sophomore year, pursuing an undergraduate degree in Computer Science and Engineering from Amrita University. I\u2019m an active member of a FOSS club in our university(FOSS@Amrita). I started actively contributing to various open source organizations from the year 2016. Initially, I started my career in Open Source by contributing to KDE. I was selected for Season of KDE(KDE-SoK) 2016-17 in which I worked on an astronomy software named called Kstars. Further, I was selected for Google Summer of Code 2017 under KDE, where I worked on a project for a libre graphics software, Krita. My work involved introducing a data sharing module in it. The module enables communication between Krita and a remote KDE server in order to help users save and publish their data online. This also required modifying the underlying framework to enable client/server communication. I have been selected for Google Summer of Code for the 2nd time, where I am working on the project Wget2 under GNU organisation. I GSoC project involves adding support for DNS over HTTPS in Wget2. I was invited as a speaker for KDE India Conference 2017 in IIT Guwahati, where I gave a talk on the topic \u201cObject tracking using OpenCV and Qt\u201d. Further, I will be travelling to Austria on August to give a talk in KDE conference, Akademy and will be talking on the topic \"Strengthen Code Review Culture: rm -rf \u2018Toxic Behaviors", + "Speaker Links": "http://anikethfoss.wordpress.com http://gitlab.com/aniketh01/ https://conf.kde.org/en/Akademy2018/public/speakers/1", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Aniketh Girish (~Aniketh01)", + "created_on": "06 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/privacy-concerns-how-dns-resolves-over-https~avLnd/", + "title": "Privacy concerns: How DNS resolves over HTTPS" + } +} \ No newline at end of file diff --git a/cfp_crawler/scrapy.cfg b/cfp_crawler/scrapy.cfg new file mode 100644 index 0000000..cf9c257 --- /dev/null +++ b/cfp_crawler/scrapy.cfg @@ -0,0 +1,11 @@ +# Automatically created by: scrapy startproject +# +# For more information about the [deploy] section see: +# https://scrapyd.readthedocs.io/en/latest/deploy.html + +[settings] +default = proposal.settings + +[deploy] +#url = http://localhost:6800/ +project = proposal From 1fc026c09a913f850eab48b0ffc6bc78c36854dc Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Wed, 27 Jun 2018 13:40:16 +0530 Subject: [PATCH 02/17] added readme file --- README.md | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 README.md diff --git a/README.md b/README.md new file mode 100644 index 0000000..dfa5d6d --- /dev/null +++ b/README.md @@ -0,0 +1,2 @@ +# Basic Usage +scrapy crawl crawler From a3238b237435f49b0cbe9c8bcba81afa2aba240d Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Wed, 27 Jun 2018 13:40:52 +0530 Subject: [PATCH 03/17] Delete README.md --- README.md | 2 -- 1 file changed, 2 deletions(-) delete mode 100644 README.md diff --git a/README.md b/README.md deleted file mode 100644 index dfa5d6d..0000000 --- a/README.md +++ /dev/null @@ -1,2 +0,0 @@ -# Basic Usage -scrapy crawl crawler From 88a4f1a4507967611799e5664fe752edc21d6030 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Wed, 27 Jun 2018 13:42:39 +0530 Subject: [PATCH 04/17] Create README.md --- cfp_crawler/README.md | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 cfp_crawler/README.md diff --git a/cfp_crawler/README.md b/cfp_crawler/README.md new file mode 100644 index 0000000..04fdecc --- /dev/null +++ b/cfp_crawler/README.md @@ -0,0 +1,3 @@ +### Basic Usage + +scrapy crawl crawler From b00db07e200908f91417a5aab0d7a3a6010aeb1c Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Wed, 11 Jul 2018 09:19:00 +0530 Subject: [PATCH 05/17] Update crawler.py --- cfp_crawler/proposal/spiders/crawler.py | 13 +++++-------- 1 file changed, 5 insertions(+), 8 deletions(-) diff --git a/cfp_crawler/proposal/spiders/crawler.py b/cfp_crawler/proposal/spiders/crawler.py index a5f3700..23a73d8 100644 --- a/cfp_crawler/proposal/spiders/crawler.py +++ b/cfp_crawler/proposal/spiders/crawler.py @@ -7,22 +7,19 @@ class CrawlerSpider(scrapy.Spider): name = 'crawler' allowed_domains = ['in.pycon.org'] url = "https://in.pycon.org" - proposals = {} + proposals = [] file = open("proposals.json", "w") def start_requests(self): yield scrapy.Request(self.url + "/cfp/2018/proposals", callback = self.parse) def parse(self, response): proposal_links = response.xpath("//h3[@class='proposal--title']/a/@href").extract() - index = 1 for link in proposal_links: - yield scrapy.Request(self.url + link, callback = self.parseProposal, meta = {"number" : index}) - index += 1 + yield scrapy.Request(self.url + link, callback = self.parseProposal) + def parseProposal(self, response): - index = response.meta.get("number") - title = response.xpath("//h1[@class='proposal-title']/text()").extract()[0].strip() author = response.xpath("//p[@class='text-muted']/small/b/text()").extract()[0].strip() created_on = response.xpath("//p[@class='text-muted']/small/b/time/text()").extract()[0].strip() @@ -47,7 +44,7 @@ def parseProposal(self, response): some_dic["created_on"] = created_on some_dic["Last Updated"] = response.xpath("//time/text()").extract()[0] - self.proposals[index] = some_dic + self.proposals.append(some_dic) def format_data(self, data, head): return " ".join([d.strip() for d in data if d != "" and d!=head ]) @@ -63,4 +60,4 @@ def spider_closed(self, spider): json.dump(self.proposals, self.file, indent = 2, sort_keys = True) - \ No newline at end of file + From 1a2a1dd8c19e1b395edbc270f2b19590b110a761 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Fri, 13 Jul 2018 20:01:47 +0530 Subject: [PATCH 06/17] Delete proposals.json --- cfp_crawler/proposals.json | 2833 ------------------------------------ 1 file changed, 2833 deletions(-) delete mode 100644 cfp_crawler/proposals.json diff --git a/cfp_crawler/proposals.json b/cfp_crawler/proposals.json deleted file mode 100644 index 4760e24..0000000 --- a/cfp_crawler/proposals.json +++ /dev/null @@ -1,2833 +0,0 @@ -{ - "1": { - "Content URLs": "Would be uploaded soo", - "Description": "My talk would be starting from the very grounds of machine learning . What is it and how is it connected with our biological brain. I will be introducing some biological concepts and infrastructure of our brain to explain to them how our natural ability of thinking and deduction work, because at last the whole field of artificial intelligence is just an attempt to mimic our brain. Isn't it?\nThis will be through a series of fun QnA . Then we will see the mathematics core which enables us to lay down the logic and basics of the brain as formulas . \n- Then we will start with the classic linear regression . Will study the basic idea behind it and also see what kind of problems we should apply it.\n- Next will be the logistic regression , a classification algorithm. Learn the difference between these two and how logistic regression could be implemented and study the beautiful mathematics behind it. \n- Then we will go for a clustering algorithm, that is, Knn . Study the simple dynamics and application of this algorithm\n- Then a glimpse over the structure and mathematics of neural network . As this talk is for the novice I would keep the mathematics to the minimum and would no go deep into \"deep\" learning.\nWe will wrap up seeing some of my projects in action so that the audience could feel the power of AI", - "Last Updated": "27 Jun, 2018", - "Section": "Data science", - "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", - "Speaker Links": "udayupreti.m", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "uday1201", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/evolution-and-basics-of-machine-learning~bWzxa/", - "title": "Evolution and basics of Machine Learning" - }, - "2": { - "Content URLs": "http://www.thedurkweb.com/automated-anonymous-interactions-with-websites-using-python-and-tor", - "Description": "Need to get some repetitive task done on your web browser? Want to automatically fill boring forms? Or maybe you want to crawl pages that annoyingly check whether you are a browser or a robot. Or maybe you want to repeatedly bias an online poll in your favour (as long as you don't harm anyone). Circumvent all of that with Selenium, the browser automation tool. And if want you want to protect your IP while doing it then just fire up tor-selenium browser, which gives you the power of tor and browser automation. In this talk: I'll show you how to set up the browser. How to access the website through code. How to design your script to navigate through the pages and button clicks. How to effectively do your activity, like filling up text fields etc. And then a demo of it working completely.", - "Last Updated": "27 Jun, 2018", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ved Mathai (~ved47)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automate-anything-on-the-web-using-python-bindings-for-tor-selenium-and-hide-your-ip-while-doing-it~eVyXd/", - "title": "Automate anything on the Web using Python bindings for Tor-Selenium and hide your IP while doing it." - }, - "3": { - "Content URLs": "in progres", - "Description": "Data classes have been introduced in Python 3.7 (Refer to PEP 557 -- Data Classes). This talk is to introduce data classes to the audience. Talk about why data classes and how they are different from other alternatives like named tuples, et", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Knowlede of Object Oriented Programming with Pytho", - "Section": "Core python and Standard library", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.\nI have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delhi I have done a talk \"How import works in Python\" at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar\nlinkedin profile - https://www.linkedin.com/in/sasidonaparthi\ntwitter handle - @sdonapa", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/what-you-need-to-know-about-data-classes-in-python-37~dRrEd/", - "title": "What you need to know about data classes in Python 3.7" - }, - "4": { - "Content URLs": "Tutorial Series https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-2 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-3 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-4 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-5 Github Repo (Most starred repo for a Python implementation of YOLO v3, at 589 stars at the time of speaking) https://github.com/ayooshkathuria/pytorch-yolo-v", - "Description": "The workshop will walk the audience on how to implement a state of the art object detector (YOLO: You only look once) from scratch using the PyTorch deep learning framework. The main The aim is not to merely show the audience how to implement the detector that can work on videos, but give them a deep insight about the problems that rear their heads only when one is implementing a deep architecture. Some of these issues include, Rapid Prototyping with PyTorch : Which PyTorch classes and abstractions to use to quickly code up neural network. How to implement a layer if it doesn't already ship with PyTorch. Our detector has 3 such layers! How to deal with complex architectures efficiently : What if your network has more than a 100 layers? Our detector certainly has 106 ! Do we write 106 lines of code for each layer? What if we want to run our detector over a folder containing 100000 images that we can't fit into our RAM at once. Best PyTorch practices to get around problems like these will be discussed. Speeding up Python code with Vectorisation : Python can be a slow language, but PyTorch does provide a lot of functions that are merely wrappers for super fast C code under the hood. Vectorisation and broadcasting will be covered in great detail. Using vectorised code instead of loops to do iterative tasks can give speed ups as much as 100x. Our detector can not work in real time without these optimisations. Managing GPU resources : How to write device-agnostic code, parallelize GPU/CPU ops, practices to reduce redundant GPU memory usage, and how to time GPU code. We will review the entire code base, and spend much time on justifying design decisions. A lot of non-critical code will be provided as it is to the audience, while they are expected to code along when it comes to the critical parts. These parts would be discussed in greater detail. Important PyTorch features might also be demonstrated using toy examples outside the detector code base, which the audience is also expected to code along. A docker image as well as Jupyter notebook will be provided to the audience. Google Colab may also be considered with notebooks provided. Most of the tutorials online demonstrate how to write code that is more proof-of-concept rather than being performant. When it comes to learning to code complex architectures, especially when we are transitioning from beginner to intermediate stage, most of us have to rely on the laborious process of reading open source code. The idea of this workshop is to help audience move along this journey", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Knowledge of Python Basic understanding of convolutional neural networks, image classification and preferably, but not necessarily object detection (Will spend 15 min or so giving an overview of YOLO algorithm) Basic understanding of PyTorch (the level that can be reached by taking the official 60 min tutorial)", - "Section": "Data science", - "Speaker Info": "I'm currently an research intern at a DRDO Lab where I work on video semantics, detecting violence as well as unusual activity in surveillance footage. My other interests include weakl supervised, unsupervised learning and generative modelling using GANS. I've recently graduated college, and while at college, I founded AI Circle, SMVDU, a club dedicated to helping students get started with machine learning through lectures and hands-on sessions, many of which were conducted by me. I am very passionate about sharing what I've learned, and write articles regularly at Paperspace and Medium", - "Speaker Links": "Paperspace blog: https://blog.paperspace.com/author/ayoosh/ Medium : https://medium.com/@ayoosh Github : https://github.com/ayooshkathuri", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ayoosh Kathuria (~ayoosh)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-implement-a-yolo-object-detector-from-scratch-using-pytorch-and-opencv~aQq9a/", - "title": "How to implement a YOLO object detector from scratch using PyTorch and OpenCV" - }, - "5": { - "Content URLs": "Slides will be uploaded soon. Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv", - "Description": "There lies a huge gap between a website made as a hobby/college project and that made for professional purposes. The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! My talk is going to be about highlighting the flexibility and power python gives in this case.\nI'm going to share my experience of building a tool for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/). The tool summarizes the contributions of the Wikipedia editors and presents it in a CV-like format. The biggest challenge here was dealing with millions of edits and doing all the related computations within seconds. Without any kind of optimizations, the page took 3 hours to load. Through my talk, I want to bring out the journey from 3 hours to 3 seconds on the table! Broad outline of my talk is as follows: Deciding upon the web framework : In this, Django, Flask and Pyramid will be compared. Reducing the response time : When one is dealing with a dataset as huge as that of Wikipedia's, response time becomes of paramount importance. Optimizations like implementing a cache layer , using cron jobs , sessions etc will be discussed. Also, design choices will be compared - like cache layer using database vs sessions in python. Database Optimizations : In this I'll be covering how database choice and query optimizations can affect the performance when dealing with large datasets. In this, ORM will be discussed in detail. Component based approach with plain javascript : When one component of your website slows down the rendering of the whole page, what should one do? This is going to be another aspect that I'm going to touch upon - dividing page into pagelets without using any javascript framework. Let code speak of professionalism : Lastly, I'll be discussing about the good coding techniques and practices that should be used. (Like making dependency graph of modules for better modularity.) Hope you will find this talk interesting. :)", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic knowledge of Python, Django, Javascript and querying RDBMS is required", - "Section": "Web development", - "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia.\nOther than coding, I love reading, writing and trying out new things", - "Speaker Links": " Blog: https://medium.com/@meghasharma4910 Github: https://github.com/MeghaSharma21 Outreachy project: https://github.com/MeghaSharma21/WikiCV Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Megha Sharma (~megha480)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/optimizations-in-web-development-journey-from-a-college-project-to-a-product-using-django~dPp4d/", - "title": "Optimizations in Web Development: Journey from a college project to a product using Django" - }, - "6": { - "Content URLs": "Will be updated soon", - "Description": "In this talk, I will provide a concise understanding of Threading and Global Interpreter Lock(GIL) in Python. In the modern era of hybrid cores and processors, there is an in demand need for concurrent and parallel programming paradigms. Python, since its inception has amazing support for single threaded applications. The extensive use of Python in booming fields like Machine Learning has paved the way to constantly improve multi-threaded applications in Python. I will speak from ground level covering very crucial aspects of Threading and Locks which will pave the way for community to develop better Python applications. Program outcomes: How threading can improve performance, its pros and cons. What works best in which environment between threads and processes. Why GIL matters the most in Python How to leverage the power of open source source code to understand the crux of language. Contents to be covered: 1. Threading for noobs: Terminologies: Process, threads, multithreading, multiprocessing, types of threads, locks, mutex, CPU and I/O bound processes. Multithreading in Python: Threading module (with example) Comparative analysis of Sequential vs Multithreaded execution in Python (with example) 2. Understanding the global interpreter lock (GIL): What and why of GIL Impact of GIL on CPU and I/O Bound Processes In-depth understanding of GIL using cpython interpreter source code Reference counting Ticks via context switching 3. Infamous concepts: Cooperative vs Preemptive multitasking Parallelism vs Concurrency Thread Safety in Python 4. Removing the GIL: Famous GIL removal patch Guido on GIL, Larry Hastings Gilectomy 5. Questions Agenda: 0 - 6 minutes : section 1, Threading for noobs 6 - 15 minutes : section 2, Understanding GIL 15 - 25 minutes : section 3, Infamous concepts 25 - 28 minutes : section 4, Removing the GIL 28 - 30 minutes : section 5, Questions ", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basics of Python: Class, objects, list, libraries", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself from scratch. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-multithreading-by-deciphering-the-cpython-interpreter-source-code~aOora/", - "title": "Understanding multithreading by deciphering the cpython interpreter source code" - }, - "7": { - "Content URLs": "https://gautam-ankit.github.io/HomeAR", - "Description": "In this project, we are going to create a home finder in which we are going to give an individual marker/bar code to each and every home and going to create a web-app which will tell about the home on starring the camera on the marker/bar code. This idea will help out to find some place way better than the Google maps because one can generate its own marker for his/her home and can edit the details of there home, through which one can recognize the home. For management of this data we are going to use several concept of Big data also. But this is the best way possible to implement and link augmented reality with python", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "HTML and CSS and basic Javascript,\nbasic python ,\nsome programming concepts", - "Section": "Core python and Standard library", - "Speaker Info": "As a Microsoft student partner, I gave several presentations for Hour of code. And as a Mozilla campus club caption, I gave several presentations for Virtual reality and Augmented reality using Aframe web framework", - "Speaker Links": "https://www.linkedin.com/in/ankit-gautam-9b0524108", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Ankit Gautam (~Gautam-ankit)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/home-finder-using-python-and-augmented-reality~dNnvd/", - "title": "Home finder using Python and Augmented Reality" - }, - "8": { - "Content URLs": "So, Slides can be seen here: https://slides.com/tanayagrawal/efficient-hyperparameter-optimization#/ Full content is available here: https://github.com/tanayag/pycon_18_hyperopt You can also have a look at my article: https://blog.goodaudience.com/on-using-hyperopt-advanced-machine-learning-a2dde2ccece7 In the Repo iris.csv is the dataset that we'll work on. docker folder contains the scripts to setup Environment \"Introduction to Hyperopt.ipynb\" is iPython Notebook which contains the implementation which we'll work on during workshop and understand the concept \"link_to_slides.txt\" contains the link to our presentation", - "Description": "Hands on Experience with Advanced Hyper-parameter Optimization Techniques, using Hyperopt We'll go step by step, starting with the Hyper-parameter optimization with SkLearn's Grid Search, we'll compare it with the more effective Hyper-Parameter Optimization TPE Algorithm implemented in Hyperopt.\nWe'll also go through on how to parallelize the evaluations using MongoDB making the optimization even more effective. A Docker Image will be provided, so that participants won't have to waste time in setting up the environment. The Workflow of the Workshop would be: We will start with a slide presentation so that participants get some insight on what they are going to do. After that we'll shift on to a Juypter Notebook(pre-installed in the docker environment, so you can just focus on the implementation part), here they will implement the code, and see the best algorithms of hyperparameter optimization working. After that we'll show a working demo of a problem that we were working on and solved using Hyperopt during our Summer Intern at MateLabs. After attending this workshop you will be able to apply Hyper-parameter optimization using better algorithms which decides the hyper-parameters based on information. In short much much efficient model training", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic Python Coding and a little familiarity with Machine Learning/Data Science", - "Section": "Data science", - "Speaker Info": "Tanay Agrawal Working on Machine Learning/Deep Learning and also an Open Source Enthusiast. Currently in Final Year of his Engineering. He is working as Deep Learning Intern at Matelabs. He along with team at MateLabs is creating Meta Algorithms, so that user even with minimum or no knowledge of Machine Learning would be able to use it. Also he is a contributor at SymPy. He has previously worked on state of the art Classification and Object detection Models as well. He has previously conducted Python workshop at SFD-SMVDU and also he conduct the session of AI Circle at his College regularly. Anubhav Kesari Currently at fInal year of engineering from IIIT Guwahati. Two worked on the same problem and solved it using Hyperopt. Anubhav is the summer intern at MateLabs as well. He has worked at Cadence Design Systems in summer of 2017 as Software Development Intern. He has also been working on development of blockchain based distributed neural networks at MateLab", - "Speaker Links": "Tanay Agrawal https://github.com/tanayag https://angel.co/tanay_agrawal Anubhav Kesari https://github.com/kesarianubhav https://www.linkedin.com/in/anubhav-kesari-588a03131", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "tanay_agrawal", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-ml-learn-how-to-improve-accuracy-by-optimizing-hyper-parameters-using-hyperopt~aMmGa/", - "title": "Advanced ML: Learn how to Improve Accuracy by optimizing Hyper-Parameters using Hyperopt" - }, - "9": { - "Content URLs": "Will be uploaded soon", - "Description": "Python - Turing Complete and easy at the same time. Given its simplicity, one may be tempted to use it to solve a problem of any magnitude. But as the codebase scales, so does the difficulty in managing it. And as the applicability scales up, so does the difficulty in maintaining performance. In this workshop, we will walk through how these problems crop up in the first place, and how to tackle them. This workshop will NOT cover scalability from the perspective of distributing data loading and computation across multiple compute units (horizontal scalability). We will focus more on how to write code from the very start that is both efficient in performance and makes a larger codebase manageable. The topics we will go through are: 1.Performance - How should one write \"fast\" code Finding the bottleneck - Profiling Compiling Python to C - JIT vs AOT / Cython vs Numba vs Pythran vs PyPy - How they differ and choosing which one is for you Concurrency - To parallelize or not to parallelize, to sync or not to sync Choosing the right data structures Hacks and bits that can get us the extra performance 2.Design Principles - How should one write \"good\" code, because we have all written code that we have difficulty in understanding ourselves in no time Logging - Keeping track of what happened when and where Type Checking - The why and the how Unit Tests and beyond", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Cython, numba, and pythran installed. All of them are available on pip/conda Working knowledge of Python", - "Section": "Others", - "Speaker Info": "I am a final year student at IIT Madras. I currently lead the CV and AI team at Detect Technologies and have headed the CVI group at CFI, IIT Madras in the past. I love learning new things about how and why things work, and love sharing that knowledge", - "Speaker Links": " Personal Website Github Linkedin StackOverflow", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-not-break-your-head-or-computer-writing-python-at-scale~dLlrd/", - "title": "How to not break your head (or computer) writing python at scale" - }, - "10": { - "Content URLs": "https://en.wikipedia.org/wiki/Decentralized_autonomous_organization\nhttps://blockchaindevs.github.io/MeetupDA", - "Description": "Open Source Communities and their management. How things work currently A case study of different open source organizations: Advantages and disadvantages of current systems. The issues with Open Source organizations are nothing new, what are the possible solutions available? DAO and automation of majority of the tasks of a \"Open by default organizations\" What part of the organization can be automated, what can't. Important Aspects that usually breed trust among members::\n - Transparency\n - Consistency & Automation\n - Inclusion & support Our Proposal We will be posting codebase and complete websites and mobile apps that offer these solutions: Automated and transparent membership procedure. Transparent Public Elections on Blockchain for a board with automated publication of votes and results. Automate votes based on proposals Automated Procedure to apply for grants: with voting members and results being put up on Blockchain Automated meetings with MOM being recorded and put up on blockchain. Testing Proposal from the ground up: Start Small and test if these methods work locally in meetup groups \n- Automation of Tasks around meetups:\n...\nWe will keep updating here as and when we have deployed solutions on blockchain Tools used for these automation: Blockchain Dapps using : Solidity & Vyper\nPython: Kivy Framework for mobile apps and Web3.js & other such frameworks. Repos:\n They will be made online shortly, currently the experimentation is going on the following repos: https://blockchaindevs.github.io/MeetupDAO please excuse for the alpha quality of the software as they are just experiments as of now. This is a open source initiative based on the needs we feel we have seen arise in open source communities around us. Ultimate Goal Use this proposal as a catalyst and create small Organizations in local communities testing this theory. If things work in local communities, create a National Level Organization for managing the tasks around PyCon India This is just one of the hopefully multiple proposed solutions for moving on post PSSI", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "A willing ness to contribute, ability to learn. \nOpen Mind to experiment even if it leads to failure", - "Section": "Developer tools and Automation", - "Speaker Info": "http://github.com/akshaurora Akkshay is huge open source enthusiast, he has helped bootstrap different communities around Kivy, PyDelhi, ILUGD, BlockchainDevs , HyperLedger Delhi/NCR & chaired conferences like PyDelhiConf, Pycon-India, Global Blockchain Conference. He has been involved and working on blockchain based projects from 2011 onwards, he is one of the core developers of Kivy python framework & Electrum bitcoin wallet that has been built on top of it", - "Speaker Links": "http://github.com/akshauror", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Akshay Arora (~akshayaurora)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-open-source-communities-on-blockchain-a-transparent-way-to-manage-organizations~aKkxa/", - "title": "Automating Open Source communities on Blockchain: A transparent way to manage Organizations" - }, - "11": { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research \nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "We survey progress in recent years toward developing a theory of deep learning. Works have started addressing issues such as: (a) the effect of architecture choices on the optimization landscape, training speed, and expressiveness (b) quantifying the true \"capacity\" of the net, as a step towards understanding why nets with hugely more parameters than training examples nevertheless do not overfit (c) understanding inherent power and limitations of deep generative models, especially (various flavors of) generative adversarial nets (GANs) (d) understanding properties of simple RNN-style language models and some of their solutions (word embeddings and sentence embeddings", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", - "Section": "Others", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban http://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban \nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Parthi", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/toward-theoretical-understanding-of-deep-learning~dJjgd/", - "title": "Toward Theoretical Understanding of Deep Learning" - }, - "12": { - "Content URLs": "http://www.calmdownkarm.com/2018/clustering (Blog Post)\nhttps://github.com/CalmDownKarm/360classificatio", - "Description": "Quick walkthrough of how word2vec combined with more traditional clustering mechanisms can be used for topic modelling and document classificatio", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Some familiarity with clustering (Kmeans) is helpful, but not required", - "Section": "Data science", - "Speaker Info": "Recently graduated from BML Munjal University, Developer at Gramener", - "Speaker Links": "calmdownkarm.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Karmanya Aggarwal (~CalmDownKarm)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/document-clustering-with-word2vec-and-hierarchial-clusters~dG7Jd/", - "title": "Document Clustering with Word2vec and Hierarchial Clusters" - }, - "13": { - "Content URLs": "TB", - "Description": "\"Data is the new Oil!\" But, what is the benefit of this oil if you cannot refine (analyse) and sell/use (derive value) it. Big Data has pushed the frontier of analytical processing to gather more actionable insights in the past decade from having separate analytical servers to performing analytics close to the Data Lake/Cloud. A new paradigm of FOG computing has recently emerged which enables analyzing data at the Edge (close to the data capture device). This talk will focus on Edge Analytics enabled by Python & Raspberry Pi. Why attend this session? This session will provide a first hand look into the paradigm of FOG computing and Edge analytics. Model deployment is a critical part of the analytics life-cycle and this talk will provide insights and best practices to ensure seamless and robust model deployment. Also, the audience will get a flavor of python in embedded devices through the live and interactive demonstration using Raspberry Pi. Content The talk will cover the following sections: Evolution of analytics (Dedicated Machines -> Cloud -> Edge) The need of Edge analytics Analytics Life-cycle (ALC): Introduction, Importance of Model Deployment, Adapting ALC for Edge Analytics Model Exchange Formats (PFA, ONNX) for Deployment: Introduction & Need for Democratizing model development process Edge Device Introduction - Raspberry Pi Introduction to Portable Format for Analytics (PFA) Model Deployment on Edge Device (Raspberry Pi) using open source PFA engine implemented in Python Hands-on Application Use Cases - Deployment of Clustering, Regression, Decision Tree, Neural Network/ Deep Learning Models", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Python 2.7.x titus python package (pip install titus)", - "Section": "Embedded python", - "Speaker Info": "A die hard Pythonista, Ankit is a full time open source contributor and a former Google Summer of Code 2013 scholar under Python Software Foundation. Currently, he is developing the open source Portable Format for Analytics (PFA) implementation - Titus on Python 3. Ankit has 4 years of industrial experience in machine learning, quantitative modelling, data analytics and visualization. Over the years, he has developed an expertise in handling the entire data analytics pipeline comprising \u2013 ingestion, exploration, transformation, modeling and deployment. He is a polyglot programmer with an extensive knowledge of algorithms, statistics and parallel programming. He has shipped multiple releases of DB Lytix, a comprehensive library of over 800 mathematical and statistical functions used widely in data mining, machine learning and analytics applications, including \u201cbig data analytics\u201d. An IIT Kanpur alumnus, Ankit is also an active researcher with publications in international journal and conferences. He is actively working in the domain of IoT Analytics and has recently presented his work: \"Discovering Knowledge from Smart Meter Data using Competitive Learning Methods\" in the Data Science Congress 2018. \u201cIn-database Analytics in the Age of Smart Meters\u201d in the 5th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, 2017. \u201cSmart Meter Data Analytics using Orange\u201d in Scipy India 2017, Mumbai. Ankit is an active contributor to the Indian Python Community and has conducted the following workshops in PyCon India and Scipy India: Scientific Computing using Orange in SciPy India 2017, Mumbai. Making Machine Learning Fruitful and Fun using Orange in PyCon India 2017, New Delhi.", - "Speaker Links": "LinkedIn Youtube channel Githu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ankit Mahato (~ankit60)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fog-analytics-using-raspberry-pi-and-python~eE7gb/", - "title": "Fog Analytics using Raspberry Pi and Python" - }, - "14": { - "Content URLs": "Open weather map https://openweathermap.org/ Twitter API https://developer.twitter.com/en/docs.htm", - "Description": "This talk focuses on demonstrating the power of Python's Statistical and Data Science Libraries. I have been working on a project to classify average human sentiments as positive or negative. Classification is completely based on the prediction made by the ML models, which incorporates the weather of the location. I will try to prove that weather is \"one of the factor\" contributing to the moods/emotions of humans and ultimately affects the decision making ability. I have achieved the accuracy of 60%, which is good enough, with the existing and publically available data. The accuracy will certainly grow along with the data", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basic knowledge of Python Basic understanding of Statistics", - "Section": "Data science", - "Speaker Info": "I am a Python enthusiast, always a keen explorer of the power of python. I have been passionate about Python since my early college days, and then I went on developing many Web Apps, APIs based on Django and Flask, later on, my journey with Python turned towards exploring the magic of Data Science. It has been quite an interesting time spent exploring this field, and I must say that the depth cannot be determined. The more you experience, the more moments of awe occur", - "Speaker Links": " https://omkar-dsd.github.io/ https://towardsdatascience.com/a-simple-word-sense-disambiguation-application-3ca645c56357 https://medium.com/@omkar_dsd/when-killing-humans-becomes-the-right-choice-e3964419e78c https://stackoverflow.com/users/5130528/omkar-deshpande https://www.github.com/omkar-dsd", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Omkar Deshpande (~omkar08)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/analyzing-the-impact-of-weather-on-human-sentiments~bD7Ka/", - "title": "Analyzing the impact of weather on human sentiments" - }, - "15": { - "Content URLs": "TB", - "Description": "This tutorial is meant to familiarize participants with Tensorflow, generally as a tensor library and particularly as a tool for doing day-to-day machine learning tasks. The ultimate goal of the tutorial is to be able to make participants comfortable enough with it so that they can use tensorflow as a scalable substitute for other ML libraries like sklearn. Why Learn Tensorflow? For the same reason that you should learn NumPy. Tensorflow is to Keras (and many other deep learning libraries) what NumPy is to sklearn (and many other machine learning libraries). It is the underlying data model of many deep learning applications. There are always nooks and crannies in any deep learning application that high level wrapper libraries cannot reach. The tutorial is aimed at making these accessible and debuggable with tensorflow. What will I learn? The focus of the tutorial would be on loss functions - ensuring their fundamental correctness with respect to the machine learning problem at hand, ensuring their differentiability and convergence are critical to solving a deep learning problem. There are many ready-made loss functions in tensorflow, and using these as building blocks, we will see how to make arbitrarily complex loss functions. FAQs: Q. Will I need a GPU? A. No. The beauty of tensorflow is that it can seamlessly deploy code to GPUs, without you needing a GPU to develop that code. Q. What is the format of the tutorial? A. Being a tutorial, this session is meant to be highly interactive in nature. It will be a sequence of units where concepts are first explained and then the audience will have to solve exercises in a Jupyter notebook. Q. I don't know anything about neural networks or deep learning. Should I attend this tutorial? A. Absolutely. The focus is on tensors, which are the domain of tensorflow, and not on network layers, which are domain of keras", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic knowledge of Python data structures and NumPy arrays Basic knowledge of linear algebra Elementary vector calculus", - "Section": "Data science", - "Speaker Info": "Jaidev is a data scientist based in New Delhi, India. He specializes in building data-driven products and the tooling around them for a living. His research interests are in signal processing and computational harmonic analysis. He is obsessed with applications of machine learning in personal productivity and recommendation systems. He blogs about these here ", - "Speaker Links": "Twitter GitHub Blo", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Jaidev Deshpande (~jaidev)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tensorflow-101~dB7Ye/", - "title": "Tensorflow 101" - }, - "16": { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research\nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "The Python ecosystem is growing and may become the dominant platform for machine learning. The primary rationale for adopting Python for machine learning is because it is a general purpose programming language that we can use both for R&D and in production. In this talk I will discuss 1. Python and its rising use for machine learning, 2. SciPy and the functionality it provides with NumPy, Matplotlib and Pandas.\n3. scikit-learn for machine learning algorithms, TensorFlow and Keras for Deep learning and PyTorch for Natural Language Processing, 4. How to setup your Python ecosystem for machine learning and what versions to use. At the end I will also give case studies on using this Python ecosystem for biomedical applications", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", - "Section": "Data science", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban\nhttp://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban\nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Parthi", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mastering-machine-learning-with-python~azNya/", - "title": "Mastering Machine Learning with Python" - }, - "17": { - "Content URLs": "Will be updated soo", - "Description": "The ELK stack consists of Elasticsearch, Logstash, and Kibana. Although they've all been built to work exceptionally well together, each one is a separate project that is driven by the open-source vendor Elastic\u2014which itself began as an enterprise search platform vendor. It has now become a full-service analytics software company, mainly because of the success of the ELK stack. The session will cover basics of ELK stack for a kickstart", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Passion to Lear", - "Section": "Others", - "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International University", - "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chhavnish Mittal (~chhavnish)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-wih-elk-stack~axNBd/", - "title": "Getting Started wih ELK Stack" - }, - "18": { - "Content URLs": "will update soo", - "Description": "Get to Know Tkinter , pyqt5 and pyqtgraph and how to create a data visualization and control interface for your geeky arduino project in no time. Tkinter is a is the standard Python interface to the Tk GUI toolkit pyqt5 is Python bindings for the Qt cross platform UI and application toolkit pyqtgraph is Scientific Graphics and GUI Library for Python I will show you how to send the commands to Arduino using Python GUI and how parse and create a real-time graphs from Arduino dat", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "You should know how to write mighty Hello World program in Python and Arduin", - "Section": "Embedded python", - "Speaker Info": "I'm just a Tinkerer. Been playing with Python , Arduino and Raspberry Pi from few year", - "Speaker Links": "Blog - My Tinkering with Arduino GitHub linkden simple dem", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Kunchala Anil (~anilkunchalaece)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-python-gui-for-arduino-project~dw88e/", - "title": "Building Python GUI for Arduino Project" - }, - "19": { - "Content URLs": "TB", - "Description": "The focus is more on teaching core concepts to programmers rather than using libraries. More than one neural network will be implemented. An Easy way to learn Machine Learning An interactive way to learn ML. With ML being a leading platform in the market, the workshop introduces to one of the most important fields of Machine Learning that is Deep Neural Networks. Only basic introduction to Mathematics required. Why Python? Python for Machine Learning Machine Learning What is Machine Learning? Why learn Machine Learning? Types of Machine Learning Regression and Classification Supervised and Unsupervised Neural Networks Deep Neural Networks Feed forward Neural Networks Convolutional Neural Networks CNN Recurrent Neural Networks Layers in Neural Networks Neuron Models Perceptron Sigmoid Neuron Binary Threshold Rectifier Stochastic Binary Cost Functions (A Loss or Objective function) Gradient Descent Gradient Boosting Backpropagation Stochastic Gradient Descent Implementing the classic MNIST dataset problem A Neural Network for handwritten digit recognition Classification using individual pixels Image Classification A simple implementation using deeper networks TensorFlow Expanding the Neural Network using Google's Library for Machine Learning Might change to Caffe - nVIDIA's library for Machine Learning Deep Learning A brief introduction to Deep Learning practices Auto Encoders Other areas of Deep Learning (A qualitative study) ", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "User Prerequisites Core Python - lists, dict, string including functions and classes NumPy, SciPy - not necessary but preferred Elementary Calculus - Differentiation and Integration (Understanding qualitatively is enough) Linear Algebra System Requirements 32/64-bit Windows/Linux architecture with at least 2GB RAM Python3 compiler with NumPy, SciPy and TensorFlow library PDF reader Other Requirements but not necessarily needed Anaconda3 (or support for ipynb files, Jupyter preferred) A graphic card", - "Section": "Core python and Standard library", - "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", - "Speaker Links": "GitHub Instagram Emai", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Aniket Chowdhury (~aniket43)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-advent-of-deep-neural-networks-neural-network-implementation-without-ml-libraries-and-extending-them-with-tensorflow~av75b/", - "title": "The Advent of Deep Neural Networks. Neural Network implementation without ML libraries and extending them with Tensorflow." - }, - "20": { - "Content URLs": "Session Content: Introduction to main units of Deep learning Feature engineering techniques for audio data DeepSpeech Architecture Live demo of DeepSpeech Project Common Voice initiative (why and its need) Community Support details Applications of speech recognition Key Takeaways: Unravel the mystery behind the AI which powers speech recognition for services such as Siri, Google Assistance etc Learn about various by which one can contribute to Project DeepSpeech & Common voice project Get introduced to major units of deep learning and state of art DL architectures powering speech to text applications Tags: AI, speech recognition, speech to text, machine learning, Python, tensorflow, deep learning, Voice search Projects links: DeepSpeech : https://github.com/mozilla/DeepSpeech https://arxiv.org/abs/1412.5567 Common voice: https://voice.mozilla.org/ https://voice.mozilla.org/en/data", - "Description": "Pitch: Our voices are no longer a mystery to speech recognition (SR) software, the technology powering these services has amazed the humanity with its ability to understand us. This talk aims to cover the intrinsic details of advanced state of art SR algorithms with live demos of Project DeepSpeech. A research says that \"50% of all searches will be voice searches by 2020\". World\u2019s technology giants have placed big bets with their investments in services providing voice search, personal digital assistant, IoT devices etc. Solving the problem of speech recognition is a herculean task, given the complexity involved with data like the human voice. The talk will cover a brief history of speech recognition algorithms, the challenges associated with building these systems and then explain how one can build advanced speech recognition system using the power of deep learning and for illustration, we will deep dive into Project DeepSpeech. Project DeepSpeech is an open source Speech-To-Text engine developed by Mozilla Research based on Baidu's Deep Speech research paper and implemented using Google's TensorFlow library. Speech recognition is not all about the technology, there's a lot more concerns, challenges around how these AI models are being part of our day to day life , it's biases etc. The bigger question revolves around centralization of these AI services, projects like Common Voice addresses these problems by enabling all to be part of this revolution, a part of the talk will focus on how people need to approach these type of research keeping in mind the community and humanitarian benefits as first priority", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic Python Feel enthusiastic about ML & AI services Interest to learn about speech recognition systems", - "Section": "Data science", - "Speaker Info": "Vigneshwer is an innovative machine learning researcher with an artistic perception of technology and business, having several years of experience in developing robust machine learning solutions for video and text analytical problem statements and have played key roles in analyzing problems, creating hypothesis matrix and delivering novel algorithms and data-driven solutions for many fortune 500 companies. An open Source aficionado, Official Mozilla TechSpeaker and the author of Rust cookbook", - "Speaker Links": "Github | Website | Facebook | Twitter | LinkedIn | Talk", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vigneshwer Dhinakaran (~dvigneshwer)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-speech-recognition-with-project-deepspeech~erNpe/", - "title": "Demystifying speech recognition with Project DeepSpeech" - }, - "21": { - "Content URLs": "https://github.com/vibrantabhi19/PyConIndia2018 (A Github Link to the slides and the Jupyter Notebooks) https://docs.google.com/presentation/d/1UmT3PbazC6sO_owIeiLNj5G1EdTwrdpS84JWenO-3eE/edit?usp=sharing (Introduction Slide for CNN and PyTorch) Some more slides and notebooks as and when we come up with more ideas to make the workshop interacting and interesting", - "Description": "Just like in our everyday lives, AI and robotics are increasingly a part of our healthcare ecosystem. Currently healthcare is broken; there\u2019s shortage of doctors; poor quality of care. There is a dire need to provide assistance to the whole medical industry to improve healthcare. PyTorch, which is a very popular modular deep learning framework for fast, flexible experimentation is an invaluable resource for such problems. It supports seamless conversion of Numpy arrays into GPU tensors and vice versa. The dynamic computational graph allows to change the network behavior on the fly unlike static graphs and due to Its highly modular nature helps in fast debugging. Unlike other production grade tools, Pytorch helps with lots of Research and Experimentation with novel architectures and is very useful to test ideas a bit more quickly and prototyping. With Medical Imaging being the field most impacted by AI, our goal in this workshop is to give a good head start covering the heuristics of Medical Imaging, the concepts involved in it and how to code your way out. This workshop would be divided into two halfs. First Half: Pytorch Introduction\nDuration: 1 hour 20 minutes\nThe first half would be a gentle introduction to PyTorch framework. We will introduce the audience with the basics of PyTorch. This workshop will cover topics like: What is PyTorch? (Use cases and war stories) Tensor 101 Ndarray/Tensor library Numpy Bridge, Fast CPU to GPU conversion of tensors The automatic differentiation engine or autograd Difference between Static and Dynamic computational graphs Advantages of dynamic computational graph with examples The optimization package Scope of debugging Ecosystem Linear Code flow in Pytorch (One of the core philosophy of PyTorch) Saving and loading models* Deep Learning workflows* Tutorial on Transfer Learning.* Workflows which involve writing custom data-loaders will also be introduced in brief.* A 10 minute coffee/kit-kat break. :-) Second Half: Let\u2019s dive in. Duration: 1 hour 15 minutes. Introduction to Radiology: What is radiology? What do the images look like? How is AI used here? How will AI help improve radiology practice? Liver, Tumor and Vessel Segmentation - setting the context of why it is needed. Challenges faced in solving liver segmentation. How we solved the challenges - edge maps, data imbalance and overall architecture and data used. Hands on with live Liver Segmentation using PyTorch. Challenges faced in vessel segmentation and classification. How we solved the challenges - vesselness filters, overall architecture and data used. Hands on with live Vessel Segmentation using PyTorch. Putting it all together A 15 minutes Q & A session", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Zeal to learn new things would be enough but basic knowledge of Python would be good to go but the following are always encouraged: Basic Knowledge of algebra. Python Libraries such as Numpy. Basic knowledge of working with Neural Network (not a strict requirement as we will be covering most of it). We also encourage the participants to have a look into the following linked talks/videos/literature to get a head start into the topic. The related materials from web for ideas: https://github.com/soumith/talks/blob/master/2017-NIPS/Coding-papers-in-pytorch.pdf https://github.com/soumith/talks/blob/master/2017-GATech-Atlanta/PyTorch-frameworks_overview_deepdive.pdf https://www.youtube.com/watch?v=LEkyvEZoDZg https://www.youtube.com/watch?v=VMcRWYEKmhw https://www.youtube.com/watch?v=Rv9naeLXolY&index=3&list=PLrzfRWNHZPa0gKBEXTJ0gbDu8NsR07KEH https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/01-basics/pytorch_basics/main.p", - "Section": "Data science", - "Speaker Info": "Abhishek Kumar: Deep Learning Engineer, Predible Health, Bangalore. I am presently working as Deep Learning Scientist at Predible Health, here, we have build state of the art segmentation network for liver, tumour and vessel segmentations. I have previously taken workshop at IIT-Bombay Techfest, I have spoken at Shri Mata Vaishno Devi University at their SFD celebrations and at MuPy (Manipal Institute of Technology's annual Python Conference), Kongu University and a few other colleges/Universities. I have been a constant contributor in the open source world and have been attending PyCon and other conferences every year. An athlete, a Real Madrid F.C follower and a part time stand-up comedian (good enough to make you laugh). Aditya Bagari: Final year Undergrad, Indian Institute of Technology, Madras I am a final year Undergraduate student at IIT-Madras doing my Dual-Degree in Engineering Design with specialisation in Bio Medical Sciences. I have been working on Medical Imaging and PyTorch for almost a year and I have been a constant admirer of Open Source Technologies and frameworks. Feel free to drop any suggestions or modifications that you want in this workshop. See you at PyCon", - "Speaker Links": "Abhishek Kumar: Website (A very outdated one), LinkedIn , Medium , Github . Aditya Bagari: LinkedI", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Abhishek Kumar (~vibrantabhi19)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploring-pytorch-for-ai-assistance-in-medical-imaging~bqXpa/", - "title": "Exploring PyTorch for AI assistance in Medical Imaging" - }, - "22": { - "Content URLs": "This talk will be based on my article on Towards Data Science The hands-on examples have also been open-sourced on GitHu", - "Description": "Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. We will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D) using a hands-on approach with Python and popular open-source visualization libraries like matplotlib and seaborn. The talk shall be structured as follows: Motivation for Effective Data Visualization A quick refresher on Data Visualization Brief introduction into python open-source frameworks for visualization pandas matplotlib seaborn bokeh Univariate analysis with hands-on examples Multivariate analysis with hands-on examples Visualizing data in 2, 3, 4, 5 and 6 dimensions Visualizing a combination of numeric and categorical data Strategies for effective data visualization Conclusion", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basics of Python, data terminology (rows, columns, feature, data points, data types) helps but we will be covering briefly during the session. Hence it's not essential", - "Section": "Data science", - "Speaker Info": "Dipanjan Sarkar is a Data Scientist at Intel, on a mission to make the world more connected and productive. He primarily works on data science, analytics, business intelligence, application development, and building large-scale intelligent systems. He holds a master of technology degree in Information Technology with specializations in Data Science and Software Engineering. He is also an avid supporter of self-learning. Dipanjan has been an analytics practitioner for several years now, specializing in machine learning, natural language processing, statistical methods and deep learning. Having a passion for data science and education, he is a Data Science Mentor at Springboard, helping people up-skill on areas like Data Science and Machine Learning. He also acts as a contributor and editor for Towards Data Science, a leading online journal focusing on Artificial Intelligence and Data Science. Dipanjan has also authored several books on R, Python, Machine Learning, Social Media Analytics, Natural Language Processing & Deep Learning. More about me: LinkedIn: https://www.linkedin.com/in/dipanzan/ GitHub: https://github.com/dipanjan", - "Speaker Links": "LinkedIn: https://www.linkedin.com/in/dipanzan/ Blog Posts: https://towardsdatascience.com/@dipanzan.sarkar GitHub: https://github.com/dipanjanS Featured stories on KDnuggets: https://www.kdnuggets.com/?s=dipanjan+sarkar Recent books:- https://www.springer.com/us/book/9781484223871 https://www.springer.com/us/book/9781484232064 https://www.packtpub.com/big-data-and-business-intelligence/hands-transfer-learning-pytho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Dipanjan Sarkar (~dipanjan)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-art-of-effective-visualization-of-multi-dimensional-data-a-hands-on-approach~ep6Vb/", - "title": "The art of effective visualization of multi-dimensional data - A hands-on approach" - }, - "23": { - "Content URLs": "Will be updated soon", - "Description": "We all(probably) love facial recognition feature isn't it?. We all edit our images before posting it to social media to give a flamboyant touch and its done in too simple steps. Open the editing software, select what you want to configure(filters, Sharpness, etc.) and you're done. Quite easy, right? But what if you know how the back-end of how these softwares run? what if you know the what kind of codes make your camera detect objects? Well with OpenCV and python its simpler than you can imagine! My talk will be about OpenCV with Python. OpenCV is an acronym for Open Source Computer Vision Library . Its a library used for image processing. The code can be written in C++, Java or Python but since we all love Python, we'll use that. We will be using ' cv2 ' library for all the image processing and detection. My talk will feature: How images are stored in computer and how each pixels store image. Different types of Colour Bands and the role of Colour Bands in forming an image. Editing images with cv2 library in python. Blurring, Sharpening, Greyscaling, and other uses of image kernels. Object and Face Detection and live object Tracking using python and OpenCV.", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basic knowledge of Python and basic mathematics(Class 10th)", - "Section": "Others", - "Speaker Info": "I am undergraduate final year student, CSE branch from REVA University. I am a passionate programmer. I am an IEEE Volunteer. I was the Chair of IEEE Computer Society Chapter REVA University. Right now i am Student Branch Coordinator at IEEE Region 10(Asia/Pacific).\nCurrently I am interning at Valtech India as a Java Developer.\nI have taught python to more than 150 students in my college by taking sessions. I have taught OpenCV to more than 80 students.\nI have started loving python from 2016 when I read the book 'learn python the hard way by Zed Shaw'. My almost all the undergraduate projects are based on python", - "Speaker Links": "Blog: bit.ly/itsrohanvj\nGithub: itsrohanvj\nLinkedin: www.linkedin.com/itsrohanv", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rohan Vijay (~rohan96)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/computer-vision-with-python~bo9Xe/", - "title": "Computer Vision with Python." - }, - "24": { - "Content URLs": "https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology I will update slides and code soo", - "Description": "Central dogma of life or of molecular biology is the core molecular process which keeps us alive! It's the machinery which converts DNA to mRNA to protein to active protein which eventually gets distributed in the body. DNA -> mRNA -> Protein Through this talk, I'll give a live demonstration of the processes by which this mechanism takes place and unravel its mysteries using Python! I'll explain how python is helping us simulating biological processes in the most elegant manner. How is DNA transcripted to mRNA? How is mRNA translated to protein? These are some of the questions I\u2019ll answer by simulating the actual processes using Python. By solving small challenges involved with this mechanism, I\u2019ll tell the audience, why Python is the best computer language for a bioinformatician and how great python libraries can make the life even easier especially BioPython. The challenges I am talking about are real bioinformatics problem, although basic, including translation, transcription and reverse complement. In the end, I\u2019ll brief some huge accomplishments of bioinformatics and computational biology and how we can contribute to this sector which has a promising future as well. Contents of the talk: Introduction : Introduction to gene and how we (computer scientists)\n recognize a gene Central Dogma of Life : a Live action of how a gene\n is converted to RNA and then to protein using Python. Why Python is best for biology? : Bioinformatics can be best studied using Python Impact of this sector : Accomplishments of Computational Biology and\n bioinformatics Conclusion : Possible ways in which we can contribute. Q & A session : Questions and answers session. Outcome: After the talk, the audience will have an understanding of how we function at a cellular level, how proteins are formed in our body and how can we simulate other biological processes using Python and will recognize the power of Python which can be harnessed in biology as well as other sciences. They will also have a basic introduction of BioPython", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Curiosity to learn :", - "Section": "Others", - "Speaker Info": "I have completed my B.Tech in Biotechnology this year from IIT Roorkee. I have interests in Web applications, Artificial Intelligence and Computational Biology. I have worked a couple of years in Computational Biology and Translational Bioinformatics Lab at my Institute and currently a Google Summer of Code student working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API ", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/simulating-central-dogma-of-life-using-python~enV7e/", - "title": "Simulating central dogma of life using Python" - }, - "25": { - "Content URLs": "Will be updated soon", - "Description": "Get to know Flask and how to create beautiful REST APIs in no time. Fall in love with Flask and learn the best practices for building APis in a hurry. Flask is a lightweight micro-framework for Python. Its simplicity and elasticity make it the best choice for building APIs in no time. In my talk, I will cover the basics concepts of Flask and Requests. I will show the tools that can automate the most common tasks in API development and will share the design patterns to avoid common pitfalls. Some of the specific tools and topics that I'll cover: Flask-Restplus, SQLAlchemy, request lifecycles, REST + CRUD API patterns, Flask architecture", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "No previous experience in Flask is needed", - "Section": "Web development", - "Speaker Info": "Sara is a seasoned software engineer and the Co-Founder of Gradient.gt, a data science and machine learning consulting company based in Guatemala, where she works crafting web applications and solutions to companies in need. When she is not coding, she spends her free time baking sweet treats and watching Rick and Morty", - "Speaker Links": "www.sara-codes.com Linkedin.com/in/sarairisgarcia Gradient G", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "montjoile", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-apis-in-no-time-using-flask~bmVGd/", - "title": "Designing APIs in no time using Flask" - }, - "26": { - "Description": "A framework which will give a drag and drop web development option using Django as the backend", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Python and basics of Djang", - "Section": "Web development", - "Speaker Info": "Sanket Sarkar [ Microsoft Technology Associate {Introduction to Python Programming}]\nA final Year Student of B.Tech", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Sanket Sarkar (~sanket78)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/drag-and-drop-framework-for-django~elVMb/", - "title": "Drag and Drop Framework for DJANGO" - }, - "27": { - "Content URLs": "Content will be updated soon", - "Description": "You all would have often faced the issue of not being able to recognize handwriting, either it is a Doctor's prescription or sometimes, even your friend's assignment. This problem might have caused some harm, maybe due to the delay in submitting the assignment or seeking chemists' that can recognize that particular handwriting.\nTherefore, in this talk, we will be focusing on how Python and Data Science can be used to recognize handwritten digits and character which will ease out the pain of recognizing haphazard writings. Topics to be covered: What is Handwritten Digit and Character Recognition? Why we need it and uses of it? How Python can help in achieving this? Future Scope", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " Basics of Python Basics of Data Science", - "Section": "Data science", - "Speaker Info": "I'm Prashant Pandey. I've deep interest in Data Science, especially in Python. I've been working in the domain of Data Science since one year now, and have completed several projects. Presently, I'm working on Handwritten Digit and Character Recognition", - "Speaker Links": "https://github.com/Prashantpandey2398", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Prashantpandey2398", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handwritten-digit-and-character-recognition-using-python~bkV6a/", - "title": "Handwritten Digit and Character Recognition using Python" - }, - "28": { - "Content URLs": "Will be updated soon", - "Description": "Your machine learning models might be intelligent enough to make predictions but may lack the wisdom to prevent bias. They may be as vulnerable as a child getting influenced by inappropriate sources encouraging racism, sexism or any unintended prejudice. Models learn exactly what they are taught. The more biased your data is, the more biased is your model. For instance, a text model by Google says how \u201cEngineer is to a Man\u201d is the same as \u201cHousewife to a Woman\u201d. This shows how incidental data can lead to unintended bias. Machines are given the power to judge so there is a need for us to ensure we prevent biased/unfair judgements. In this talk, we are going to discuss What is Machine Learning bias? How is it caused? Different ways to identify bias? Techniques to prevent bias One Famous example of bias:", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Knowledge in python3 and pandas Knowledge of building machine learning models Little idea on deep learnin", - "Section": "Others", - "Speaker Info": "I am a software developer, speaker, opensource contributor and a wannabe developer evangelist. I love everything python and NLP(Natural Language Processing) research. I have been volunteering with various local startup and tech communities to promote entrepreneurship and technology. I work at mroads and help them develop better a.i", - "Speaker Links": "Links: Linkedin: https://www.linkedin.com/in/poornagurram/ Github: https://github.com/poornagurram StackOverflow: https://stackoverflow.com/users/5443381/poorna-prudhv", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "G POORNA PRUDHVI (~poornagurram)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-fair-machine-learning-systems~egVkd/", - "title": "Building fair machine learning systems" - }, - "29": { - "Content URLs": "Will come soo", - "Description": "Blockchain Technology is the talk of the town. Almost all articles published have some relation to Blockchain concepts.\nWhile Public Networks usually pertain to Cryptocurrency, Private networks pertain to business-level implementations. In order to develop with this technology as our base, it is important to understand the key features, as well as make implementations using the existing skillset, which happens to be the Python Programming Language. The talk will feature Complete in-depth explanation of Blockchain technology, and the working of Bitcoin as an example. Developing your personal Cryptocurrency with Python Introduction to Hyperledger Sawtooth, and understanding how and why to use Python with it. Best practices to consider in mind while developing for a blockchain. By the end of the talk, you will be able to Explain the concepts of Cryptocurrency and Blockchain technically. Understand Python's role in one of the most popular frameworks created by Intel, and implement your own ideas with the same.", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "General Pytho", - "Section": "Others", - "Speaker Info": "Hi, I'm Priyansh! Here's a quick bio. CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms. Technical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-with-python~e0yLa/", - "title": "Blockchain with Python!" - }, - "30": { - "Content URLs": "Will be updated soo", - "Description": "Automation is something we all desire, may it be the twitter feed of a celebrity, or perhaps the latest price of bitcoin. For students, it can range from tracking assignment deadlines or message updates. For developers, it can be the tracking of an important issue or auto merging of pull requests. For management, deadlines for a work assignment or a due presentation. With Python, everything listed above is possible. The talk will feature how to start automating the small things that can prove highly productive. We will use simple libraries first, and this will be followed by using fully headless browsers like selenium and understanding the concepts of web crawling. Integration of API services like Google Calendar and Google keep, to sync all the data collected will be demonstrated. Finally, we will deep dive into an interesting open-source project I made, and how I have automated most of my college work", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic understanding of REST APIs and Frameworks, and Beginner-Intermediate Level of Python Programmin", - "Section": "Developer tools and Automation", - "Speaker Info": "CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms.\nTechnical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-your-life-with-python~b873a/", - "title": "Automating your life with Python" - }, - "31": { - "Content URLs": "Will be updated soon", - "Description": "Dash is a Python framework for building analytical web applications, built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs to your analytical Python code. The workshop will include building interactive dashboard with Dash framework. How to visualise the data purely in python will be the key take away", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Python 3 Pip3", - "Section": "Web development", - "Speaker Info": "I am software engineer working at Juxt Smartmandate, who believes in creating products using open source technology", - "Speaker Links": "https://github.com/kapoorabhish https://www.linkedin.com/in/abhishek-kapoor-4b7b9295", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "kapoorabhish", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-interactive-dashboard-using-plotly-dash~e771e/", - "title": "Building interactive dashboard using Plotly Dash." - }, - "32": { - "Content URLs": "A sample code can be found here :\nhttps://github.com/KaustabhGanguly/Recurrent-Neural-Networks-to-predict-Google-Stock-Pric", - "Description": "I will show you how to predict google stock price with the help of Deep Learning and Data Science .\nThe predictions are not realistic as stock prices are very stochastic in nature and it's not possible till now to accurately predict it .\nAs I'll only have 30 mins to talk , I can't train the data and show you as it'll take several hours for the model to train on google collab . So , I will show you : Basics of Recurrent Neural Networks and LSTM Basics of pytorch Coding line by line with describing every words Then starting to train the model and prematurely closing it and move forward to show you the results that I'll bring with me after training .", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "You should have basic pyTorch understanding but I'll guide you anyways through the basics .\nBasic understanding of LSTM or RNN is preferred but not required ", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India . I'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 . I'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github : github.com/kaustabhganguly Connect with me on linkedin : linkedin.com/in/kaustab", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-stock-price-time-series-prediction-with-rnnlstm-using-pytorch-from-scratch~b67Rd/", - "title": "Google Stock Price Time Series Prediction with RNN(LSTM) using pytorch from Scratch" - }, - "33": { - "Content URLs": "The code is in this repo :\nhttps://github.com/KaustabhGanguly/Smile-Detector :", - "Description": "In this era of deep learning and machine learning , the beginners may get lost sometimes , as there is a steep learning curve involved with the process .\nWhen I was starting out on machine learning , I always wanted to get my hands dirty in the advanced stuffs but It was hard for me and there was no guidance .\nSo , in this talk and coding session I will guide you through how you can build your own facial recognition system and implement a smile detection very quickly and easily with the power of openCV and python . It will take 10 mins and any beginner with basic knowledge of python can grasp the concepts easily .\nI will not use convNet or anything ,but a model called HaarCascades . It's an old mathematical model which was/is mainly used where deep learning is not an option . I will guide you through the basics and tell you some quick things and facts and we will enjoy a lot . See you on pyCon 2018 ! kindly upvote if you want some quality 10 mins learning something new ", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic Python knowledg", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India .\nI'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 .\nI'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github :\ngithub.com/kaustabhganguly\nConnect with me on linkedin :\nlinkedin.com/in/kaustab", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quick-and-easy-implementation-of-smile-detector-on-your-webcam-using-python-and-opencv-from-scratch-without-any-neural-network-and-for-beginners~e5E8e/", - "title": "Quick and easy implementation of Smile Detector on your Webcam using python and openCV from Scratch without any Neural Network and for beginners ." - }, - "34": { - "Content URLs": " Apache Beam : https://beam.apache.org/ Apache Beam Python SDK : https://beam.apache.org/documentation/sdks/pydoc/2.4.0", - "Description": "Data together with 3Vs characteristic, volume, variety and velocity is labelled as Big Data. Big Data and parallel processing have been hot topics since Google\u2019s paper on MapReduce and till today the era of different runners like Apache Spark, Google Cloud Dataflow etc. Apache Beam is a unified big data processing paradigm which enables the user to run batch and streaming data processing jobs on multiple execution engines like Apache Spark, Apache Flink, Google Cloud Dataflow etc. *Objective of the talk* : Overview of Apache Beam Python SDK Core SDK constructs like Pipeline , PTransform , PCollection etc. Creating custom DoFns and composite Transforms Creating a Pipeline with customizable options Running a pipeline on different runners like DirectRunner , DataflowRunner etc Unit testing a Pipeline with asserts Demo: StreamingWordCount example using Google Cloud Dataflow Q&A", - "Last Updated": "22 Jun, 2018", - "Prerequisites": " A little knowledge about Python 2.7 Enthusiasm for Parallel Data Processing Motivation to play with lots of Data", - "Section": "Others", - "Speaker Info": "I am Mukul Arora, working as a Software Engineer in Schlumberger India Technology Centre. I graduated from Delhi Technology University in May 2017. I am a Data Science and Big Data practitioner and have been highly involved in solving Computer Vision and Medical Imaging problems using Deep Learning Techniques. Currently, I am exploring efficient ways to solve Big Data problems on Cloud.\nI am an avid cricket fan and love to write poems", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/mukularoradce/ Github : https://github.com/codemukul95 YourQuote : https://www.yourquote.in/mukul-arora-ffds/quotes", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "mukul arora (~mukul11)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unified-and-portable-parallel-data-processing-using-apache-beam~b4Dxb/", - "title": "Unified and Portable Parallel Data Processing using Apache Beam" - }, - "35": { - "Content URLs": "A similar version of this talk was recently delivered at Pycon APAC2018 (Singapore). Slide deck: https://goo.gl/xRRdKt An attendee's review of my talk: https://tryolabs.com/blog/pycon-apac-2018-singapore-experience", - "Description": "Offensive / abusive content is a major issue for social-media and digital interaction platforms. In some jurisdictions (Eg: Europe), platform providers are required by law to remove such content within 24 hours of posting or risk hefty fines (upto \u20ac50M in Germany). In order to meet the governance mandate, we need to have systems in place that can automatically detect abusive content at scale. This talk is based on my practical experience of building an automated solution to solve this problem. This talk begins with discussing some of the approaches currently being employed for offensive content detection at scale: word filtering, rule-based systems and actual human annotation. The former two are restricted by the following: Offensive content is context specific. A given word (f ck) can be used in both positive (that\u2019s f cking awesome) and negative (that\u2019s f*cking terrible) contexts. Robustness to spelling variations (The word \u2018shit\u2019 can be spelt as \u2018sh*t\u2019, \u2018sh!t\u2019, etc) Failure to detect content that is offensive in idea but uses non-offensive words. (Eg: your mom is a fat cow, X people are inferior, etc) Manual human annotation is notoriously hard (ask Google!) and expensive to scale. The talk presents a Deep neural network based approach to overcome the previously mentioned limitations. It introduces and discusses the building blocks of model architecture (deep convolutional networks, word embeddings, etc). The second half of the talk focuses on implementing the above model to solve the problem at scale as a RESTful micro-service using python, Django, Tensorflow and Docker. This architecture can also be used to implement other text classification systems as well (eg: user intent detection systems, topic-of-discussion classifiers, etc.), making the talk relevant for a wider user base. Attendees will: Gain insights into building deep learning based text-classification systems that can scale Learn the nitty gritties of the offensive content detection and text classification Learn about the basic concepts of Deep Learning and NLP (convolutional neural nets, multi-layer perceptron, word embeddings, etc.) Understand the scientific and software challenges involved in text classification and learn to overcome them Be able to apply the learnings from here to other text classification problems as well", - "Last Updated": "22 Jun, 2018", - "Prerequisites": "Just bring an open mind ;", - "Section": "Data science", - "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. He is currently employed as a Machine Learning Engineer. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", - "Speaker Links": "https://www.linkedin.com/in/alizishaan-khatri-32a2063", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Alizishaan Khatri (~alizishaan)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/detecting-offensive-messages-using-deep-learning-a-micro-service-based-approach~e30Ra/", - "title": "Detecting offensive messages using Deep Learning: A micro-service based approach" - }, - "36": { - "Content URLs": "Git Hub Repository : click here Demo: click her", - "Description": "The workshop will be escalating from a very beginner level and so I only require you to know the basics of python and if possible a glance of the OpenCV library. The workshop will be proceeding accordingly : Basics of Image processing. Image classification using Deep Learning ( CNN ). Deploying your own Emotion recognizer. ", - "Last Updated": "21 Jun, 2018", - "Prerequisites": " Basics of Python Please download and install the following libraries in beforehand : Pytorch OpenCV Fastai numpy matplotlib dlib imutilis We will be using all of the mentioned libraries to make the goings of the workshop easy to understand and implement. Additional Files : Please download from her", - "Section": "Data science", - "Speaker Info": "I am shaaran and my main aim is to take technology to everyone and spread my knowledge as far as I can, in a journey to fulfill my dreams I have went to many institutions and have conducted workshops and talks in Robotics and AI, I am currently a second-year student at VIT University and also a part of many organizations like Google Developers Group, RoboVITics and more , I have interned at Toshiba recently and have made a new AHU control system using IOT and AI", - "Speaker Links": "Github: click here Linkedin: click her", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "shaaran Lakshminarayanan (~devshaaran)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-your-own-emotion-recognizer-from-scratch~b2rzb/", - "title": "Building your own Emotion recognizer from Scratch !" - }, - "37": { - "Content URLs": "https://github.com/someshchaturvedi/customizable-django-profiler Will be updating slides soon", - "Description": "Django, as we all know, is an excellent framework for building high stable, scalable, extensible web apps. Django framework operates around middlewares. Do we really understand how a middleware works? What happens when the request comes in and response goes out? Which middleware is used for what purposes? Why is the order of middleware stack important? How can we implement a custom middleware? Benefits and complications of implementing custom middlewares My talk will cover all the above questions along with a live demo of a profiling middleware ( customizable-django-profiler ) which is used to track down the function calls associated with an API call taking more time for execution. Contents of the talk: Introduction : Introduction to middleware. Middleware architecture : I will talk about the middleware architectural design. It\u2019s basics and various use cases Implementation of middleware in Django : Explain how the request-response cycle works along with targeting above mentioned questions on the go. Live demo : I will demo the development of a simple custom middleware which can be used for profiling requests. Conclusion : Possible use cases for Django middlewares. Q & A session : Questions and answers session. In the end, the audience will have an understanding of Django middleware stack, middleware architecture, request-response cycle in Django and will be able to develop their own middleware for Django from scratch", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics of Python and Djang", - "Section": "Web development", - "Speaker Info": "I am recently graduated from IIT Roorkee. I have been working on web applications (especially Django for more than 3 years now). Selected for Google Summer of Code this year and working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API . My areas of interest are Web Applications, Artificial Intelligence and Computational Biology", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-django-middleware-stack-with-a-live-demo~e1qme/", - "title": "Understanding Django middleware stack with a live demo" - }, - "38": { - "Description": "Data proliferation is putting pressures on business leaders to become data-driven. Although, leaders have to rely on data analysts to run those queries and get insights out from data warehouses. Its a common principle-agent problem wherein data analysts only ask questions from data which they are directed to ask, but its never a one-way street. One has to flirt with data for a long time to get to know it and leaders get stuck in the loop of data analyst direction as leaders are not equipped with or don't have time to write SQL queries. This calls for a natural language query wherein a business leader can ask a question in simple plain English and data is spitting out either in a table or graph. This session is guided towards how Innovaccer has solved this problem and provides an architecture, knowledge base building, and natural language processing guidance to build one on your own. The session will also emphasize on the fact that accuracy of such a software will be very poor if it is industry agnostic as SalesForce and ThoughtSpot have tried in the past. Thus, one has to tame it to their own business context or vertical", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics knowledge on natural language processing, not even how to code it, but what are its basic components. https://www.nltk.org", - "Section": "Data science", - "Speaker Info": "Kanav Hasija is Co-Founder and Chief Product Officer at Innovaccer. He has developed a healthcare data platform with his team which helps connect to various healthcare IT systems to get a longitudinal view of the patient record and turn it into analytical insights on risk, cost, and utilization behaviour of patient to act on them and treat them before they get sick to reduce the cost of healthcare. The platform today has more than 10 million lives on the platform and an estimated $1 Billion has been saved till date in US healthcare costs while keeping people healthy with a quality of care bump of 15%. He is a coder and mathematics enthusiast since the age of 10, completed his bachelor in engineering from IIT Kharagpur and pursued higher studies in Intellectual Property Law from UNH Law in the US. He is recipient of various awards like Samsung-Stanford Patent Prize, Honorable Mention for Excellence in Technology, Best Graduate Student Award, and is also an author in a few publications like IEEE. Harshil Rastogi is a software development engineer at Innovaccer. He has worked on various enterprise-grade software components in the fields of data management, data transformation, and natural language processing", - "Speaker Links": "https://www.linkedin.com/in/kanavhasija/ https://www.linkedin.com/in/harshil-rastogi-3a754b65", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kanav Hasija (~kanav)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bringing-analytics-in-hands-of-leaders-natural-language-query-in-python~bYx2a/", - "title": "Bringing analytics in hands of leaders: Natural Language Query in Python" - }, - "39": { - "Content URLs": "Speaker will focus on when and how to use design patterns, rather than what are the design patterns available. Github repository for the talk", - "Description": "Having less time to design software and solving the design problems correctly, to create robust , modular and highly maintainable code is current challenge.\nMight be, you are aware of some of the design patterns but it will never solve your problems until you have deep understanding on the problem and right place to use design pattern. If you think, you need to design a very unique architecture, then may be you are missing powerful available design pattern that can provide you generic solution template. Let's learn ( and become expert), to speed up development process; guessing issues that can come up later development stages and selecting the right design pattern in the right stage of the software development in Python", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Coders and programmers who want to learn about software design and architecture", - "Section": "Others", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/i-would-have-known-this-software-design-techniques-before~eXwgd/", - "title": "I would have known, this software design techniques before.." - }, - "40": { - "Description": "for students,\nunderstanding data analysis with pandas, using ipython shell or terminal and jupyter notebooks", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "understanding of python scripts", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year B.tech(information science) student from Bangalore, Karnataka", - "Speaker Links": "https://github.com/pandyamaru", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marut Pandya (~pandyamarut)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-with-pandas~bWvxa/", - "title": "Data analysis with Pandas" - }, - "41": { - "Content URLs": "Will be updated soon", - "Description": "Talk Summary :- Recently, there is a boom in concept of face recognition system with the introduction of Face ID by Apple in their iPhone X mobile phones. This was also incorporated by OnePlus for their mobile phones too. The most notable use of this technology is at Baidu, an internet company, are using face recognition instead of ID cards to allow their employees to enter their offices. Another place where this technology is prominently seen is in auto photo and video tagging feature of Facebook. In this talk we will build a Facial Recognition program using python library \u201cface_recognition\u201d and then we will dive deep in the behind the scenes action of this library and will try to build a One Shot Learning face recognition model using PyTorch. We will be implementing a Siamese neural network on AT&T Laboratories Cambridge dataset. We will also cover the basics of this neural network, triple loss function and and will discuss the reason for choosing this architecture. I will explain how the network models a relation between two images and relates them. Outcome of this Talk :- Attendees will be able to possess the power to implement state of the art Facial Recognition program in a few minutes. They will also get to know how facial recognition works when we have very small dataset. They will be able to make a state of the art One Shot Learning face recognition based on Siamese Network (the working force of face_recognition and implementation of Google\u2019s FaceNet). Agenda :- Introduction to Face Recognition [2 mins] Introduction of python library \u201cface_recognition\u201d [1 min] Building a face recognition program using \u201cface_recognition\u201d library\n (possible live demo of the output) [6 min] How \u201cface_recognition\u201d encodes faces [2 min] Introduction of Triplet Loss and Siamese Network and reason to choose one shot learning (which is used to\n encode faces) [5 min] Implementation of Siamese Network using PyTorch on AT&T Laboratories\n Cambridge dataset and its results [10 min] Q&A Session [3 min]", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basic Knowledge of Machine Learning and Neural Networks Love for Pytho", - "Section": "Data science", - "Speaker Info": "Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", - "Speaker Links": "Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Saurabh Ghanekar (~saurabh29)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-state-of-the-art-facial-recognition~eVrXe/", - "title": "Understanding State of the Art Facial Recognition" - }, - "42": { - "Content URLs": "Github repository links will be updated soon", - "Description": "In this talk, I am going to talk about advanced concepts of Python related to Caching. A cache can be easily understood as a saved answer to a question. Caching can speed up an application if a computationally complex question is asked frequently. Instead of the computing the answer over and over, we can use the previously cached answer. Caching is an important component while scaling applications which are to be used by many users. It solves various problems related to cost and latency. Usually it takes more time to retrieve data from DB rather than cache. Using a cache to avoid recomputing data or accessing a slow database provides us with a great performance boost. I will describe in depth the different methods of Caching, their pros and cons. This talk will help developers focus on their code before scaling their applications. It will provide immense performance improvements with this simple concept. Outcomes: The novice audience will be able to understand basic Caching Mechanisms. They will be able to utiilize their knowledge which will serve pivotal while scaling applications Contents to be covered in talk: Local Caching: What is it, how to do it, example, built-in Python libraries: (using cachetools ), advantages, dis-advantages Memoization: What is it, pseudo-code algorithm, implementation using example, built-in Python libraries: (using lru_cache ), advantages, dis-advantages Distributed Caching: What is it, techniques: (using memcached , using pymemcache ) Agenda: Initial 10 minutes: Introduction to Caching and its various techniques. 10 - 20 minutes: Examples and code walk through for various techniques. 20 - 25 minutes: Comparative analysis of how caching is better than non-scaled applications. 25 - 30 minutes: Q&A session", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-caching-in-python~aQm9a/", - "title": "Understanding Caching in Python" - }, - "43": { - "Content URLs": "Will be updated soon", - "Description": "Talk Summary: Bitcoin has become so mainstream these days. It unveiled the importance of decentralization. But how does Bitcoin work? It\u2019s because of its core technology called Blockchain. After the Internet, Blockchain technology is regarded as the next big revolution. This talk gives a hands-on demonstration of how Blockchain technology works by building a toy version from scratch. Outcomes: After this talk the audience should be able to understand the basic working principles of bitcoin. They will be able to leverage their knowledge as a starting point of open-source contributions to projects like Ethereum. This demonstration will consider three important features of Blockchain Technology. All these features are essential to blockchain technology and we will be building a minimal version in Python. Agenda: 0 - 5 mins:\n Blockchains are secure because they use SHA256 or SHA512 algorithm for cryptography. I will describe the logic behind these hashing algorithms and give some computational facts about them. 5 - 10 mins: \n I will use the Python library called \u2018hashlib\u2019 to implement the SHA256 algorithm in Python. This makes us to convert data into SHA256 hashes. 10 - 15 mins:\n The SHA256 algorithm is used to convert all the transactions and their details into a single hash. Once the everything is converted into a hash, this hash must be stored for future usage. After a new transaction is approved, this new transaction and its details are again converted into a new hash along with the previous hash. I will demonstrate the process of storing the hash and using it again for a new transaction. 15 - 20 mins:\n Here I will explain a basic working principle of blockchains and how linking the previous transactions with the new one helps in the their security. The hashes stored are called blocks and the process of liking the previous hash the new hash makes a chain like connection thus forming a Hyperledger. 20 - 25 mins:\n Later in the process of mining will be explained using the variable quantity called Nonce. This explains why bitcoin miners need high computation power to do Proof-of-Work. \nI will also cover a variety of essential terms and concepts through the course of the talk which haven\u2019t been detailed in the agenda. Also, I will use python module called 'TkInter' to build a basic GUI for our blockchain. Last 5 mins:\n Questions and further reading + code sharin", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Love for Python and acquaintance with its libraries", - "Section": "Core python and Standard library", - "Speaker Info": "I am Koushik, a Computer Science sophomore whose research interests lie in decentralization and cryptocurrencies, occasionally working on deep learning projects. As a member of the Next Tech Lab, a QS-Wharton award-winning student-run lab, I work in the Satoshi research group for blockchain technology. I also regularly participate and give talks in paper-reading groups and meetups like PyData", - "Speaker Links": "Visit my profile on LinkedI", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "KOUSHIK BHARGAV M M Srinivas (~koushik_bhargav_m)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchains-from-scratch~dPl4d/", - "title": "Understanding blockchains from scratch!" - }, - "44": { - "Description": "With examples build the concept of creating a language model using text data", - "Last Updated": "19 Jun, 2018", - "Section": "Data science", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "divya chowdhary (~divya69)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~aOkra/", - "title": "Language Model (Text Analysis) using Python from scratch" - }, - "45": { - "Description": "Abstract: Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. The Big Question: \"Is everything Perfect in AWS Lambda?\" .... Well it depends on how you use it and this is what I will cover in my Talk. Note: This Talk will have some code references using PYTHON Outline: What will you learn from this session/talk: What are Lambda Functions . What are the different features of Lambda Functions. The famous Lambda Timeout . The Deployment and Resource Limits . The Cold Start issue and its workarounds. The Cost Factor Why do you need to know this: Helps develop decision making in the project design architecture The Case Study: Case Study in which you should/should not use Lambda Functions. Real Life project experience: The hidden learning with an on job project on the limitations to Lambda Function. Q&A ", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Python: Basics of Serverless Computing Basic of Python Programming Basics of Python Libraries Usages (Imports)", - "Section": "Others", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Ritu Mehra (~ritu86)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-lambda-with-python-dos-and-donts~dNjvd/", - "title": "AWS Lambda with Python : Do's and Dont's" - }, - "46": { - "Content URLs": "https://docs.openstack.org/infra/jenkins-job-builder", - "Description": "Jenkins job builder is an openstack project used for automation and reusing of templates in yaml and json to make jobs and subscribe them to Jenkins. People who like to save time on tedious details can use this open source software and live there life a little better", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Jenkins( a little bit )\nPython\nPip\nRelated libraries like PyYAML, Jinja etc", - "Section": "Developer tools and Automation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jenkins-job-builder-automating-jobs~aMgGd/", - "title": "Jenkins job builder - automating jobs" - }, - "47": { - "Content URLs": "Coming soon", - "Description": "Do you know, your favorite superheroes in Avengers , cute characters of Kung Fu Panda and the epic wars of Baahubali were brought to screen with the help of python ? If you are into gaming , you need to thank python for the characters you have played and the world you have explored. Even the next generation technologies like AR and VR use python to deliver their magic to you in new formats. It won't be a overstatement if we say python is the backbone of the animation Industry In this talk we go behind the scenes and see how our favorite programming language is used in the animation industry, why it plays a huge role and the kind of applications built with it", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "A bit of curiosity and interest in learning about usage of python in various industries, usually less represented in the python community", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/amazing-world-of-animation-powered-by-python~dLDrd/", - "title": "Amazing world of animation - powered by python" - }, - "48": { - "Content URLs": "Coming Soo", - "Description": "It's really hard to escape the 3D buzzword. You find it used in all sorts of places, right from the movies you watch, Games you play, 3D printing , webgl graphics in the browser and VR , AR applications. In this workshop we are going to cover the basics of 3D and do a hands on session on creating 3D Art using a professional open source application called Blender . Of course, python is a major part of blender and we will put your python skills to some good use. What is this workshop NOT about : This is not one of your boring programming workshops. We are not going to try improve your python knowledge ten folds in a matter of 2 hours. What is this workshop about : Come to this workshop if you want to be a kid again and have fun creating art in 3D using Blender and Python !!! Who am I : Hello, Sreenivas here! I am a 3D artist turned programmer. I work in the animation and VFX Industry and battle production issues with the power of python. I love art, technology and excited about combining both. I support open source by evangelizing Blender and Krita . Who are you : You are a person with an open mind, bitten by the curiosity bug and intrigued by how 3D Art is made. You have at least basic knowledge of python and ready to use your super powers to create 3D Art. Takeaway : By the end of the session\u2026 You will know a broad overview of 3D Art . Have a working knowledge of the professional open source 3D application, Blender . Get a deeper understanding of the workflow for creating 3D art. Use your python skills in the process of creating 3D Art.", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Laptop with a decent GPU (any modern laptop) A mouse with a middle click button (scroll which is clickable) Download and install Blender from https://www.blender.org/download/", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3d-art-using-blender-and-python~aKBxe/", - "title": "Creating 3D Art using Blender and Python" - }, - "49": { - "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. \nThe website for the workshop at PyCon India 2015 is here . \nYou can find the introduction slides here , the sphinx tutorial here and the exercises in form of IPython notebooks. Note: that the notebooks are hosted statically, you can download from here and run locally to have an interactive session", - "Description": "SymPy is a Python library for symbolic mathematics. It aims to be an alternative to systems such as Mathematica or Maple while keeping the code as simple as possible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.\nThe talk will highlight the following: SymPy, what it is and how it is different from others. What is symbolic computation and how SymPy achieves it. Power of SymPy: Symbolic manipulations Equation solving Calculus Linear Algebra ", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Basic mathematics, just enough to appreciate the manipulation done by the computer algebra system and Python. No prior knowledge of SymPy or other Python libraries is required", - "Section": "Data science", - "Speaker Info": "SymPy India developers will be conducting the talk: Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers module", - "Speaker Links": " Resource repository: https://github.com/sidhantnagpal/pycon-sympy SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://www.youtube.com/watch?v=5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://www.youtube.com/watch?v=nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://www.youtube.com/watch?v=AqnpuGbM6-Q SymPy Tutorial, SciPy 2014: https://www.youtube.com/watch?v=Lgp442bibDM SymPy Tutorial, SciPy 2013: https://www.youtube.com/watch?v=dAgShwIx72c", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Yathartha Joshi (~Yathartha22)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-sympy~dGxJe/", - "title": "Symbolic Computation with SymPy" - }, - "50": { - "Content URLs": "Will share the Slides post my Talk through a proper channel", - "Description": "Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. Note: In this workshop all the implementation will be done using PYTHON Session Takeaways: How to use different features of AWS to create your Serverless Application. What is Serverless Computing and how \"Functions as a Service\" is a revolutionary way to develop applications. Understand AWS Lambda Functions, the FaaS offering on Amazon Web Services. Understanding of the AWS services - Lambda, S3, EC2, CloudWatch, API Gateway, RDS, IAM How to access the AWS services using Python libraries in the Lambda Function. Hands On Cloud Native Web Applications Development using AWS Lambda and other offering. Practical examples of how you can combine multiple services and events in AWS and develop applications rapidly using AWS Lambda Functions", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Python: Basic of Python Programming Basics of Python Libraries Usages (Imports) AWS Free Tier account - https://portal.aws.amazon.com/billing/signup?redirect_url=https%3A%2F%2Faws.amazon.com%2Fregistration-confirmation#/start", - "Section": "Web development", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ritu Mehra (~ritu86)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/serverless-application-development-using-aws-and-python~eEvga/", - "title": "Serverless Application Development using AWS and Python" - }, - "51": { - "Content URLs": "https://docs.google.com/presentation/d/1_hyRLHdITpIMzhAbpxuaTQkm6qop4ZWQt6ERGW4MFag/edit?usp=drivesdk&ouid=10471550379351873801", - "Description": "This is a simple talk about web scraping using python.In this lecture we going to have a clear picture of webscraping. \nBy the end of the lecture audience are going to have a clear picture of \nWhat is web scraping? \nWhat is the use of it? \nWhat are the useful libraries in python for web scraping? \nPros and cons of the libraries\nAnd mainly how to parse the Websites with practical examples", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "A little amount of python knowledge is useful but not mandatory. I'm going to explain right from the very beginnin", - "Section": "Others", - "Speaker Info": "I am a student of Vishnu Institute of technology, Bhimavaram. I am studying 2nd IT. I was fallen in love with coding when I listened to the 1st lecture of my academic about C programming. That day changed my life. I have been working on python from January 2018.\nI am a quick learner, self disciplined, self motivated guy. \nMy hobbies are coding and learning new thing", - "Speaker Links": "https://www.sololearn.com/Profile/495149", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Deepak Puppala (~deepak12)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping~bDrKe/", - "title": "WebScraping" - }, - "52": { - "Content URLs": " Hydra Draft Hydra Ecosystem Wiki Hydrus Hydra Flock Demo Hydra CG homepage I'll be sharing my slides after the talk", - "Description": "Building Web APIs seems still more an art than a science. How can we build APIs such that generic clients can easily use them? And how do we build those clients? Current APIs heavily rely on out-of-band information such as human-readable documentation and API-specific SDKs. However, this only allows for very simple and brittle clients that are hardcoded against specific APIs. Hydra, in contrast, is a set of technologies that allow us to design APIs in a different manner, in a way that enables smarter clients. The main aim of this talk is to provide an overview of Semantic Web, Hydra Draft, and Hydrus. Hydra - Hydra is a framework to enable REST API to be described semantically using RDF. It is based on JSON-LD and proposed as W3C draft . Hydrus - Hydrus is a Flask server meant to build and deploy Hydra-based Web APIs in a straightforward and effective way. Hydrus utilises the power of Linked Data to create a powerful REST APIs to serve data. Hydrus uses the Hydra draft standard for creation and documentation of it's APIs. The flow of the talk will be as follows: My Introduction Brief Overview of Semantic Web and JSON-LD What is Hydra Draft? Detailed introduction to Hydrus How can we use Hydrus to create REST APIs easily? Future Scope An interactive Semantic Web demo. Q/A session", - "Last Updated": "18 Jun, 2018", - "Prerequisites": " Python Basic knowledge of APIs and Web", - "Section": "Web development", - "Speaker Info": "My name is Akshay Dahiya. I'm a Mentor and Organization Admin for Python Hydra in Google Summer of Code 2018 and I love working on Semantic Web and AI related projects. \nRecently, I have been learning through Udacity, adding more structure to my education on Web Technologies, Machine Learning, Deep Learning and Software development in general. I also mentor students across various Udacity Nanodegree programs (FullStack Nanodegree, React Nanodegree and Deep Learning Nanodegree) in my free time", - "Speaker Links": " http://www.xadahiya.me/ https://github.com/xadahiya/ https://www.linkedin.com/in/xadahiya/ http://www.typingeek.com/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Akshay Dahiya (~xadahiya)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3rd-generation-web-apis-using-hydra-and-hydrus~dBpYa/", - "title": "Creating 3rd Generation Web APIs using Hydra and Hydrus" - }, - "53": { - "Content URLs": "A library for ANTLR that is being built by me is available here: https://gitlab.com/virresh/coala-antlr ANTLR's official page: http://www.antlr.org/ My blogs related to ANTLR in Python: https://virresh.wordpress.com/tag/antlr/ An example calculator: https://github.com/virresh/ANTLR4-Exampl", - "Description": "This talk aims at introducing ANTLR for python 3, and talk about Abstract Syntax Trees. It will present an overview of the process, the intricacies and will end with a concrete example to show the utility. ANTLRv4 is a tool that can generate parse trees for any compatible grammar, and provide tools to walk through that tree, so I will illustrate how to use that rather than dwelling more on the theory aspect of the parse trees and boost up the development of language tools. There is a speciality with ANTLRv4, we can separate context from the grammar (so we can get very close to the expectation that grammars are context free). I expect the session to be beginner friendly so no pre-requisites save some basic python expected. Also I will cover some basic examples, and also a demo of an actual language grammar to create a meta-program if time permits. The session is expected to have the following things: What is a grammar ? What are Parse trees and how do they compare to ASTs ? What is ANTLR ? (The parser generator and the runtime provided) How do we use a parse tree ? (dwelling on setting up the environment for ANTLR based development and a short, basic calculator building example) Visitors and Listeners A short real world example on detecting technical constricts in actual programming languages (probably Python itself)", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "A working knowledge of python basics and some familiarity with some sort of command line interface is ideal (best suited if you are familiar with any unix/linux based systems, simple script invocation etc", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm a student presently pursuing BTech in CSE at IIIT-Delhi, and am a GSoC student this year at coala.io and have been programming various stuff using python for around two years. I am developing a library to facilitate easy usage of ANTLR for building linting tools. I've worked on a large array of technologies in any area that I get to know about, ranging from Full stack development, to Systems programming to Language tools. I do my best to pick up and experiment with whatever technologies I can, and I love to learn ", - "Speaker Links": "GitHub: https://github.com/virresh Website: https://virresh.github.io/ Blogs: https://virresh.wordpress.com/ LinkedIn: https://www.linkedin.com/in/virresh", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viresh Gupta (~virresh)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-antlr-with-python~az5ye/", - "title": "Using ANTLR with python" - }, - "54": { - "Description": "We have a word for it now - Domotics . The fun started a year back when I laid hands on this beautiful device from Amazon, which could not only manage your music, reminders, lists but also make calls and send messages. Basically, a smart phone in the cloud to be used without hands. But a developer sees endless possibilities with this powerful tool. Although speech recognition technology itself is nothing new, Amazon Echo has made its way to the homes of regular consumers. This talk is specially focused on giving a head start to the attendees about building and using powerful applications in python using an Alexa device. Being a python developer for the past 10 years and working on alexa skills for the past year, I intend to share my experience with the python community and enthusiasts. Broadly, this talk will be covering the following topics: How the echo framework and Alexa skills work An introduction to creating alexa skills in python with flask-ask Handling requests , responses , contexts and sessions . Testing applications with ngrok and deploying to the cloud. A sneek peek into other home automation possibilities like micropython embedding with popular microprocessors. The talk would be illustration and example driven and will include demos of cool app(s) I have been working on", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "This talk is intended for developers who have a decent grasp on the basics of the python framework and trends, although you do not need knowledge of any specific packages or libraries. Just an enthusiastic mind is enough! The primary takeaway of this talk would be learning how to get started ideating and building applications for an alexa enabled smart home device and discuss some cool developer tips", - "Section": "Developer tools and Automation", - "Speaker Info": "Sonal Raj ( @_sonalraj ) has been an avid pythonista for 10 years. He has been working as an integral part of the financial technology industry for the past 4 years. Sonal holds a masters in Information Technology and has been a research fellow at the Indian Institute of Science, Bangalore. His domains of interest include distributed systems and graph databases, and he loves to explore new gadgets and develop new technology. He is also the author of the best selling book 'Neo4j High Performance' ", - "Speaker Links": " Talk at PyCon India 2014 Talk at PyCon India 2013 Real Time Computation with Apache Storm - IISc Bangalore Human Computer Interaction Systems : Slides Website Github Reasearch Profile", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sonal Raj (~sonal)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/alexa-enabled-smart-home-programming-with-python~dy5nd/", - "title": "Alexa enabled smart home programming with Python" - }, - "55": { - "Content URLs": "http://github.com/gnsrikanth/simplelinuxbackdoor", - "Description": "In this talk, we discuss how python scripts can be used in the world hacking. Python can be used to automate many tasks and see how we can use network protocols using python. Programming isn't just codes, but it's a way of communication. This talk is more an awareness of the possibilities python can be used and hacking is one of them. We break down steps to hack a system and automate tasks using python. Topics covered: Sockets in python Using TCP, UDP protocols and creating a Server/Client A basic backdoor for windows Using HTTP protocol to steal users data Using encryption to obfuscate network traffic Subprocess module Pyinstaller to make binaries of malware Bypassing antivirus (we will test by uploading exe to virustotal) Using Sqlite3 to retrieve chrome passwords Emailing subprocess outputs with python Send data to google forms as POST Simple Ransomware code Other Python tools for hacking", - "Last Updated": "16 Jun, 2018", - "Prerequisites": "Basics in python, Operating system fundamentals, Networking basics", - "Section": "Networking and Security", - "Speaker Info": "I am Grandhi Srikanth, and truly passionate in cyber security. I hold C|EH, CCNA in Routing and Switching, Cyber Ops certification and interested in creating malware codes and as python makes it simple, I like using python", - "Speaker Links": "Twitter: @gn_srikanth LinkedIn: https://www.linkedin.com/in/grandhi-naga-srikanth/ Blogs: www.thebinarynoob.com Github: https://github.com/gnsrikant", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Naga Srikanth Grandhi (~naga_srikanth)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/coding-back-doors-with-python~ax5Bb/", - "title": "Coding Back-doors with Python" - }, - "56": { - "Content URLs": "Apache_Build_Monitor Jenkins' REST API & Pytho", - "Description": "As a build and release engineer, have you felt how good it would be to know the status of scheduled nightly builds before you reached office ? As a developer, have you wondered, while you were away from the desk, what's the status of quality gate builds that should be passed before the changes can be integrated to the mainline ? Intent of this talk is to outline what's offered via Jenkins's REST API and showcase some of the possibilities by consuming the API using Python", - "Last Updated": "16 Jun, 2018", - "Prerequisites": " Read-up docs on Python libraries XML, JSON Capability to follow and assimilate code snippets", - "Section": "Developer tools and Automation", - "Speaker Info": " Speaker works for a CyberSecurity firm in Bengaluru, India Likes being outdoors and reading books.", - "Speaker Links": "Linkedi", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ramanathan Muthaiah (~ramanathan)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/consuming-jenkinss-rest-apis-in-python~dw58a/", - "title": "Consuming Jenkins's REST APIs in Python" - }, - "57": { - "Content URLs": " Code will be updated on github very soon.", - "Description": "There are many framework available in the market for free and with a lot\u2019s of feature like Django , Flask , Tornado . These framework help us to build web application and serving the files over the network without worrying about the low level details like how it works , how the files are being severed to the clients , web browser and how it handles the clients to be connected and serving the data to the lot\u2019s of clients with minimum amount of time with managed thread. So in this talk I\u2019ll share my knowledge how does the web server work and how we can build our own framework like other available framework and further enhance it , to make it big, and to handle the clients with multiple processes and threads. In this talk I will be talking about : What is a WebFramework and How does a web framework work? How we can make a simple web sever to serve the \u201chello world\u201d webpage to the browser How we can make the HTTP custom request header to tell the browser about the current status of request on the different situation like 200 , 404 , 500. how to server files like html, css to generate the advance webpages using socket to the browser. Getting the requested URL Params and serving the files over the network. Making a Download link and let the user to download the files over socket. Improvement of request and response time of the web server and optimising it so that the web server can handle more and more clients over the network. ", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "1. Basic python understanding. 2. Python installed on your system. 3 .Socket library (you can install it using the pip installer", - "Section": "Core python and Standard library", - "Speaker Info": "I am Nawneet Kumar, CTO at Elezire Technologies Pvt. Ltd. I have worked in Different Projects and in Different Languages in my past year. I have worked in era like IOT Development , Android Application Development , IOS Development and Web Development", - "Speaker Links": "Linkedin : https://www.linkedin.com/in/nawneet-kumar-77b64814b/ github : https://github.com/navSharma4", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "nav.sharma47", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-own-webframework-like-django-flask-tornado-to-serve-web-application-using-core-socket-programming~av55e/", - "title": "Building Own WebFramework like Django , Flask , Tornado to serve Web Application using Core Socket Programming" - }, - "58": { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/welch/seasonal Example Slides: https://www.slideshare.net/CheukTingHo/pydata-amsterdam-2018-time-series-analysis-with-seasonal-data-9909335", - "Description": "For time series analysis, everyone\u2019s talking about ARIMA or Holt-Winters. But there\u2019s other models which could also break down a seasonal series into trend, seasonality and noise. We will use an open source Python library called Seasonal to analyse B2B worldwide travel data. Times series analysis is an important part of data analysis for lots of businesses. It is very often for stakeholders to be interested in the performance of the business by analyzing measurements of profit, cost, number of sale, number of searches etc over time. In this talk, we will do a case study of showing how we estimate the impact public holidays made on the travel business. The method of analyzing the time series by seasonal breakdown will be explored and the work flow of solving the problem will be explained. In the first half of the talk, an introduction about time series and its characteristic will be explained for audiences who is new to analysis on time series. The data we use will be from a business to business travel company. It has seasonality thought out the year, a weekly cycle and also a growing trend in business. As the company have clients around the world, data from different countries will shows different behaviors as well. Therefore, before we show the analysis, the complexity of the data will be explored. In the second half, we will introduce a open source Python library called Seasonal. Using this package, we will demonstrate how to break down the travel data and extract the fluctuation of the sale in different countries. By comparing the fluctuation and Google calendar, public holidays in different countries can be spotted and their impact on the business can be estimated. This talk is for people who are interested in time series analysis and its application in business. Audiences with or without experience would also found this talk useful in giving them insights in how a business could benefit in making use of the data and doing a proper time series analysis", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-time-series-analysis-with-seasonal-data~er5pd/", - "title": "Case Study in Travel Business - Time Series Analysis with Seasonal Data" - }, - "59": { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/networkx/networkx Slides (not finalized): https://docs.google.com/presentation/d/1y_Wmuv_hqs8OZTI8XLJ5ajvjEpllK7Xeifa52yTpw-k/edit?usp=sharin", - "Description": "When you make a search for a hotel room, do you know how many travel agents are searching for you at the same time? In this talk, we demonstrate how to use the millions of searches a sourcing company received to build a network of travel agents and finding the main hubs among them using NetworkX. Network analysis is getting more and more attention in Business Intelligence, people hope to get information out of the structure of an organization or a communication network. In this talk, we use the hotel room search requests from travel agents, including online public website, B2C, B2B and B2B2C, to build a relational network among them. By using this network as an example, we demonstrate how insights can be extract by studying network properties. In the first half of the talk, we will explain how the network is built using NetworkX, an open-source python library that is designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. When 2 agents are making the same search at the same time , a link ( or an \u201cedge\u201d in network analysts terms) is made pointing form the initial searcher to the subsequent searcher. Using a list of these searches, a directed graph is built. We will also demonstrate how to pick the biggest connected component out form the graph. In the second half, with the graphs created, we show how different functions of NetworkX can be used to study the graphs. By compare the graph properties of our graph to the other popular network graphs, we can get the insight of how the network was created. Also by studying the graphs, we can understand the behavior of the agents and can even figure out which agents are acting as main hubs in the network. This talk is for people who are interested in network analysis and would like to see how it can be used in a business case. Audiences with any level of python experience can learn some basic concept of network analysis work and how it can be applied to provide business insights", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-understanding-agent-connections-using-networkx~bq5pb/", - "title": "Case Study in Travel Business - Understanding agent connections using NetworkX" - }, - "60": { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/seatgeek/fuzzywuzzy Source code available on Github: https://github.com/Cheukting/fuzzy-match-company-name Slides (not finalized): http://slides.com/cheukting_ho/fuzzy-matchin", - "Description": "Ever encounter a tricky situation of knowing there\u2019s names that are the same, but matching strings straight away leads you no where? All you need is FuzzyWuzzy, a simple but powerful open-source Python library and some wit. This talk will demonstrate how to efficiently fuzzy match company names. Matching strings should be one of the first natural language processing problem that human encounter since we start use computer to handle data. Unlike numerical value which has an exact logic to compare them, it is very hard to say how alike two strings are for a computer. One may compare them character by character and have an idea of how many characters in the pair of stings are the same. Unfortunately in most application we need computer to perceive strings like we do and therefore we have to use fuzzy matching. Fuzzy matching on names is never straight forward though, the definition of how \u201cdifference\u201d of two names are really depends case by case. For example with restaurant names, matching of words like \u201ccafe\u201d \u201cbar\u201d and \u201crestaurant\u201d are consider less valuable then matching of some other less common words. Also, do we consider company names that matches partly (like \u201cHappy Unicorn company\u201d and Happy Unicorn co.\u201d) are the same? In the first half of the talk Levenshtein Distance, a measure of the similarity between two strings, will be explained. Different functions in FuzzyWuzzy like \u201cpartial_ratio\u201d and \u201ctoken_sort_ratio\u201d will also be explored and compared for difference. It is very important to understand our tool and choose the right one for our task. Then in the second half, we will start tackling the example problem: matching company names, we will show that besides using FuzzyWuzzy, we have to also handle problem like finding and avoid matching of common words and speeding up the matching process by grouping the names. By combining all tricks and techniques that we demonstrate, we will also evaluate how efficient this method is and the advantage of using this method. This talk is for people in all level of Python experience who would like to learn a trick or two and would like to be able to solve similar problems in the future. Theory of how the library works will be explained and It is easy to be pick up even for beginners", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fuzzy-matching-smart-way-of-finding-similar-names-using-fuzzywuzzy~epKVd/", - "title": "Fuzzy Matching - Smart Way of Finding Similar Names Using FuzzyWuzzy" - }, - "61": { - "Content URLs": "Project source code on Github: https://github.com/Cheukting/GCP-GPU-Jupyter Demo code: https://github.com/Cheukting/jupyter-cloud-demo Example slides: https://www.slideshare.net/CheukTingHo/pycon-israel-launch-jupyter-to-the-clou", - "Description": "There are lots of reasons using a cloud service is favorable, but how to make sure consistency between development and deployment? With Docker and Terraform, we can create the same environment on cloud easily. For example, we will deploy a Jupyter notebook on Google Cloud Platform using both tools. In this talk, we will use a task: hiring a GPU on Google Cloud Platform to train neural network, as an example to show how an application can be deployed on a cloud platform with Docker and Terraform. The goal is to have Jupyter Notebook running in an environment with Tensorflow (GPU version) and other libraries installed on a Google Compute Engine. First we will briefly explain what is Docker and what is Terraform for audiences who has no experience in either or both of them. Some basic concepts of both tools will also be covered. After that, we will walk-through each steps of the work flow, which includes designing and building a Docker image, setting up a pipeline on Github and Docker Hub, writing the Terrafrom code and the start up script, launching an instance. From that, audiences will have an idea of how both tools can be use together to deploy an app onto a cloud platform and what advantages each tool can bring in the process. This talk is for people with no experience in application deployment on cloud service but would benefit form computational reproducibility and cloud service, potentially data scientists/ analysts or tech practitioners who didn\u2019t have a software developing background. We will use an example that is simple but useful in data science to demonstrate basic usage of Docker and Terraform which would be beneficial to beginners who would like to simplify their work flow with those tools", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Developer tools and Automation", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/launch-jupyter-to-the-cloud-an-example-of-using-docker-and-terraform~boKXb/", - "title": "Launch Jupyter to the Cloud: an example of using Docker and Terraform" - }, - "62": { - "Content URLs": "Source code available on Github: https://github.com/Cheukting/Style-mimicking-text-generator Example slides: https://slides.com/cheukting_ho/pylondinium1", - "Description": "Computers are getting closer to speak like humans. But can we even make them speak in particular ways, like as Trump or Shakespeare? In this hands on talk we will see how this is possible with the latest deep learning techniques combined with word embeddings and other advanced NLP technique. In this talk, first we would introduce two neural network and machine learning mechanisms which in popular and widely used in NLP (natural language processing): Word Embeddings and Recurrent Neural Network. Word Embeddings is a way to extract the context of a word by \u201clearning\u201d its presence in a paragraph; while Recurrent Neural Network, including LSTM (long short-term-memory), enable us to \u201ctrain\u201d sequential data. After that, we will showcase how to implement these mechanisms in a neutral network. With that, we can \u201cbuild\u201d a machine to generate articles, plays or speeches in the style of the training corpus and have lots of fun. In the first half of the talk, concepts of how Word Embeddings and LSTM works will be explained. Audiences will understand why this is essential in the field of NLP and why we are using it. In the second half, a code demo will be used to showcase how to implement these mechanisms. Through an example, audiences will learn how Keras is used together with Tensorflow and Python to build a sequential neutral network. We will showcase generating a paragraph using Shakespeare\u2019s play and another one using Trump\u2019s speech. This talk is for people who have some experience with data science and understand the concept of how a neural network works, but would like to go deeper into the details of how does it applied to NLP to solve more complex AI problems. We used very simple code but did a complex task like text generation, that opens the door for a lot of people who wants to experiment with deep learning", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "Basic concepts of Neural Network like Stochastic Gradient Descent and back propagation, as it will not be covered in the talk due to time limit", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-keras-building-an-ai-that-talks-like-shakespeare-or-trump~enX7b/", - "title": "Deep Learning with Keras : Building an AI that Talks like Shakespeare or Trump" - }, - "63": { - "Content URLs": " Hello world of chatbots world - wordbot An Experiment with Opensource chatbot engine - RASA NLU ", - "Description": "Google Assistant and Siris\u2019 of the world have tickled our curiosity enough to deep dive and understand under the hood technologies that make a chatbot. Though we don\u2019t have Google level of data to create a generalized chatbot, we can use the existing NLP engines and create chatbots that produce valuable results in a specific domain. For eg., anything that goes in your FAQ page can be converted into content for a chatbot. In this talk, I\u2019ll share my 2-year journey with chatbots. Existing bot platforms and how to leverage it to build your own chatbots and connect it with messaging platforms like slack, telegram etc., \nI\u2019ll also share my experience from my experiment on trying to build your own NLP engine. Key Takeaways Chatbot\u2019s architecture Natural language Processing, Understanding, and Generation what and how it plays an important role in building chatbots How to use existing chatbot engines to build a chatbot How to connect chatbots to Slack, FB Messenger etc., How to build your own chatbot engine", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of Pytho", - "Section": "Data science", - "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape - Tech Enthusiast - Django & Chatbot specialist - Mentor/Speaker Build2learn , Chennai Geeks. Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", - "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavan", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Bhavani Ravi (~bhavaniravi)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatbots-101-peeping-under-the-hood~bm6Gd/", - "title": "Chatbots 101 - Peeping under the hood" - }, - "64": { - "Content URLs": "GitHub Repo: https://github.com/sleebapaul/gospel_of_rnn.git Google Colab Notebook: https://drive.google.com/file/d/1qh94MdQr9SeTLxGkMJc6kZGguRID8LqW/view?usp=sharing Blog: https://sleebapaul.github.io/rnn-tutorial", - "Description": "Language modeling was a complex task of previous days. But advancements in Deep Learning has solved this problem very effectively. Using many to one architecture of Recurrent Neural Networks, I've built a language model which can effectively generate the fifth gospel of bible by learning from four existing gospels. This model is also able to divide verses and chapters along with meaningful passages", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Recurrent Neural Networks basics Deep learning basics Language modeling basics Familiarization with PyTorch", - "Section": "Data science", - "Speaker Info": "Sleeba Paul is a Power System graduate and published researcher who loves intelligent machines. He currently works as a Machine Learning Engineer at Refly; an AI startup in India where he works on content enhancement and video analytics", - "Speaker Links": "Personal website: http://sleebapaul.github.io/ LinkedIn: https://www.linkedin.com/in/sleebapaul/ Github: https://github.com/sleebapau", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sleeba Paul (~sleeba)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gospel-of-lstm-how-i-wrote-5th-gospel-of-bible-using-lstms~elLMe/", - "title": "Gospel of LSTM : How I wrote 5th Gospel of Bible using LSTMs" - }, - "65": { - "Content URLs": " Research Paper Github repository of project with over 80 stars: pyCAIR Beta release on PyPI: pyCAIR Docs: pycair.readthedocs.io", - "Description": "In this talk, I will speak about a simple yet very powerful image manipulation mechanism. The naive user utilizes the services of any standard toolkit, be it a web service or a remote application for image manipulation. The black box approach to this process is: A user provides an image and other parameters as input to the toolkit which in turn produces the results and returns it back to the user. Often these results are not up to the mark. The image sometimes gets distorted, misaligned or blurred. Deviating from the standard mechanisms, I would like to talk about a technique called as Content aware image resizing . The primary factor in this technique is the content . It is the content which drives the entire technique. The image is cropped, enlarged or modified keeping in mind the primary factor. I will talk about an algorithm called as Seam Carving which is used under the hood to achieve the aforementioned technique. It is this algorithm and the power of Python libraries , that makes this technique perform better than the standard mechanisms. Agenda of Talk: Introduction: Basics of seam carving, how the algorithm works Understanding energy concepts, basics of computer vision and dynamic programming Walk over the pseudo-code and dry run of algorithm Comparative analysis of this technique with standard mechanisms Q&A Session Conclusion", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pycair-smart-image-resizing-using-python~bkK6b/", - "title": "pyCAIR: Smart Image Resizing using Python" - }, - "66": { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "Problem description : Deep learning algorithms have shown great results in speech recognition domain, So here we have used deep learning techniques to enable the machines to read the lips from a video without sound better than humans. By analysing the movement of lips of a person we are trying to predict what that person is trying to speak.\nAutomated Lip reading can be helpful in many ways. Some of them are: Silent dictation in public spaces. Covert conversation. Helping the people with speaking ade in talking to other people. Improved hearing aids. Speech recognition in a noisy environment. The talk will be focused on : How the problem should be tackled. Discussion of different phases Algorithms and python libraries used for implementation.", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations Basic understanding of Recurrent Neural Networks : An excellent resource to understand this is Understanding LSTM Networks . Similar to CNN the motive should be to understand the basic working of Recurrent Neural Networks. The coding part will be discussed in the talk.", - "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saqhas", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-lip-reading-using-convolutional-neural-networks-in-python~ejMvd/", - "title": "Automated Lip reading using convolutional Neural Networks in python" - }, - "67": { - "Content URLs": "Will be provided soo", - "Description": "Everyone need not to know everything to build something great. If you are a student and wants to build a major/minor or a professional level project without worrying about the DevOps/Servers and its cost. If you are a Data Scientist and works with files/data and want to make your analytical tool public but you don't want to get in Server handling and learning some web framework . If you are a Frontend developer or work in a fast paced organisation where shipping out fast, better, robust and always running services are required. If you want to prepare a POC or a working model API fast without the requirement of server engineer. Then, this Talk is the place which your are looking for. This talk will be focused on How one can build really scalable and robust web APIs without learning any web framework that too in a very very easy manner. We will be talking about a python package I have made called Lamlight which makes the process of building web APIs as simple as a Git push . This package provides a CLI tool and answers the limitations imposed by the services like AWS lambdas . Lamlight enables Developer to: Make web APIs without learning any web framework or DevOps. Just focus on the core business logic because everything else it will provide you. (Eg: full python boilerplate, CLI automation tool ) Live code Changes. Put large dependencies on your Serverless web api like Numpy, Scipy, Pandas. Save 80% of time by making the process as simple as Git push. Objective of the Talk: Problems faced in a Servered Architecture. Introduction to Serverless Web APIs. Why Shift to Serverless Web Architecture. Platforms providing these Services and their limitations. Get Faster and beat these Limitations. Problems solved by Lamlight. Explanation of its working. Live demo. Q & A The talk would be extremely beneficial for students, Algorithm developer, Frontend Developer, Data scientists and others who are not familiar with server side development and server technologies or want to save time of server handling but still want their work to be done", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Love for Python Linux AWS(Optional)", - "Section": "Developer tools and Automation", - "Speaker Info": "Hello I am Rohit Negi. I am a developer with 1 year of professional experience and +2 years of freelancing experience. I have a Bachelor's degree and I am currently working as a developer in Elucidata Corporation, where I work on making technical architectures for the system to get connected and work robustly , designing Server APIs, Working with Frontend technologies like Angular to make the robust Frontend apps. I am very passionate about creating new and better stuff", - "Speaker Links": " https://www.linkedin.com/in/rohit25negi/ Email: rohit25.negi@gmail.com", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rohit Negi (~rohit17)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lamlight-develop-webmobile-apps-without-learning-django-flask-and-any-other-web-framework~egKke/", - "title": "Lamlight: Develop web/mobile apps without learning Django, Flask and any other web framework" - }, - "68": { - "Content URLs": "GitHub More content will be updated soon", - "Description": "What is Transfer Learning? Transfer Learning is the method of reusing our existing knowledge developed for one task to solve a similar task. Say, you want to detect cars on night-time images and instead of learning from scratch we could reuse our existing knowledge from a model which has been trained on day-time images. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. I believe Transfer Learning is a major achievement in our quest for Artificial General Intelligence (AGI) as Transfer Learning allows us to generalize our knowledge which is something we humans excel at. Andrew Ng, ex-chief scientist at Baidu, co-founder of Coursera and professor at Stanford, said during his widely popular NIPS 2016 tutorial, \u201cTransfer Learning will be the next driver of ML success.\u201d Training Deep Neural Networks from scratch is an expensive process. Not only does it require a lot of compute resources and time, deep Learning models require a huge amount of data and it is a major bottleneck when it comes to start-ups and niche areas of research like health care. What you will learn :- How to build an image classifier in a few minutes using Transfer Learning When and how to fine-tune pretrained models Freezing layers of a pretrained model depending upon the scenario Using ConvNet as a feature extractor Using differential learning rates Constraints of using pretrained models Transfer Learning : Beyond Computer Vision Cross-Lingual Domain Adaptation : Using the knowledge we have learnt from one language and applying our knowledge to another language is another application of transfer learning with huge potential. Cross-lingual adaptation methods would allow us to leverage the vast amounts of labeled data we have in English and apply them to any language, particularly languages with very less labeled data such as Indian languages. Reinforcement Learning and Learning from Simulations : Training an agent (in Reinforcement Learning) to achieve general artificial intelligence directly in the real world is too costly and hinders learning initially through unnecessary complexity. It is better to train an agent in a simulated environment such as the OpenAI Gym before deploying it in the real world. Eg: Self-driving cars Agenda 1.Introduction to Computer Vision (3 min) 2.Introduction to Transfer Learning (3 min) 3.Why should you use Transfer Learning? (2 min) 4.When to use Transfer Learning? (2 min) 5.Build an image classifier in minutes using Transfer Learning (2 min) 6.Effective Transfer Learning techniques (6 min) 7.Feature Extraction using pretrained models (3 min) 8.Constraints of using pretrained models (1 min) 9.Transfer Learning beyond Computer Vision (3 min) 10.Transfer Learning : A right step towards Artificial General Intelligence (AGI) (2 min) 11.Q&A session (3 min", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of deep learning Love for Pytho", - "Section": "Data science", - "Speaker Info": "Hi! I\u2019m fascinated by AI and it\u2019s applications particularly in art and culture - generating art, fashion styles, music, literature, etc. I\u2019m a 3rd year student (just started) at SRM Institute of Science and Technology, Chennai studying Computer Science Engineering. I\u2019m also part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in AI, Blockchain, Computational Biology, Electrical Systems, Internet of Things, and Mixed Reality. I\u2019m currently working as a Computer Vision intern at Cogknit Semantics, Bangalore. I'm working on a fashion recommender system which analyses an image of a shirt/pant/shoe and suggests matching clothes to go along with it. I love Python because of it\u2019s simplistic philosophy and lucid coding style which allows me to think more about model architectures rather than fixing bugs in my code", - "Speaker Links": "Connect with me on LinkedIn Find me on GitHub Follow me on Twitter E-mail me at : niladrishekhardutt@gmail.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "niladri99", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-subtle-art-of-effective-transfer-learning~dw5ra/", - "title": "The Subtle Art of Effective Transfer Learning" - }, - "69": { - "Content URLs": "https://www.slideshare.net/mobile/karx01/micro-python-pycon-india-2018-proposal-kartik-aror", - "Description": "This session will aim to achieve 2 objectives Introduce you to (in a fun and practical way), what is microPython. equip you to be up and running to build your own systems!", - "Last Updated": "13 Jun, 2018", - "Prerequisites": "Must know a guy who owns a raspberry Pi", - "Section": "Embedded python", - "Speaker Info": "Hello World. I am Kartik Arora, founder at Akriya Technologies . Before starting my journey in the wild, I worked for Rivigo for a few months, and in Bing Team during my 2 years at Microsoft", - "Speaker Links": "https://twitter.com/karx_brb https://www.facebook.com/karx01 https://www.linkedin.com/in/karx01 https://github.com/kar", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kartik Arora (~kartik53)", - "created_on": "13 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/micropython-time-to-get-building~av58e/", - "title": "MicroPython : time to get building" - }, - "70": { - "Content URLs": "My python script", - "Description": "Information is being generated at an exponential rate everyday. There are multiple sources generating information. It becomes really tedious for a person to go and visit all the sources to obtain information. It could be of great help to the person if there can be a single source which cumulatively providing all the links of news generated by different newspapers. This is where web scraping and automation comes into picture. In this talk I want to explain how to scrape webpages hassle free , gather information and represent the gathered content in a easy to visualize format. By executing just a single Python file we can get all the data what we want from the web. Its not just about collecting the data, it is to reduce the repetitive work which a person does again and again to achieve the same goal. We can put repetitive work into a module and leave it upon the computer to do the same. This in turn will help us channelize our time more on the information rather than gathering that information. Agenda of Talk: Introduction: Web scraping, automation tools, parsing and scraping python libraries. How it helps in learning python extensively: My experience with web scraping and various use-cases on which I utilized. Q&A session.", - "Last Updated": "12 Jun, 2018", - "Prerequisites": " Basics of python", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking.", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/importance-of-webscraping-and-automation-using-powerful-python-libraries~er52d/", - "title": "Importance of webscraping and automation using powerful python libraries." - }, - "71": { - "Content URLs": "Will be updated on github before the conference", - "Description": " It is always essential to understand the genesis of evolution or the roots of revolution. Keeping in mind the above saying, in this workshop, I will provide a hands-on understanding of Blockchain technology using Python. There are multiple resources to get a firm understanding about this domain, but the best way to understand it is by using the concept of \"Learning-By-Doing\" . Following are few reasons why I want to willingly contribute to this domain: Blockchain is the underlying technology behind most of the\n cryptocurrencies and it has a potential of changing the way we work\n and communicate, making it more secure, efficient, and trustworthy. There is a immense amount of speculation going around in this domain\n with the rise of Bitcoin. What\u2019s happening with blockchain\n technology, I would say, is similar to the great American gold rush\n that happened in the mid 1800s. Innovators, investors, entrepreneurs, technologists all are hovering\n over the same underlying idea on how these cryptocurrencies work and\n how could blockchain be leveraged to create use-cases beyond\n crypto-systems. Also, I would love to mention few quotes to support the escalating phenomenon of Blockchain : The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping\neverything along its way by the force of its progression. -- William\nMougayar Over the next decade, there will be disruption as significant as the Internet was for publishing, where blockchain is going to disrupt\ndozens of industries, one being capital markets and Wall Street. -- Patrick M. Byrne I will help people in understanding the bits and bytes of this domain, including the basic cryptography concepts, algorithms and how to utilize the power of Python language to build their own blockchain. As we progress, we would engage into more advanced concepts pertaining to scalability and deployment once we build a minimalist prototype of aforementioned. Using on-the-go learning while developing will serve as a pivotal entry point for all the people who are willing to enter into this space and planning to build smart-contracts or invest in cryptocurrencies. Agenda for workshop : Introduction to Blockchain: Existing problems, what is Blockchain, why it matters, gist of few use-cases, related concepts. Python revisited: Functions, libraries, object-oriented programming terminologies, basic data structures, basics of zen of python. Blockchain under the hood: Cryptography 101, underlying data structure and algorithms, conceptual terminologies. Python and Blockchain amalgamated: Create blockchain using python. User-friendly front-end: Integrating the scripts in previous section with a basic front-end. Discussion regarding scalability methods and resources. Generating self-help focused Pypi library called pymyblockchain . (optional) Q&A session. Note: The above agenda is subject to change. It is tentative for now. Any changes will be updated here itself", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basic python: Functions , Classes and Objects , Use of Libraries *No prerequisites apart from aforementioned. Even a person who is new to python will be able to grasp everything in workshop", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchain-by-implementing-it-from-scratch-in-python~bq57b/", - "title": "Understanding blockchain by implementing it from scratch in Python" - }, - "72": { - "Content URLs": "https://www.tensorflow.org/ https://github.com/aymericdamien/TensorFlow-Example", - "Description": "Hey everybody!\nIf you have ever heard of this thing called as neural network , than this workshop is definitely for you .Neural networks are not new they been there for a long time . but they have become quite famous recently\ntensorflow is consisdered one of the best frameworks for getting started with neural networks and deep learning . About TensorFlow TensorFlow\u2122 is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google\u2019s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. We will also try and build an image recognition model using deep learning from scratch . Tensorlfow helps getting started with deep leaning and building neural networks ", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basics of python and an open mind to learn new things ", - "Section": "Data science", - "Speaker Info": "Python lover . Machine learning enthusiast . Currently working on BIG ML ( training machine learning models on big data ) and efficient deployment of machine learning models on production ", - "Speaker Links": "Contributor at https://github.com/polyaxon/polyaxo", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-build-neural-networks-from-scratch-using-tensorflow~boKYb/", - "title": "Learning to build Neural networks from scratch using tensorflow" - }, - "73": { - "Content URLs": "Any related material will be shared soo", - "Description": "Financial data is difficult. It is sensitive to many unknown factors. So we need a good strategy for trading with deep learning. That's where reinforcement leaning comes in. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over.\nBy the end of the talk, you will learn:- What trading is? Why it's hard? How Can Deep Learning solve the trading problem? Why is reinforcement learning an effective solution?", - "Last Updated": "11 Jun, 2018", - "Prerequisites": " Willingness to learn Basic python", - "Section": "Data science", - "Speaker Info": "I have always been amazed by computers and how much you can do with soo little. Curiosity lead to passion. Passion lead me to work on some amazing things. AI is the buzzword around and I have been working on AI for quite some time and it's been a really great journey, challenging but rewarding. Recently, I started working with some startups. Currently, I'm working for a Silicon Valley startup, who has been working on making serious predictions on small data. I have also been interested in Fintech data. I started with simple fraud detection models and now I'm working on solving the trading problem with reinforcement learning", - "Speaker Links": "Connect on Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Himanshu Singh (~himanshu61)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-trade-with-reinforcement-learning~enX5b/", - "title": "Learning to Trade with Reinforcement Learning" - }, - "74": { - "Content URLs": "Will be uploading soon !", - "Description": "My philosophy has been : If you haven't build it you don't know it. So lets build a hadoop clone and see how it works . This workshop is basically about building your distributed processing system . It will take you through some basics of distributed system and we will try and build our very own distributed system in python ", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Google \"what is hadoop\" Google \"what is a distributed system", - "Section": "Networking and Security", - "Speaker Info": "class Pankesh (human)", - "Speaker Links": "class Pankesh (Human): def __init__ ( python=\"Python3\" ) :\n\n super.name = \"Pankesh gupta\"\n\n super.age = 25\n\n curiosity = True\n\n experience = 2\n\n education = \"Thapar University , Patiala", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lets-build-a-hadoop-clone-in-python~bm6Rd/", - "title": "Lets Build a Hadoop clone in python !!" - }, - "75": { - "Content URLs": "-> How does a web framework work -> WSGI basics -> Getting hands dirty with coding More information will be uploaded soo", - "Description": "Build your own web framework using python .\nLets unleash the power of python by building a web framework from scratch . \nIt will help you understand what actually happens under the hood in most famous web framework", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Web development basics\nCuriosity\nTrust in python :", - "Section": "Web development", - "Speaker Info": "Not so useful BTech ( biotechnology ) from Thapar University\n2 years of experience working in pytho", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-our-own-web-framework-like-flask-in-python-from-scratch~el0je/", - "title": "Building our own web framework like flask in python from scratch" - }, - "76": { - "Content URLs": " Will have own slides. Link will be shared with all This GitHub Repo contains some of the content that will be delivered during the course of the talk. A lot of other websites from where I pick a point or 2", - "Description": "Everyday we listen to this word \"DATA\".\nBut after listening to that word, some questions might pop up in your mind. WHAT IS DATA? WHY DOES ANYONE NEED TO WORK WITH DATA? HOW TO UTILISE AND WORK WITH THIS DATA? Data is now one of the most important things for any business to run. From small startups to large companies, everyone looks at data to improve their business.\nEveryone looks at data to increase their profits. Everyone looks at data to understand why they failed and where they failed. Everyone looks at data to understand how a product gained success in the market. Basically Data is everything today for companies. Data is available everywhere now and it's become more important than ever to actually work with data and luckily we have great modules to work with data in Python. I'll be focusing on these modules and the power that data possesses. My primary focus here would be about the power of data. I surely will be talking about how to use this data in Python to make the most out of it, but before that I'd like the entire crowd to know what the power of data is. This would be a good talk for beginners honestly. Even if you have no idea about how data could be used or what is data, after this talk, you'll get a decent idea about it. Through this talk the 3 questions mentioned above in bold will be answered. The talk would progress in the following manner : Self introduction (3 minutes) Introduction about the topic (2 minutes) What is data? (3 minutes) Where is this data? (2 minutes) How to make the most out of data? (3 minutes) How Python helps in this process? (2 mins) Name and explain about different Python modules like Pandas, Numpy, Matplotlib and Seaborn in brief (10 mins)", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "No prerequisites required. This talk will deal about everything from scratch and will give you a basic understanding of what modules could be used in Python. So you could research on those modules after the talk, but for the talk, no prerequisites required", - "Section": "Data science", - "Speaker Info": "Hey everyone, I'm Rahul Arulkumaran, a B.Tech 3rd year Student pursuing my major in Computer Science Engineering from Mahindra \u00c9cole Centrale, Hyderabad. I'm an open source and data science enthusiast. Coding is one thing I love doing all day and all night. Never feel like quitting.\nPython is my go to language. Anything I think of developing comes to life using Python. I have a very strong connection with Python as it was the first programming language I learnt. I'm also a full stack developer and perform data science on various datasets. I'm a Contributing and Managing Member in the PSF. I also am the President of the Computer Science Club in my college. Apart from that, I head the website development team for TEDxMahindra\u00c9coleCentrale and the Marketing and Promotions team for Aether (the techno cultural fest of MEC). I'm the Co-Founder and CEO of a startup which goes by the name FreeFlo. It is a product based company that looks at developing products related to Machine Learning, Blockchain and other related fields. I'm also currently interning in IIIT-Hyderabad in the Machine Translations and NLP Lab in the field of sentiment analysis. It might seem although I'm not interested in the non tech aspects of businesses, but I actually love working in teams related to business development and marketing. So that's mostly about it. Looking forward to interact with all of you out there ", - "Speaker Links": " GitHub My Blog Facebook LinkedIn Twitter Telegram Gmail ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/power-of-data-and-working-with-it-using-python~bkgJb/", - "title": "Power of Data and Working with it using Python" - }, - "77": { - "Content URLs": "Will be updated soon", - "Description": "Fog and haze (referred to as the atmospheric light) are the main cause of distortions, degradation in the quality of images clicked during foggy situations. But with the advancement in technology, thanks to Python and OpenCV libraries and brilliant minds of people out here in this small world, recovering almost a fog-free image has been made possible in recent times. And now we are moving towards making this algorithm more optimized so that it can work in real time for videos and live camera feed. Different mathematical models have been presented over the time for this algorithm but there are very few real-life implementations in any particular programming language, so here the Python implementation of this algorithm will be discussed. Basic steps and the ideas implemented will be discussed in a brief and different implementation will also be shown in the session", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of the numpy functions. An idea about the OpenCV computer vision libraries and the different filters implemented there. Love for Python", - "Section": "Developer tools and Automation", - "Speaker Info": "Speaker: Vivek Modi Final Year undergrad at NIT Durgapur Tech Head at GNU/LINUX USERS' GROUP NIT Durgapur Summer Intern at DRDO (Integrated Test Range) Contributor in the project: Soumam Banerjee Final Year undergrad at NIT Durgapur", - "Speaker Links": "modiher", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vivek Modi (~modihere)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-and-opencv-for-removing-fog-and-haze-from-an-image~ejBye/", - "title": "Using Python and OpenCV for removing Fog and Haze from an Image" - }, - "78": { - "Content URLs": " http://github.com/vaideesg/omsdk http://github.com/dell/omsdk", - "Description": "Abstract Ever wonder creating your own super-type-manager leveraging the python's own type constructs? Ever explored alternatives to APIs for integration? In this talk, we will cover our experience in building a new type manager (as part of developing open source OpenManage(tm) Software Development Kit) leveraging pythons own type constructs and explore how this new type manager provides a credible alternative to APIs, especially in those information-heavy environments like Device Management. Description Devices (like Servers, Switches, Telecom Switches) are data-intensive systems. Their information model is so intensive, that practically all operations (health, inventory, metrics, configuration) on the device ends up in primarily as CRUD operations on the information model they expose. Only a paltry few operations are exposed as APIs. When building an API for managing these devices, we realized that providing classic function-style APIs only degraded the user experience. What we realized was there was significant information available on the Servers, and providing an API for exposing traditional CRUD (Create, Retrieve, Update and Delete) for all information nuggets was just exploding the API sets. It was not necessarily covering all the scenarios that could be possible for management and did not seem to scale. Our approach was to take this information model within the devices and expose them as a huge navigable data structure representing the entire spectrum of the device and provide a language native experience. We created a new type manager leveraging the python class special operators ( getattr (), setattr (), le () etc.) to create a whole new type manager that provides additional controls and safeguards. Some of the safeguards include: Not allowing edits to read-only components Allowing only applicable changes only (ranges, enumerations) Providing native python experience for special types (IP Address Types etc.) Providing mechanisms to validate cross-attribute validations Providing custom indices for arrays (like Virtual Disks, Users) Providing mechanism for tracking changes to configuration Apply changes to the device optimally Provide mechanisms for identifying configuration drifts Outline : Outline of the presentation: Introduction Device Configuration - Aspects & Peculiarities Pitfalls of API approach for Device Configuration Type Manager - introduction Super Types - Enumerations, Fields, Classes and Arrays Bringing in Native Type Experience Data as API - Enriched user experience Demo Q&A Key takeways to audience Audience will get an exposure: How to create your own type manager by overloading python type constructs Exposure to alternative approach to creating APIs for data-heavy systems & explore benefits Learn how type manager simplifies your life as well as the life of your consumers. Secrets of the python inbuilt __ operators - and how you can leverage them to provide native type experience even for your own custom classes How you can create a better user experience for customers in a simple way How you can incorporate Object Oriented SOLID principles", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " General familiarity with type concepts (fields, arrays, classes, enums) is needed Exposure to in-built operators like ( getattr etc. will help) Exposure to Systems Management would be useful.", - "Section": "Core python and Standard library", - "Speaker Info": "Vaideeswaran Ganesan, Senior Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and data center products. His passion is compiler design, analytics, systems management, networking protocols and automation. Ajaya Senapati, Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and storage products", - "Speaker Links": "Vaideeswaran Ganesan\n 1. My Github Repository 2. My Linkedin Article which I wrote while implementing this Fun with Python Code Generation Ajaya Senapati\n1. Lin", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Vaideeswaran Ganesan (~vaideeswaran)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-as-api-building-a-type-manager-with-python~egyrb/", - "title": "Data as API: Building a Type Manager with Python" - }, - "79": { - "Content URLs": "Any related material will be shared soo", - "Description": "Natural language processing(NLP) is a branch of artificial intelligence concerned with automated interpretation and generation of human language. From keyword search to Virtual Assistants, from spell checkers to language translators and from sentiment analysers to Chat bots, NLP finds its applications in most of our day to day applications.\nThis workshop aims at delivering a basic Hands on tutorial to get started with NLP in Python. It commences with an introduction to NLP, discussion on various applications and a linguistic breakdown of Language (English). By the end of this workshop you will be able to : Install relevant packages such as nltk, gensim and pattern . Applying text processing techniques such as Tokenization, Stemming, Lemmatization and Chunking . Forming a Document Term Matrix using Bag of Words Model . Building a simple Spam/Ham classifier using Bag of Words Model . Generating Word Vectors using Gensim Word2Vec module. Building a Sentiment Analyzer . This workshop provides preliminary insight and a simple explanation to enthusiasts who wish to explore the field of Natural Language Processing.\nIt enables you to talk to your computer!", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of Python. Any knowledge of Python modules such as Numpy, Pandas etc. is and add on.", - "Section": "Data science", - "Speaker Info": "Hello, I am Osheen Nayak, working as a Software Engineer at Texas Instruments Bangalore. I belong to Delhi Technological University batch of 2017.\nI am a Machine learning and Data Science enthusiast and I have been actively driving various Machine Learning activities. I have delivered few talks on Machine Learning in the past one of them including \"A primer on Machine Learning and Artificial Intelligence\" in the IEEE forum to and audience of 50 people. I am an avid football fan and also an amateur player.Also, I like to play video games, cricket and chess", - "Speaker Links": "Connect on LinkedIn : https://www.linkedin.com/in/osheen-nayak-31022a10b", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "osheen nayak (~osheen)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-talk-to-your-computer-a-101-on-natural-language-processing-with-python~e0M5a/", - "title": "How to talk to your computer - A 101 on Natural Language Processing with Python" - }, - "80": { - "Content URLs": "Slides TBD Code repository TB", - "Description": "Abstract Today, massive systems are running on microservices communicating with each other using REST APIs. HTTP is easy to get started, loosely structured and does good job in exchanging messages. But it's convenience comes with a performance trade-off, which takes us back to other optimal alternative: gRPC Description In this talk we will see what gRPC is and how it is different from REST. We will get started with GRPC by generating stubs for python and \nbuild a simple gRPC API server. We will try to find out the advantages of gRPC over REST by doing a side by side comparison of our APIs. We then deploy our server in Kubernetes and discuss how we could scale our microservices. Outline Introduction to gRPC (3 min) gRPC concepts (5 min) Designing the APIs REST-fully (3 min) Going the gRPC way (5 min) Generating python stubs Duel: gRPC vs REST python servers (4 min) Demo (4 min) Deploying our gRPC apis in kubernetes Summary (3 min) Q & A (3 min) Key take aways to audience Audience will get a practical introduction to gRPC and protocol buffers. Now the audience will know an alternative to HTTP/REST. This allows them to design better microservices\nbased on their use cases. Bonus: Deploying and scaling python microservices in Kubernetes. Links Companies using gRPC in production Protocol buffers ", - "Last Updated": "09 Jun, 2018", - "Prerequisites": "This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners", - "Section": "Web development", - "Speaker Info": "Naren is a Product Engineer with specific focus on building robust backend systems. Past 5 years, he has built dozens of microservices and scalable systems using Python, Go and AWS cloud. He is an open source enthusiast who loves speaking at tech conferences and currently works as Senior Software Consultant at Tarka Labs. In his industry experience he\u2019s worn plenty of hats- like the one of a Trainer, Embedded Engineer, Product Engineer and Consultant and sometimes even helmets- while he\u2019s out cycling.\nWhen he\u2019s not stirring up code, you can find him whipping up a delicious gluten-free treat or training for cycling races.\nHe also blogs about software, productivity and goes by the handle DudeWhoCode across the internet", - "Speaker Links": "Past 5 years I have been architecting and building scalable backend systems using Python. I have built a dozen of microservices at scale. Recently I built a production infrastructure in Python that handles 20+ millions of API calls per day. At one point of time, I realised I should know some alternatives other than REST to communicate between the microservices. Out of curiosity I explored and used gRPC in few of my microservices. Since then, I wanted to share the knowledge so that developers will get to know other options while architecting their infrastructure. This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners. I have spoken in various conferences, my recent one was PyCon Singapore 2018. Below are some of my previous talks and speaker portfolio: Speaker Portfolio Featured talk 1 Featured talk 2 Featured talk 3 portfolio blog Github", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Narendran R (~narendran)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-better-python-microservices-using-grpc~e9jJa/", - "title": "Building better Python microservices using GRPC" - }, - "81": { - "Content URLs": "I will upload slides soon", - "Description": "Object-Relational Mapper (ORM) is one of the powerful feature of Django. It allows us to interact with database without writing long complex SQL queries. The contents that will be covered in the discussion are as follows. Introduction to ORM, How it works ? What is queryset ? how it works ? Explaining use of values, values_list, only and defer to run ORM query efficiently How to use select_related and prefetch_related to optimize queries Some examples to show, how to query very complex data using only ORM What not to do while using ORM to avoid slow performance", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic knowledge of Python and Python web framework (Django) Some experience in quering relational databases", - "Section": "Web development", - "Speaker Info": "My name is Hiren Patel. I am working at Aubergine solutions pvt ltd and I have been doing full stack web development there from last 2.5 years. While working on some web projects, I have always focused on learning django in more detail and try to optimize APIs to return response faster", - "Speaker Links": " Github: https://github.com/hirenalken LinkedIn: https://www.linkedin.com/in/hiren-patel-046672ab/ StackOverFlow: https://stackoverflow.com/users/3553279/hiren-patel?tab=profile Medium: https://medium.com/@hirenpatel_38103 I had presented a talk on this same topic in meetup organised by Ahmedabad based meetup group. here is the link to meetup: lin", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Hiren Patel (~hirenalken)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/efficient-use-of-django-orm~b8gja/", - "title": "Efficient use of Django ORM" - }, - "82": { - "Description": "This workshop is dedicated to discuss and extrapolate on the core of Object Oriented Programming its finer details and nuances. The objective of the talk is to introduce concepts that will ensure OOP becomes second nature to a programmer. What you will gain after this session Detailed overview of Object Oriented Programming Intuition on the finer nuances of Object Oriented Programming. Tips on keeping the OOP code clean and readable. Expanding your horizon by understanding some lesser known concepts in Python. The session will focus on the following aspects with examples Inheritance and everything about it. Method Resolution Order Method Types Custom Base Object, Collections, and Dict Objects Extending Built-in Types Data Models Meta Classes and where they help Decorator and Class Decorators. Factory Design pattern Singleton Things to remember while writing code Conclusion", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic Python syntax Some understanding of Object Oriented Programming", - "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-object-oriented-programming~e7MQb/", - "title": "Advanced Object Oriented Programming" - }, - "83": { - "Content URLs": "Will be sharing soon", - "Description": "Your introduction to concurrent programming in python. This talk is dedicated to a developer to enable him/her get started in asynchronous programming. The contents that will be covered in the discussion are as follows. What is asyncio? Why should we bother? Multi Threading vs Multiprocessing vs asyncio understanding the differences. All about what an event loop is with examples Futures Tasks and coroutines Streams Multiple Coroutines. Scheduling Calls Synchronization primitives Queues Working Example with a few notes on sockets and summary. The talk provides preliminary insight and a simple explanation to programmers who wish to explore asyncio and/or concurrent programming. ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Basic understanding of python syntax. Some OS concepts like differences b/w multiprocessing and multithreading. Understanding UNIX (not mandatory).", - "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-asyncio~b6MOa/", - "title": "Introduction to Asyncio" - }, - "84": { - "Content URLs": "Part 1 Part 2 Github Rep", - "Description": "Websites and blogs have become a common trend amongst professionals to display not just their resumes but also their daily work items. Static blog generators have gained popularity over the last few years . People who have been using Wordpress, Blogspot or Blogger are now shifting to Pelican , Jekyll etc. One major annoyance was that Wordpress had a huge attack surface. Everytime someone found out a Wordpress exploit, your site was at risk. When comparing Blogger vs Pelican, the Slant community recommends Pelican for most people. In the question \u201cWhat are the best solutions for a personal blog?\u201d Pelican is ranked 10th while Blogger is ranked 14th. Python is becoming more and more popular amongst programmers and so is Pelican . \nPelican is a static blog generator and supports several formats like Markdown , ASCII etc . It turns Markdown and some Jinja templates into the Full Stack Python site. Its beauty lies in its simplicity and even a non programmer can get started with Pelican in just a few lines of code and plain text . Over the past few years people have shifted from Wordpress to Pelican .This is because a static site has basically no attack surface, and can be hosted on free or inexpensive hosts like Github Pages .\nThis talk is focused on introducing a simple static site generator to beginners and even avid bloggers who aren't coders . This talk will cover:- Basic installation of Pelican Writing a blog post with Pelican Changing themes of a blog/site Comparison between Jekyll and Pelican The main aim of this talk is to familiarize people with the concept of edifice . I have met a lot of non coders who have asked me about creating a basic website for personal use . This talk is also targeted to all those you are interested in blogging and everyone out there has something to say and something to blog ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "Absolutely nothing ", - "Section": "Web development", - "Speaker Info": "Anumeha Agrawal is a Pythonista and an open source enthusiast . She is in her third year of undergraduate program in Information Technology at NITK Surathkal . She is also a Google Summer of Code 2018 student at Systers . In her project at Systers , she has used python to write scripts to retrieve data from GitHub API and use it in her MEAN stack project . She uses python scripts to simplify most of her work like API data collection and web scraping . Python was the first language she was introduced to when she began programming and it is her weapon of choice . Owing to the simplicity of python syntax, she also used python to code her algorithms for her talks and workshops at college . Apart from being a full stack developer ,she is also a Data science enthusiast and employs python for designing most of her Deep Learning models and algorithms ", - "Speaker Links": "Link to Github Link to Linkedin Profile Link to Medium Blog Link to GSoC projec", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anumeha Agrawal (~anumeha)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pelican-magic-for-beginner-bloggers~e5MYe/", - "title": "Pelican - Magic for beginner bloggers" - }, - "85": { - "Content URLs": "http://click.pocoo.org (Cool power-point and Github repo coming up", - "Description": "Who hasn't used Git in the terminal? An absolute beast of a tool. But did you ever have an idea to build your own cool Command Line tool for something you believed could simplify life for other devs but you didn't because you were too lazy to research? Worry not! I present to you Click! Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It\u2019s the \u201cCommand Line Interface Creation Kit\u201d . It\u2019s highly configurable but comes with sensible defaults out of the box. In this talk, I'll go through the process of designing a simple (or complex) Command Line Interface called thanos which tells you whether you survived the SNAP or not. I'll be taking you through the process of designing, building and publishing our thanos package. We'll then upload it to the Python Package index so that you can do pip install thanos from any system worldwide and find out if you perished or not. Outline What is a CLI ? Building our own CLI called Thanos , to find out whether you survived the snap or not. >>thanos snap\n You didn't make the snap. Creating complex commands using beautifully decorated code. Exploring arguments, flags and options within the CLI. What's PyPI, and why do we need it? Uploading your new Thanos package to Python Package Index. QA", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Should have seen or used a terminal before. (Mandatory) Basic Python knowledge preferred.", - "Section": "Developer tools and Automation", - "Speaker Info": " Adarsh is a visionary who strives to build amazing tools for people. He is currently pursuing bachelors in CSE. Currently he is Google Summer of Code Intern at CloudCV , an organisation which works on making reproducible AI research, where he is building a versatile CLI for EvalAI project. He was one of the youngest speakers at FOSSASIA International Summit 2018 in Singapore for his work on Python based NLP POSTagger. Worships Open Source software and have contributed to multiple organisations like FOSSASIA, Zulip where he was also a mentor for Google Code-In 2016 .", - "Speaker Links": "https://www.youtube.com/watch?v=TzIr9THCUJg https://2018.fossasia.org/event/schedule.html#s-4267 https://github.com/isht3/ https://www.linkedin.com/in/guyandtheworld", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "isht3", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-your-own-command-line-application-and-upload-it-to-pypi~b427e/", - "title": "Build your own Command Line Application and upload it to PyPI!" - }, - "86": { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "In today's Era, the IT sector is moving more and more towards automation. Now every company is trying to provide its users with the facility to perform their task without the need for any human intervention.\nIn this talk, we are addressing a similar problem of automating the vehicle parking systems. Problem description: Automated license plate recognition(ALPR) is a well-known problem where we try to extract the license number from a cars number plate using machine learning algorithms. The scope of its real-world application ranges from highway toll plaza to automated parking and charging of future electric cars.\nThis problem has been targeted with a variety of algorithms like traditional template matching to advance deep learning algorithms like YOLO . Here we will be presenting a combination of little template matching clubbed with some deep learning to solve this problem in the most simplistic way", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations", - "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saqhas", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-license-number-recognition-in-python~e33Ae/", - "title": "Automated License number recognition in python" - }, - "87": { - "Content URLs": "Would update soon after feedback", - "Description": "Most machine learning algorithms require feature vectors as inputs. In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object (image, text, sound). Feature engineering, the practice of extraction of features from objects is a combination of art and science; it requires the experimentation of multiple possibilities and automated techniques with the intuition and knowledge of the domain expert. Automating this process is called \"feature learning,\" where a machine learns the features itself. One way to obtain features is to use the 'Bag-of-Features' model, the idea behind which is to simplify object representation as a collection of its subparts. Originally used for representing text data, the \"Bag-of-Words\" methodology can be extended to different types of objects resulting in models such as \"Bag-of-Visual-Words,\" \"Bag-of-Audio-Words.\" The significance of these models in the age of self-learning deep networks still holds because of their ability to work with limited data. The contents of the talk are: Introduction to Feature Engineering Working with Text Data Understanding 'Bag-of-Words' Example: Text Classification Working with Image Data Introduction to 'Bag-of-Visual-Words' Example: Image Classification Comparing the performance to CNN Overview of 'Bag-of-Audio-Words' Generalizing 'Bag-of-Features' This talk primarily discusses Bag-of-Words, Bag-of-Visual-Words through an example of text classification and image classification respectively. It also covers the concepts that generalize to models other than Bag-of-Features. The goal is to acquaint the audience who have previously worked on numeric data with some ideas to get started with text and multimedia data", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Intermediate knowledge of Python Familiarity with classification problems Familiarity with basic NLP/CV is helpful (but not necessary)", - "Section": "Data science", - "Speaker Info": "I'm a fresh graduate in Computer Science & Engineering. I am passionate about Data Science, and I spent most of my time learning about skills required to excel in the domain. Outside of my professional interests, I am fond of rock music and reading", - "Speaker Links": " Blog: https://pranavsuri.com GitHub: https://github.com/pranavsuri LinkedIn: https://linkedin.com/in/suripranav Twitter: https://twitter.com/pranav_suri", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pranav Suri (~pranavsuri)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bag-of-features-representing-text-image-data-as-numerical-vectors~b2XMe/", - "title": "Bag-of-Features: Representing Text & Image Data as Numerical Vectors" - }, - "88": { - "Content URLs": "https://github.com/Laneone/askfm-pytho", - "Description": "Hey everybody! Ever tried to webscrape? Ever faced a \"No robots allowed! No web scraping allowed!\" message from a favorite site? This talk is for meant for you. Usually when you're done building a fancy web scraper and begin running the homebrew'd tool on your favorite site there's chances you'll face a block on your IP address preventing your computer from accessing more resources and therefore downloading the contents of the website. Your tool maybe fast, it might be scalable, it might be the best written scraper out there, but with just one IP address under your belt, it's easy for giants to block your ip address and prevent you from getting that precious data, especially if you've built a threadsafe and multi-node webscraper. Enter The Onion Router, The ToR project, allows you to use the the internet vis-a-vis a proxy and visit the same website under a different endpoint ip address, but that's just for one instance of ToR. What if you ran, say 200? at once? 200 ip addresses > 1 ip address. With 200 endpoints and the latest update to the requests library, you can now use your multi-threaded and resource hungry webscraper and it can(not) be stopped! Whatever your rate of data collection, you can 200x it! The stack is simple, you open a SOCKS5 proxy per ToR endpoint, connect it to a request with it's own port number and you're good for that one request, same for multiple requests. You can build a task scheduler to orchestrate the url to scrape and the port number the tor endpoint is on and have the entire application running on a cloud service provider to ensure you face no bandwidth issues. The demo centered around the talk will attempt to rapidly and quickly scrape users from the famous social network Ask.fm which is known to restrict users from retreiving from their site if you attempt to download more than 4 users in under a second, but with the hack in place, you'll be retrieving close to maximum efficiency on a DigitalOcean droplet , but this can be applied to virtually any website and any cloud provider. Never pay for webscraping again! Thanks and see you at PyCon! \n-Lokesh Poovaraga", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic concepts of web scraping, Regex, Task scheduler, ports and proxies", - "Section": "Developer tools and Automation", - "Speaker Info": "Hi I'm Loki! (Lokesh Poovaragan) A full-stack developer from Dayananda Sagar, Bangalore, and I love to code in python! In my free time I love to web scrape and gather good amounts of public data and encompass them into json format for data(sentiment) analysis. I also build prototypes of interesting combinations of technology to solve unique problem statements. I love exploring new and interesting areas of work and I love to play with code", - "Speaker Links": "Blog: http://laneoneblog.blogspot.in GitHub: http://github.com/Laneon", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Laneone (~Laneone)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-intermediates-guide-to-theoretically-unlimited-webscraping-with-python-using-requests-lxml-tor~e1MZe/", - "title": "A Intermediate's Guide to (theoretically unlimited) WebScraping with Python using Requests & lxml & ToR" - }, - "89": { - "Content URLs": "This one is the essence of it but closed source and in java: https://lifehacker.com/how-to-build-your-own-amazon-echo-with-a-raspberry-pi-1787726931", - "Description": "Voice is the new touch. It's not going to be too long before the likes of Alexa or Google Home take over our day to day life like the Internet and the mobile phones have. There are countless tutorials on how to hook up a home automation system using a Raspberry Pi like here and here . Pair that up with voice capabilities and you can basically tell your lights to turn themselves off or the TV to change the channel. In this talk I'll cover the following: Hook up a microphone to a raspberry pi and be able to capture wav files on python. Use an online API like Google's Speech API to convert the wav to text. Give a background on what intents and entities (slots) are. Installing open source software like Snips Encoding our intents and example sentences and training the open sources software Calling a functions to do particular activities At the end there'll be a cool demo", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of what a Raspberry Pi and Python is. And maybe played with an Alexa, Siri or Google Home. Yup, low barrier of entry", - "Section": "Embedded python", - "Speaker Info": "I am Ved. I have a masters in Computer Science/Data Science from IIIT-Bangalore and I work on NLP/Linguistics at Slang Labs. My goal in life is to sit down and have a conversation with a computer at a bar coffee shop. Maybe we won't get there soon, but at least maybe I can make it reserve my seat for me", - "Speaker Links": " vedmathai.com https://github.com/vedmathai/ https://www.linkedin.com/in/vedmathai/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ved Mathai (~ved47)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/create-a-voice-conversational-agent-for-your-raspberry-pi-home-automation-system~eZgQa/", - "title": "Create a voice conversational agent for your raspberry pi home automation system" - }, - "90": { - "Content URLs": "Shall be updated soon", - "Description": "Here, We will talk about how you can make a bot to help you automate your life and make your very personal Assistant, and maybe you will end up making something better than Google Assistant or Siri. We will be using modules to perform a task, so you can keep making them as you go and your assistance will keep becoming more powerful and yes all this will be done in python. In this talk: - We will start with setting up project creating simple python GUI. - Making some modules to perform a simple task. ~ Composing email with speach ~ Some other cool modules - Explaining what else we can achieve with this. ~ Let's make, its personality using tensorflow for talking stuff - Showing my work and explaining how it works Here, Is in early development phase Then we will end with some questions and how they can continue with this project", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic Understanding of Python", - "Section": "Developer tools and Automation", - "Speaker Info": "He is a student, a self-taught programmer loves to dig deep and know more about the computers. Fell in love with python and now loves to Automated things with python. He is GSoC aspirant. He is an active volunteer at PyDelhi and ALiAS . When he is not automating things he loves to contribute to open-source and closing issues", - "Speaker Links": "Website: omkar.site Github: @omi1085", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "omkar yadav (~omkar10)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/superpybot-your-personal-assistant~bYZAd/", - "title": "SuperPyBot: Your Personal Assistant" - }, - "91": { - "Content URLs": "https://www.artima.com/weblogs/viewpost.jsp?thread=214235 http://www.dabeaz.com/python/GIL.pdf -slides tb", - "Description": "Python is an amazing language, known for its vast standard library and use in rapid prototyping. When we were trying to build a robotics system that is primarily modular and upgradeable, we ended up using Python to power the brain of the project. In this talk, we'll discuss how we designed the event loop, responsible for controlling the mechanical actions and state of a robot snake. Animating multiple motors concurrently at different speeds to different positions. Foreground and background tasks. Interrupting ongoing tasks. We will discuss best practices when performing asynchronous actions in Python, and how to ensure actions are completed within a bounded time.\nFinally we touch one of the lesser known 'features' of Python, the Global Interpreter Lock. GIL is a mutex that protects access to Python objects, preventing multiple threads from executing at once. Two threads calling a function may take twice as much time as a single thread calling the function twice. We'll discuss some of the real world implications of the GIL, along with some considerations that must be taken while writing highly synchronous Python code", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Knowledge of common Python syntax would be great", - "Section": "Core python and Standard library", - "Speaker Info": "Hi, I'm Pranith, a final year undergrad student at NMIT, Bangalore. I'm a robotics enthusiast with a passion for cypherpunk, virtual reality, and generally, the future. Apart from the usual frameworks, I've used Python across the field, ranging from web technologies implemented on raw CGI to microPython on the ESP8266. I try to apply Python in odd ways to bridge various layers of the stack, and as a result have a fair amount of experience breaking it", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pranith Hengavalli (~prnthh)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/robot-snakes-and-the-global-interpreter-lock~eXPve/", - "title": "Robot Snakes and the Global Interpreter Lock" - }, - "92": { - "Content URLs": "Slides : Coming soo", - "Description": "Large Python codebases can be hard to maintain. If we make it easier to understand our code bases, we make everyone more productive and help each other write fewer bugs. Static typing is one of remedies that can improve readability and maintainability of the code. That's why Python now features optional static typing as described in PEP-484 , implemented as Mypy . Mypy is an experimental variant of Python that let's you add optional type annotations to type check your Python code. And it works great on both Python 2.7 and 3.3+. Adopting static typing is easier that you think, you can start on a small set of code and move on to bigger pieces. In this talk I'll share about, PEP-484 and Introduction of type annotations in Python 3.5 Use cases of Mypy and how to use it with Python 2 and 3 Project typeshed and how to leverage it Lessons I learned by type hinting the project Twine We\u2019ll also discuss how to make it a seamless part of your project; what order to approach things in; and some powerful new packages that make it even easier today to add static types to your Python codebase than ever before", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of Python Difference between dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Wasim is a Senior Software Engineer at Zemoso Labs, Hyderabad. He's an open source fanatic who loves to create meaningful software and contribute to open source projects. Some of his contributions are included in projects like Sendgrid, Warehouse, Twine and Hazelcast. Apart from programming he also tweets . You can find him interesting on his GitHub profile ", - "Speaker Links": "Article on Medium about Mypy Open source contributions can be found at my GitHub profile ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Wasim Thabraze (~waseem18)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mypy-optional-static-typing-for-python~bW1Ee/", - "title": "Mypy: Optional Static Typing for Python" - }, - "93": { - "Description": "In Data Science, Garbage In = Garbage Out. Feature engineering is one of most of the important yet most neglected step in life cycle of Machine learning projects. Kaggle competitions have showed us that top Kagglers spend more than half of their time in feature engineering. Through various experiments, its also proved again & again that better features with simple model triumphs even advance models. In this talk I am planning to discuss basic as well advance feature engineering techniques which can be used by everyone in their projects Outline What is Feature Engineering ? Techniques for Numerical Variables Techniques for Categorical Variables Techniques for Textual data Advance techniques Feature Selection & Dimensionality reduction QA", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic knowledge of Python & Machine learning", - "Section": "Data science", - "Speaker Info": " Sudarshan Gadhave is a Data Science ,Data Engineering & Data\n Integration professional with over 8 years of experience working on\n Machine Learning , Data Engineering , Data Visualization and Data\n Warehousing Projects. Currently he is working as a Specialist Data Scientist in Analytics R&D team of\n Nice Actimize ( Nice Systems) working on developing Anomaly & Fraud detection models. Earlier experience of working in Advance Analytics & Data Warehousing\n teams of NEC, Japan & John Deere (Deere & Company). Pythonista & expert in Python Machine learning stack (Numpy,Pandas,\n Scikit-Learn, Matplotlib) Active & Core member of Python Pune meetup group.Presented several\n talks on Python & machine learning in meetups, conferences and\n colleges all over Pune.", - "Speaker Links": " Github:- https://github.com/sudarshan1413 Linkedin:- https://www.linkedin.com/in/sudarshan-gadhave-73567b23/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "sudarshan1413", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/art-of-feature-engineering-for-machine-learning~eVWza/", - "title": "Art of Feature Engineering for Machine Learning" - }, - "94": { - "Content URLs": "A few topics I will be covering, I would not be covering everything in detail, but hope to highlight important aspects from these links over the talk session: http://openmusictheory.com/ https://in-thread.sonic-pi.net/ https://github.com/gkvoelkl/python-sonic http://www.daveconservatoire.org/course/introduction-to-sonic-pi By the end of this talk, I aim to instil a much better idea about Live Coding and Programming Musi", - "Description": "Sonic Pi: An open-source live coding platform developed by Dr Sam Aaron aims to explore and teach programming concepts based primarily on the process of creating new sound.\nWe will venture deeper into the live coding platform and produced different genres/styles on music while coding live and dwell further into performing algorithmic music on a wider scale. I have tinkered with different styles of tones and sounds in sonic-pi and Python and re-created a rendition of popular 21st century music, only through algorithmic-generation, and seek to promote appreciation about open-source software such as sonic-pi and aim to demonstrate it's applications, along with the use of Python over the course of a thirty minute-talk and demo, in the rendition of producing Algorithmic-Music Live , during the course of the talk. By the end of the session, I aim to establish a better understanding of Live-coding, Programming Music and Intelligent-dance music Artists such as Aphex Twin. The flow of the talk will be as follows: Self Introduction Introduction to Music-theory and Sound Generation Introduction to Live Coding and Python-sonic Understanding the algorithmic workflow Diving beyond: Guitars, drums and Piano Produce an algorithmic-track! End of talk Q&A Session We shall also fiddle with a physical midi-controller if we find time, and demonstrate various interesting forms and styles of music; \nWe will also be producing a popular 21st century track from scratch ", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " A curiosity for algorithmically-produced music, Python and open-source software. Basic Music theory knowledge is appreciated, but anything relevant will be covered during the talk.", - "Section": "Others", - "Speaker Info": "My name is Sushen Kumar. I am a currently pursuing a Bachelor of Engineering in Computer Science at Sir M Visvesvaraya Institute Of Technology, Bangalore. Over the course of my academia I have dabbled into a few open-source projects, as well as contributed to open-source organisations on GitHub: Attended several hackathons around India: (Winner-ValuePitch Hack, Runners' up- IESA Makeathon) Given talks and held beginner sessions on Creative Coding in Python and sonic-pi. Completed three grades in hindustani-classical music-theory, with 8+ years of experience in playing the Guitar and Harmonium. Received 3 Honours and Awards (National level). I absolutely love Music and Coding, and aim to merge this passion and demonstrate the applications of Python and open-source frameworks in Music Production by means of this talk :)", - "Speaker Links": " https://github.com/nehsus https://www.linkedin.com/in/sushenk/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Nehsus (~nehsus)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-algorithmic-music-and-melodies-with-python-sonic~dRXVa/", - "title": "Generating Algorithmic Music and Melodies with Python-sonic" - }, - "95": { - "Description": "Data Wrangling involves detection, correction, removal, or otherwise dealing with inaccurate and corrupted data. The most common file formats in which data can be stored are CSV, JSON, and XML. However, many times, the data is not available in the desired format and rather is available in some unconventional file formats like PDF or PPT. Parsing PDFs may seem like a daunting task to many as it is quite an unpredictable format. Simply stated, PDF is a hard-to-parse format. This workshop will help you understand the concept of Wrangling PDFs in an easy and fun way. Following will be the flow of this workshop: Self Introduction Brief Introduction to Data Wrangling Why prefer CSV, JSON, or XML? Why avoid using PDFs? Basics of RegEx based Pattern Matching Parsing PDFs Programmatically using \"slate\" and \"pdfminer\": Getting hands-on Inefficient Parsing? Consider Data Cleaning Exploring PDF Wrangling with \"pdftables\" Where to go from here? Question and Answers Session The End :) Key Takeaways: Gain confidence in Data Wrangling using Python. Get familiar with the daunting PDF Parsing task. Get hands-on with popular PDF Wrangling libraries in Python: \"slate\", \"pdfminer\", and \"pdftables\". Understand the concept and importance of Data Cleaning.", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Basic knowledge of programming in Python language. Familiarity with wrangling CSV, JSON, or XML files will be good but is not necessary.", - "Section": "Core python and Standard library", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/wrangling-unconventional-file-formats-with-python-playing-with-pdfs~aQXGe/", - "title": "Wrangling Unconventional File Formats with Python: Playing with PDFs" - }, - "96": { - "Content URLs": "I delivered a talk on Recurrent Neural Networks at GeoPython 2018, Switzerland. The proposed talk will be enhanced version of my previous talk. This time, I will be covering more topics to make it a more detailed talk.\nLink to my previous talk: https://github.com/greatdevaks/GeoPython_Basel_201", - "Description": "Recurrent Neural Networks (RNNs) have become famous over time due to their property of retaining internal memory. These neural nets are widely used in recognizing patterns in sequences of data, like numerical timer series data, images, handwritten text, spoken words, genome sequences, and much more. Since these nets possess memory, there is a certain analogy that we can make to the human brain in order to learn how RNNs work. RNNs can be thought of as a network of neurons with feedback connections, unlike feedforward connections which exist in other types of Artificial Neural Networks. The flow of the talk will be as follows: Self Introduction Introduction to Deep Learning Artificial Neural Networks (ANNs) Diving DEEP into Recurrent Neural Networks (RNNs) Comparing Feedforward Networks with Feedback Networks Quick walkthrough: Implementing RNNs using Python (Keras) Understanding Backpropagation Through Time (BPTT) and Vanishing Gradient Problem Towards more sophisticated RNNs: Gated Recurrent Units (GRUs)/Long Short-Term Memory (LSTMs) End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras or TensorFlow will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-recurrent-neural-networks-using-python~dPGAb/", - "title": "Understanding and Implementing Recurrent Neural Networks using Python" - }, - "97": { - "Description": "Considering the fact that businesses these days make a lot of money by recommending customers the things that match their likes, knowing how to build a Recommendation System would be of great use to many aspiring Deep Learning enthusiasts. This workshop is all about understanding and implementing Auto-Encoders. Auto-Encoders are the Unsupervised Deep Learning Models which are widely used for Dimensionality Reduction and Feature Discovery. New types of Auto-Encoders have enabled us to build very nice Recommendation Systems. The talk will focus on understanding Auto-Encoders, their types, and building a Recommender System that Predicts Rating (1 - 5) using PyTorch. The flow of the workshop will be as follows: Self Introduction Introduction to Unsupervised Deep Learning Diving DEEP into Auto-Encoders (Theory, Architecture, and Working) Introduction to Sparse Auto-Encoders Introduction to Denoising Auto-Encoders Introduction to Contractive Auto-Encoders Introduction to Stacked Auto-Encoders Understanding the Deep Auto-Encoders Training Auto-Encoders Building a Recommender System that Predicts Ratings (1 - 5) Understanding the Problem of Overcomplete Hidden Layers End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras, TensorFlow, or PyTorch will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-auto-encoders-using-python~aOGRa/", - "title": "Understanding and Implementing Auto-Encoders Using Python" - }, - "98": { - "Content URLs": "Will share the code, slides, and resources as a GitHub repository after the talk", - "Description": "Automatic Visual Speech Recognition comes very handily in scenarios that have noisy audio signals. A video image of a person talking is analyzed and shapes made by the lips are examined which are then turned into sounds by comparing to a dictionary to create matches to the words being spoken. In this talk, we will use a VGG+GRU network which is based on CNN+LSTM layers to predict the text spoken by the speaker and classify it into 20 classes from audio-less videos, consisting of 10 words and 10 phrases. This will be done on the audiovisual MIRACL-VC1 dataset. The talk will cover how a CNN+LSTM can be used to recognize a sequence of shapes formed by the mouth and then match it to a specific word or sequence of words spoken from Visual Feed. It will include data-preprocessing, creation of CNN and LSTM layers using Python and applying them on the dataset", - "Last Updated": "06 Jun, 2018", - "Prerequisites": "Basics of Python Syntax, Tensorflow, Keras, Neural Network", - "Section": "Data science", - "Speaker Info": "Kanika Modi holds a Bachelor's in Computer Engineering from Netaji Subhas Institute of Technology, University of Delhi. Having finished her coursework, she will join Amazon as a Software Development Engineer(SDE). She is an open source enthusiast and has contributed to organizations such as Systers, Fossasia, etc. She is also a Google Summer of Code'18 mentor at Systers, a GirlScript Summer of Code'18 mentor and mentor at RightApprise. Her interests also extend to the fields of artificial intelligence and machine learning. She prefers Python as her weapon of choice", - "Speaker Links": "Link to LinkedIn Link to GitHub Link to Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "kanika_96", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-lip-reading-system-to-recognise-visual-speech-using-python~dNG2e/", - "title": "Building A Lip Reading System To Recognise Visual Speech Using Python" - }, - "99": { - "Content URLs": "Brief content is here: https://github.com/yashug/Pandas Actual workshop will cover more inf", - "Description": "The Goal of this workshop is to make you more fluent at pandas to answer data science questions. Python has long been great for data munging and preparation, but less so for data analysis and modelling. pandas help fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R", - "Last Updated": "04 Jun, 2018", - "Prerequisites": " Laptop with Anaconda installed Basics of Python", - "Section": "Data science", - "Speaker Info": "Yaswanth is a Senior Software Engineer, currently working in ZeMoSo Technologies and Graduated from IIT Guwahati. Free and open source software enthusiast, and passionate about Python and Machine Learning", - "Speaker Links": "Linkedin | Githu", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Gosula Yaswanth (~yashug)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-pandas-for-better-data-science~aKGGa/", - "title": "Using Pandas for Better Data Science" - }, - "100": { - "Description": "The Jupyter ecosystem of tools lets you interleave code and stories for a literate computing experience, where you can visualize your data as html, plain text, svg and images. You could also view the same rich displays in multiple environments - on the web, on your desktop, in your shell or even your IDE . But how is this possible without duplicating logic, re-inventing the wheel multiple times? How do visualization libraries like Bokeh, Plotly work across frontends - like jupyter notebook, jupyterlab and nteract? This talk explores Jupyter's display system and how it handles multiple display formats in multiple environments. We will see how this idea is applied in some open visualization libraries. After this talk, you will know how to integrate your python objects better with the notebook. You will also get an idea of how to create a visualization library that works across the Jupyter ecosystem of tools. Duration 45 mins (Content can be modified to fit into 30-minute slot too) Outline - Setting some terminology for the rest of the talk (what is a frontend, kernel, displayhooks) (5 mins) - How to use Jupyter's display hooks for your python objects with the notebook (10 mins) - The Jupyter messaging protocol - specifically, the display_data and update_data messages (5 mins) - Custom mime-types (and this is the secret to Jupyter's display system!) - separating what to display from how to display it (10 mins) - Examples of custom mime-types in the wild (a look at altair , vdom , plotly and more) (10 mins) Additional notes This proposal might seem to overlap with another - Jupyter Notebooks: Internals and Extension - which explores how jupyter works under the hood and how to create alternative frontends. My talk's focus will be different, and will dive into a very specific part of Jupyter - the display system - in depth", - "Last Updated": "04 Jun, 2018", - "Prerequisites": "Some experience using either the jupyter notebook or jupyterlab ", - "Section": "Others", - "Speaker Info": "I am a software developer at D.E.Shaw, Hyderabad. I've occasionally contributed to projects in the jupyter ecosystem - the notebook, ipywidgets, hydrogen, nteract", - "Speaker Links": "Github Twitte", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Madhumitha psg (~madhumitha)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyters-rich-display-system~dJ1Kb/", - "title": "Jupyter's Rich Display System" - }, - "101": { - "Description": "With the advent of Tableau and languages like Python and R, converting raw data into meaningful insights is much easier and convenient than before. Tableau is a tool used to visually represent data and is powerful enough to analyze the given data at any required level. At an industry perspective, the tool comes handy in finding the trends in marketing and sales with a click of a button. Introducing Python to Tableau using TabPy can help define calculated fields in Python, thereby giving it the power to leverage a large number of Machine-learning libraries right from the visualizations. This widens the scope of its applications to any field that deals with big data and its analytics. Optimisation and cross-sharing of data models facilitated by TabPy immensely enhance the efficiency and usability of the tool. With just a few lines of code, we can churn out predictive models and increase the accuracy of future predictions. The talk will primarily focus on: An introduction to data manipulation and visualization using Tableau. An overview of the steps to leverage TabPy in Tableau. The impact and advantages of Tableau-TabPy combination in the real world.", - "Last Updated": "03 Jun, 2018", - "Prerequisites": "A rudimentary understanding of Data Science and Python scripting", - "Section": "Data science", - "Speaker Info": "I am a sophomore undergrad in computer science from Amrita School of Engineering, India of which I am a part of an intra-college FOSS initiative called FOSS@Amrita. Developing small but useful things that improve lives of the common and affects the open-source community has always been my passion. I believe that with the right technology applied, it can do wonders for the lives of people. Furthermore, I have completed the Google Summer of Code\u201917 with The Wikimedia Foundation and was also a Google Code-In mentor for the same community. Worked on the project that aimed at the improvement and enhancement of the ProofreadPage Extension and Wikisource , through important bug fixes that are left as backlog and implementation of significant features that would make it more user-friendly. This was done so that the extension and Wikisource become easier to use and are raised to the contemporary Mediawiki standards. Apart from this, I'd love to \u200bexpress\u200b \u200bviews\u200b on\u200b \u200bcontemporary\u200b \u200bworld issues,\u200b \u200bget\u200b to know\u200b \u200bthe\u200b \u200bdifferent dimensions\u200b of\u200b \u200bit and analyze the\u200b \u200bmultiple\u200b\u200b ways\u200b \u200bin\u200b\u200b which\u200b \u200bthe\u200b \u200bproblems\u200b \u200bcould be rectified", - "Speaker Links": "Linkedin Blog Gerrit GitHu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Amrit Sreekumar (~amrit95)", - "created_on": "03 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-leveraging-python-in-tableau~dGAKa/", - "title": "Data Analysis: Leveraging Python in Tableau" - }, - "102": { - "Content URLs": "We will share the Github repository for the workshop here couple of weeks before the conference", - "Description": "\"Our Business Is Our Business None Of Your Business\u2026\" Yes, they wish, but we want to know everything about Bollywood! Who is more popular, Katrina Kaif or Deepika Padukone ? When budget is not a problem, do producers prefer Shah Rukh Khan or Salman Khan ? Which city in India is home of the most active actresses and actors? What movie is the most similar to PK ? And lots of other questions. Do you want to know the answers? And even better, would you like to discover them yourself by using Python and popular libraries such as pandas, Gensim and scikit-learn? And cutting-edge data science techniques? Join us for a workshop full of insights where you will be able to answer your own questions while learning the most advanced Python libraries and algorithms. The workshop is designed for Python programmers new to data science. Everybody is welcome, but data analysts and people experienced with pandas will find some parts quite basic. What will we cover? Loading, merging, cleaning and analysing your data with pandas Advanced data visualisation with Bokeh Embeddings and natural language processing with Gensim Forecasting with statsmodel Basic machine learning with scikit-learn All this while answering the questions above, and letting you answer your own questions", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Laptop with Anaconda3 installed Clone of the workshop repository Knowledge of Python Good knowledge of Bollywood desirable :)", - "Section": "Data science", - "Speaker Info": "Himanshu is the organiser of Kanpur Python and PyData Kanpur. Free and open source software enthusiast, and passionate about Python and data analysis, He is currently working for KanpurFOSS organization which organize free technical workshops in India. Yai Workshop\u2026 Data Analysis Ke Workshop Hai\u2026 Kisi Ke Data Analysis sikha kar He Khatam Hoge... Marc (known online as datapythonista) is a data scientist from London. Pythonista since 2006, pandas contributor, and organiser of the London Python Sprints group. Worked for companies like Bank of America, Tesco, Unilever or NTT Communications. Regular speaker at PyCon and PyData conferences. His favourite actor is Aamir Khan, but wouldn't mind teaching Python to Asin", - "Speaker Links": "Himanshu : https://twitter.com/IHackPY | https://www.slideshare.net/HimanshuAwasthi14/ | https://speakerdeck.com/johim9493 Marc : https://twitter.com/datapythonista | https://www.linkedin.com/in/datapythonista/ | http://datapythonista.github.io", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Marc Garcia (~marc)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decoding-bollywood-with-python-and-data-science~eEyWe/", - "title": "Decoding Bollywood with Python and data science" - }, - "103": { - "Content URLs": "PyCon India 201", - "Description": "What's a good way to Set up many development version(s) ? Developers need consistent isolated development environment, running exact same container(s) as what runs in production , automated test tools, package, ship & deliver. Let's touch features of docker to make it run for Python programs/web apps. Outlines First 5 minutes, I'll be talking about current developers need and present solution. Next 5 minutes, what is docker and how it can solve these problems. Next 10 minutes, I'll be demonstrating, how I use docker for in my Python development tasks (Python library, Python web app). After 20 minutes I will have delivered the enough knowledge for the docker, and next 5 minutes I will let the audience know about the some advance features in docker that they can learn from various resources, to get the maximum power of docker. Q/A along with this. Detail description Basic terms of docker Docker Container Docker Image Dockerfile Docker Compose Docker Repository and Docker Hub Docker Daemon, Docker Client and Docker Engine Docker Swarm Docker Machine Docker for Developers Reproducibility and Developer teams Isolation Security Environment Management Continuous Integration Creating Custom Images and Containerizing Your Application Sample Dockerfile to build an image of an small python program. We will run the image and play with this container. Using Docker Compose in development adds an important constraint: your services are not on the same machine anymore. Container Logs Learn how you can see or capture the logs of the container(s) and services. Docker for Python developers In this section I will demonstrate, how you can setup a development version of real world software.\nI will setup the development version. After creating an image and running it in a container, I will show volume sharing techniques as well. Audience will understand how I have created an consistent isolated container, integrated CI which is easy and fast to ship. Docker for Python Web applications Django and Flask web app will be run under the docker container, different environments in one system. We will learn how to use microservices and advantages of making services using docker-compose. Advance and new features of docker Now audience have understood the docker and they can learn many more powerful features of docker. I will share some good resources and let them know about docker swarm, docker machine, Dealing with Logs, etc ", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "Prior experience with docker is not a necessity but having some exposure to Python development, version control system, Unix System is recommended. At the starting talk basic developers need, basic docker features will be covered. So starting point, anyone (entry/intermediate) can understand the docker concepts. Slowly moving to docker for developers, expert Python developers will get ideas to use docker in their development system and how they can solve most of the development conflicts because of using having multiple environments", - "Section": "Developer tools and Automation", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/containerizing-your-application-is-the-solution~dBvQd/", - "title": "Containerizing Your Application is the solution" - }, - "104": { - "Content URLs": "Slides will be updated soon. Django2 release note", - "Description": "Django is one of the most used Python framework in the world of Python and is even used more than Tensorflow(Stack Overflow 2018 Developer Survey). Django is an excellent web-application framework to build scalable, extensible and high-performance web applications that can serve hundreds of thousands of requests per second -- while keeping the development cycle optimal and maintaining the sanity of developer mind-space. The latest version of Django 2.0 has been just released this year. The new Django 2.0 begins a new era without any backward incompatible changes except the removal of Python2.7 in latest version and it aims to completely remove Python2 support for Django environment when LTS Django 1.11 expires in 2020 with Python2 . This release also starts the Django using the loose form of semantic versioning. Django 2 has introduced a lot of major changes like : SImplified URL routing syntax Performance optimisation and improvements Mobile Friendly Admin site Newer functions like Windows and more modified aggregate functions More stricter schema Made Mysql isolation as read committed Talk Outlines What is Django and why use Django? Django design patterns - MTV kind of MVC How does Django works? Simplified URL routing syntax in Django2 Other new features in Django2 When should you move your old project to Django2 and Django release Cycle Tips on converting your legacy code to Django2 This talk aims to provide some general insights on Django and latest Django2 version. Apart from being a talk focussed exclusively on Django, the talk aims to give be an introduction to what server side programming is and in general to Web Development ", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Python Django (preferable) After all this is a Hitchhiker\u2019s guide, this talk will focus on a general introduction to Django and don\u2019t be afraid all the noobs in Python and Django will welcomed and be accommodated in this talk", - "Section": "Web development", - "Speaker Info": "Kurian is currently in his sophomore year, pursuing an undergraduate degree in Computer Science from Govt. Model Engineering College, Kochi. He has interned in multiple startups like Entri.me, WiM as a product intern developing products using Python and web frameworks like Django. He is also a Open source Enthusiast and have contributed to multiple organisation like Zulip , FOSS Asia. He is an active member of FOSS club in his college(FOSSMEC) and of Kochi Python Club(Python Meetup Group of Kerala)", - "Speaker Links": "Github LinkedIn Medium Twitte", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kurian Benoy (~kurianbenoy)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-hitchhikers-guide-to-django-2~aAr9b/", - "title": "The Hitchhiker\u2019s Guide to Django 2" - }, - "105": { - "Description": "The goal of this talk is to explain this quote : \u201cYou shall know a \u2018word\u2019 by the company it keeps!\u201d In this talk, we will go through as to how to build a model for text summarisation (from scratch) and its possible applications in the real world scenario. An intuitive explanation will be provided (the talk would not be all mathematical!) as to how to do the data preprocessing for a large dataset and provide a reasoning as to why we choose a specific model for training. We will also talk about how certain Python libraries make it easier to structure a machine learning pipeline. We will also walk through the best practices and various caveats while building these kinds of complex models and how to circumvent these", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "The prospective audience should have a basic understanding of neural networks and natural language processing", - "Section": "Data science", - "Speaker Info": "Harshdeep is currently a student at the University of Manchester pursuing his Bachelors in Artificial Intelligence and is interested in Natural Language Processing. My experience with Python started at IBM Bristol where I worked for a year developing the compliance automation tool. After that, I worked on my final year research project using Python which was based on finding summaries and sentiment of news articles. I have previously spoken at PyCon APAC in Malaysia last year in August which was a talk about the basics of Neural Networks. After university, I will be working with some early stage startups in India related to AI and Aviation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harshdeep Harshdeep (~harshdeep)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/text-summarisation-made-fun~azAqe/", - "title": "Text summarisation made fun!" - }, - "106": { - "Content URLs": " Initial version of slides (will update regularly and mark it complete once done)", - "Description": "Abstract Being one of the most used collaboration tools used by software engineers and data scientists, \"Jupyter Notebooks\" are transforming the way \"data science\" is happening in the industry. Started as a smart Python interpreter, the Jupyter project has grown into a common platform that supports the development of data science and scientific computing tools across multiple programming languages. This talk is aimed at understanding the technical internals of Jupyter project. Agenda A brief introduction to Jupyter How is it different from IPython Component architecture Kernel Frontend Communication protocol used between a frontend and kernel How does a kernel work Magic commands How to create one Let's create a Jupyter frontend Wait! What if you can use Slack as a Jupyter notebook? Jupyter, Interactive computing, and possibilities What will you learn Process that powers an interactive Jupyter session Do you know how does the tab-completion work? Extending the capabilities offered by Jupyter ecosystem for a custom use-case We will learn how to create magic commands and frontend Black magic", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Basic understanding of Python, comfortable with functions/classes Experience working with Jupyter/IPython notebooks (Optional) Interested in knowing how stuff works", - "Section": "Data science", - "Speaker Info": " Tech & Product at Vernacular.ai Data-driven journalism practitioner Featured in Tech in Asia and Global Investigative Journalism Network Contributor to Go programming language", - "Speaker Links": " Website GitHub Twitter", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pravendra Singh (~pravj)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyter-notebooks-internals-and-extension~dyz6e/", - "title": "Jupyter Notebooks: Internals and Extension" - }, - "107": { - "Content URLs": "Programs in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=", - "Description": "Mention of \u201cCancer\u201d evokes words like tumor, chemotherapy, hair loss, vomiting and pain. Interestingly our knowledge and thereby cancer treatment has changed radically in the past few years and is changing rapidly every passing day. In 2003, human genome was sequenced and for the first time we could read entire human DNA from end to end. Interestingly DNA and cancer are deeply connected. Scientists deciphered that always a change in DNA (mutation) led to cancer (oncogenic mutation). Cigarette smoking, alcohol, pollution etc only led to such DNA change (oncogenic mutations). This led to numerous diagnostic companies starting to extract and sequence tumor DNA, to detect the root cause of each patient tumor. While drug companies formulated new drugs that targeted specific DNA change (mutation). These were called targeted therapies which were very different from chemotherapy in being very precise, less toxic, less side effects and they could be taken orally just like any regular pill. Thus, an oncologist (cancer doctor) could treat a cancer tumor effectively if s/he knew the precise location of mutation in the entire patient tumor DNA and the drug that targeted it. Suddenly oncologists in India and elsewhere, found themselves struggling to comprehend tumor DNA and the technology around it. Already burdened with tomes of ever changing patient treatment guidelines, now they were needed to integrate tumor DNA information to make accurate treatment decisions. For eg. NCCN (National Comprehensive Cancer Network, USA) which publishes treatment guidelines for all cancer for oncologists across the world, published lung cancer guidelines that is 271 pages long. To this, add the complex data of patient\u2019s tumor DNA, various mutation databases, clinical trials and research papers. Modern day oncologist are often overwhelmed. They need tools to simplify and hasten their decision making. I am a molecular biologist who understands the tumor DNA and the technologies around it. As Chief Scientist (molecular oncology) of Neuberg diagnostic lab, I also write patient DNA reports that guide oncologists to take treatment decisions. While meeting various oncologists and marketing them different DNA tests for different type of cancers, I got acutely aware of the problems oncologists faced. To simplify their decision making, I created algorithms that combined patient\u2019s clinical history, histo-pathology data, molecular test decisions, mutational databases and NCCN guidelines. Subsequently I coded these integrated and complex decision algorithms as Python programs that can be executed from a browser. They are available for free and oncologists are/can use it.\nPrograms in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=0 \nMy article on need of Python programing for cancer treatment: https://sites.google.com/view/molecularpathology/programming/is-it-time-for-precision-medicine-app?authuser=", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Interest in using programing to resolve healthcare problems in India", - "Section": "Others", - "Speaker Info": "I am a PhD in Biochemistry with significant research experience at the University of North Carolina at Chapel Hill, in the areas of molecular oncology, cardiovascular biology and biology of infectious diseases. Currently, I prepare molecular diagnostic reports for cancer patients as Chief Scientist (Molecular Oncology), Neuberg Center of Genomic Medicine, Ahmedabad", - "Speaker Links": " Molecular pathology of cancer: https://sites.google.com/view/molecularpathology/home?authuser=0 The DNA Labs: https://sites.google.com/site/thednalab/ , https://www.facebook.com/TheDNALab , https://www.youtube.com/channel/UCf2HKt1vgjhe8MXbvMSwELg/feed", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "siddharth srivastava (~siddharth40)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/helping-oncologists-to-take-complex-decisions-in-treating-cancer~axylb/", - "title": "Helping oncologists to take complex decisions in treating cancer." - }, - "108": { - "Content URLs": "share here soon", - "Description": "Flutter is Google\u2019s mobile app SDK for crafting high-quality native interfaces on iOS and Android in record time. So lets create web services for Flutter app using python/Flask framework", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Basic of Python Knowledge of Webservices REST and JSON Hello world Knowledge of Mobile App. Familiar with Android Studio and Pycharm", - "Section": "Web development", - "Speaker Info": "I am opensource lover. I love to explore opensource technologies for mankind. I am organiser of \"Arduino and IoT ,Kanpur\" . I teach kids under coderdojo program", - "Speaker Links": " https://twitter.com/vivdroid https://github.com/vivekaris", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/write-python-web-services-for-flutter-app~avw8b/", - "title": "Write Python Web services for Flutter App" - }, - "109": { - "Content URLs": "https://github.com/vivekaris/firebase-io", - "Description": "Now Days Internet of Things are Trending technology for every makers. Lets Build Python based Automation controller for any Hardware (tested on Raspberry Pi and Node MCU).\nWe will use firebase as a data storage and Action handling.\nWith the help of Firebase Realtime Database ,we can control hardware from any geographical location", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Keen to learn Basic of Python Knowledge of PIP Knowledge JSON Basic Knowledge of C for Arduino(Node MCU Programming) Laptop with Linux/Mac/Win 7 onwards. Node MCU v3 2 LED with 4 Jumper Wire Internet Connectivity Google Account enter code her", - "Section": "Web development", - "Speaker Info": "I am opensource tech lover", - "Speaker Links": " https://github.com/vivekaris https://twitter.com/vivdroid http://makerspacekanpur.com/blog/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-firebase-build-amazing-iot-application~erp2b/", - "title": "\"Python and Firebase\" Build Amazing IoT Application" - }, - "110": { - "Content URLs": "Kubernetes Docker Azure Kubernetes Service aka AK", - "Description": "Kubernetes is considered as the new Kernel of the Cloud. It's a distributed computing platform letting users not have to care about infra and helping them concentrate mainly on business logic. By having your web app deployed on a kubernetes cluster you can make sure your app is highly available, and can fail-over when there's a problem. One of the main goals of the Kubernetes project is to democratize distributed computing. With Kubernetes being open source, Companies do not have to redo the mundane task of writing a distributed computing platform to achieve high availability, automated deployment, scaling and management of your applications. Kuberentes will take care of that for you. Kubernetes is also considered as a container orchestrator, as it manages containers to achieve the above said goals. In this talk: We will first write a basic python web app. Next, We will go through what a container is Containers are becoming the de-facto way of deploying applications as they remove the complexities of dependency management,etc. Running apps on Individual Containers provide the isolation almost to that of a Virtual Machine without having the overhead of having individual Kernels as they all share the host kernel. Isolation is provided by using kernel level features like cgroups and namespaces. We will containerize the application using docker and push it to a Container Registry. Once we have the image deployed to a registry, this image will be used to create instances i.e containers of the web app. We will next create a kubernetes cluster on Azure, all along going through what a Kubernetes cluster is, and its components. We will then deploy our python web app onto the cluster. Now As we have our python web app up and running, We can then do some experiments on how Kubernetes self-heals the application when a node goes down,etc. After that I will run down some points on where Kubernetes is being\n used, its impact. To Finally answer the question, Is Containers and Kubernetes worth all the Hype ? This talk will be demo focused, But before going to a demo we will have some slides explaining the overview of the components and how they work. By the end of the talk, Audience will have a brief overview of what containers and kubernetes are, and how to deploy a web app on Kubernetes. From this overview, Audience can start digging deeper online and know more", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Understanding of Python. Basic Understanding of Deployment of a web app. It's good if you already have some basic understanding on what containers and kubernetes are", - "Section": "Developer tools and Automation", - "Speaker Info": "Tarun Pothulapati is currently pursuing his B.Tech in Computer Science and Engineering in Hyderabad.\nHe is a Tech Enthusiast and codes mostly in Python and C#. He is very much interested in distributed computing platforms like Kubernetes and Microsoft's Service Fabric which are trying to democratize \nthe technology which was before only a privilege of the Big-Tech firms.\nHe spends most of the time learning about it and trying to contribute to their repositories. He is also very enthusiastic about sharing the knowledge about these cutting edge technologies.\nTarun has also worked on many projects on chatbots, Web apps etc and have won some\nhackathons held by IEEE, IBM & Amazon and he was one of India's 40 finalists of AICTE's \nStartup Contest 2017", - "Speaker Links": "Twitter Github Linkedin Websit", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Tarun Pothulapati (~Pothulapati)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deploying-a-python-web-app-onto-a-kubernetes-cluster~bqo7e/", - "title": "Deploying a Python web app onto a Kubernetes Cluster" - }, - "111": { - "Content URLs": "---In progress, will be ready to share by July last week can make it to July first week if urgent--", - "Description": "Signal processing is a fundamental part of ECE and is also used in many other fields. Students for years have been using expensive Matlab for learning this skill. The talk/workshop/interactive session can be used by students to get a better understanding of signal processing and implementing it with python. The use of python language in signal processing is preferred as it is portable, easily available and fast to deploy Topics covered include but are not limited to Sound and Signals Noise Fourier Transform Filtering Modulation Sampling LTI Systems The talk will be at a simple level so that even a high school student can understand signal processing and implement it. If time allows another session on using python to solve electrical networks and visualizing them can also be implemented", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic knowledge of python and Signals and systems (WikiPedia knowledge is enough.) NumPy (Used for array manipulation ) SciPy (For computation) matplotlib (For plotting various signals etc.)", - "Section": "Others", - "Speaker Info": " Speaker is a 3rd year ECE student with experience in python for numerical computations, web development and most importantly signal processing , and electrical networks Interested in using python in modern electronics like the pyboard and raspberry pi and advocates the use of python over expensive software. An avid python user, always tries to find a way to implement given task in python and believes that where there is a task to be done there is a suitable python library.", - "Speaker Links": "LinkedIn Faceboo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Abel Joseph John (~abel91)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/digital-signal-processing-with-python-and-applications-in-audio~epnQb/", - "title": "Digital Signal Processing with Python and Applications in Audio" - }, - "112": { - "Content URLs": "https://www.py4e.com/\nhttps://www.coursera.org/specializations/pytho", - "Description": "This session will take a look at the \u201cPython for Everybody\u201d series of courses on the Coursera platform. This course has impacted over 1.3 million students over the last five years. We will look a the history and goals of the course and how the course works to create a learning community. We will show how the free open educational resources (OERs) and book associated with the course have been used by teachers, students, and courses around the world to form a network of educational activities centered around Python. We will also cover briefly the Tsugi (www.tsugi.org) software that is used to build the learning assessments and distribute the OER materials in a way that enables maximum reusability of the materials for other teachers", - "Last Updated": "31 May, 2018", - "Prerequisites": "No pre-requisite", - "Section": "Core python and Standard library", - "Speaker Info": "http://www.dr-chuck.com/\nhttps://www.si.umich.edu/people/charles-severance\nhttps://twitter.com/drchuck/\nhttps://github.com/csev\nhttps://www.sakaiproject.org\nhttps://www.tsugi.org\nhttps://www.slideshare.net/cse", - "Speaker Links": "http://www.dr-chuck.com/dr-chuck/resume/index.htm Charles is a Clinical Professor and teaches in the School of Information at the University of Michigan. He is the Chair of the Sakai Project Magament Committee (PMC). Previously he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project and worked with the IMS Global Learning Consortium promoting and developing standards for teaching and learning technology. Charles teaches ten popular MOOCs and two specializations to students worldwide on the Coursera platform: Internet History, Technology, and Security, Web Applications for Everybody, and Python for Everybody and is a long-time advocate of open educational resources to empower teachers. Charles was the editor of the Computing Conversations column in IEEE Computer magazine from 2011-2017 that features a monthly article and video interview of a computing pioneer. Charles is the author of several books including: Python for Everybody, Sakai: Building an Open Source Community\", \"Using Google App Engine\", from O'Reilly and Associates and the O'Reilly book titled, \"High Performance Computing\". Charles has a background in standards including serving as the vice-chair for the IEEE Posix P1003 standards effort and edited the Standards Column in IEEE Computer Magazine from 1995-1999. Charles is active in media as a hobby, he has co-hosted several television shows including \"Nothin but Net\" produced by MediaOne and a nationally televised program about the Internet called \"Internet:TCI\". Charles appeared for over 10 years as an expert on Internet and Technology as a co-host of a live call-in radio program on the local Public Radio affiliate (www.wkar.org). Chuck's hobbies include off-road motorcycle riding, karaoke and playing hockey. Charles has a B.S., M.S., and Ph.D. in Computer Science from Michigan State University", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Charles Severance (~charles)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/inside-the-worlds-largest-python-course-on-coursera~bomYe/", - "title": "Inside the World's Largest Python Course on Coursera" - }, - "113": { - "Content URLs": "Slides: https://docs.google.com/presentation/d/1z-pWhSOERi-vl_wPLVsdCNpl54G3IA0D8K7ve13HFZI/htmlpresent Source code for the examples: https://github.com/minhajuddin/collaborative-canvas-demo", - "Description": "Outline/structure of the Session\n1. An introduction to Elixir\n2. An introduction to Phoenix\n3. Outline and design overview of our canvas app\n4. Implementing our app\n5. Deploying it to a server\n6. Q&A Learning Outcome\nLearn how easy it is to use Elixir and Phoenix to create real time applications at a massive scale", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic understanding of the web applications", - "Section": "Web development", - "Speaker Info": "I am a very passionate programmer. I am also the CEO of a Micro ISV, Cosmicvent Software. I have been in the software industry for 10 years.I love writing code and have worked with Elixir, Golang, Ruby, .NET and Javascript among other technologies", - "Speaker Links": "Follow me on twitter https://twitter.com/minhajuddin Follow me on GitHub https://github.com/minhajuddin/ My Blog: https://minhajuddin.com/ Previous presentation: https://www.youtube.com/watch?v=WabGxSZhPE", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Khaja Minhajuddin (~minhajuddin)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-collaborative-canvas-using-elixir-and-phoenix~enl5b/", - "title": "Building a collaborative canvas using Elixir and Phoenix" - }, - "114": { - "Content URLs": " Postman Jmeter Burp", - "Description": "API testing is fun! For a small team of 7 (Dev + QA), having dedicated resources to do functional, Security and Performance of the APIs is close to impossible.\nHence, We came up with a framework which automates the process of API testing covering the basic functionality, Security, and Performance so that we don't miss out testing any of these layers. I would cover up the basics of Postman, Burp and JMeter components used for the framework", - "Last Updated": "31 May, 2018", - "Prerequisites": " Interest in automating the Webservices testing :)", - "Section": "Developer tools and Automation", - "Speaker Info": "A tech enthusiast who has 7+ years of experience in the Software Testing in Startups. I love to explore new technologies and automate mostly everything which takes more time. A strong believer in processes. Love testing Webservices. Would love to share the experience we had in building the framework for API testing", - "Speaker Links": "https://www.linkedin.com/in/sarala-v-620b0b1a/ https://twitter.com/saralaVeerann", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sarala V (~sarala)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-rest-api-testing-for-functional-security-and-performance-testing~bmkRe/", - "title": "Automating REST API testing for functional, security and performance testing" - }, - "115": { - "Content URLs": "https://github.com/radhikascs/cryptography-pytho", - "Description": "This talk is meant for the end users who aspire to learn basics of cryptography and its implementation in real world projects. \nThis tutorial is also useful for networking professionals as well as hackers who want to implement new frameworks instead of following traditional approach", - "Last Updated": "31 May, 2018", - "Prerequisites": "It is expected that the end user should know basics of cryptography and algorithms. The knowledge of cryptography algorithms becomes a cakewalk for a user who reads this tutorial", - "Section": "Core python and Standard library", - "Speaker Info": "A pinch of optimism with a blend of hard work and focus defines Radhika Subramanian. She works as an Academic Writer and Tutor with various organizations. She has completed MSc(CA) from Symbiosis International University. She also includes a passion for research work in Artificial Neural networks and it's technologies. She is currently working as an Author with BPB Publications and Apress Media LLC", - "Speaker Links": "https://www.linkedin.com/in/radhika-subramanian-486a771a/ https://www.unanth.com/tutor/radhika-subramanian-14135", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Radhika Subramanian (~radhika14)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cryptography-and-python~elkjd/", - "title": "Cryptography and Python" - }, - "116": { - "Content URLs": "To get a feel of Numba see - first step", - "Description": "Thinking parallel is an art, applying it is another. While applying it, the first hurdle for us is to move to another language like C or C++ to get performance gains. \nWhat if we write simple python code and someone magically helps us gain C like performance? Sounds like a dream, it ain't ! . Enter Numba :) In this workshop you will - Witness how Numba help you get insane performance gains to your code without changing a line of it. Learn to harness the power of your GPU/CPU for performing math intensive computations. See how it compares to other libraries like Numpy , etc. and how they can complement it. Use Numba to parallelize the very famous Particle Swarm Optimization Algorithm Flow of the workshop - Where to use Numba in your code - (time profiling, small examples) The wow of Numba in my life, a small example of how it helped in my research Introduction to jit complier, internals of Numba Introduction to the Particle Swarm Optimization (this is where the fun starts :) ) Code up basic PSO Profile PSO to find pain areas Try to speed up the pain areas using Numba Kick up a hierarchical swarm (just for fun, if time permits) QA Session", - "Last Updated": "31 May, 2018", - "Prerequisites": "numpy, matplotlib, jupyter, ipython, numba, line_profiler , llvmlite. A more specific description is available her", - "Section": "Others", - "Speaker Info": "Hi, I am Shubham Bhardwaj. I am currently a Research Intern at Jio CoE for AI/ML and a final year undergrad at VIT University, Vellore. I am a die-hard pythonista. \nMy daily work involves developing and implementing algorithms for interesting problems in AI. Apart from this I am also an organizer at GDGVIT, I love dev :) and contribute to various open source organisations, organise workshops, promote python whenever I can", - "Speaker Links": " LinkedIn Github", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Shubham Bhardwaj (~shubham0704)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/leveraging-the-power-of-your-gpucpu-for-math-intensive-computations-with-python~bkjJa/", - "title": "Leveraging the power of your GPU/CPU for math intensive computations with python" - }, - "117": { - "Content URLs": "The Magenta Project Music Composition using Recurrent Neural Network", - "Description": "Music is mainly an artistic act of inspired creation and is unlike some of the traditional math problems. But, a sequence of specific chords and notes can be observed when we listen to music. With the recent advancements of the AI tech, sequence models are used invariably in innumerous fields, one such sequence model, LSTM( Long Short Term Memory Networks) can be used to generate melodies and beats. So, this talk is about how deep learning models, specifically LSTMs were used to produce music - catering particularly to the Electronic Dance Music Industry. CONTENTS AND ORDER OF THE TALK Learning how LSTMs help in generating music, and the concepts behind it. Preprocessing the MIDI data for the melodies and beats using MIDI packages created by the Python community. Building the LSTM network using Keras with Tensorflow as backend and understanding it. Train the network with the melodical data to create the LSTM network for melodies and same thing for beats. Generating melodies and beats(using pretrained model) and combining the two to create different type of genres of music. I am including a piece of music generated by an MIT alumnus, but I will be explaining the steps from scratch . Generated Techno Beat", - "Last Updated": "30 May, 2018", - "Prerequisites": "Tensorflow, Keras, Recurrent Networks and a Good taste in music ;", - "Section": "Others", - "Speaker Info": "I am Kumar Abhijeet, a sophomore from RV College of Engineering, Bengaluru and an AI enthusiast. I am a budding EDM producer and a python programmer as well(no doubt in that). I have worked with small AI startups in building their frameworks. I am an open source contributor and a GSOC aspirant. I have always loved the idea of mixing technology with regular phenomena, which I will be doing with music. I love going to meetups and meet different kinds of communities to learn from them", - "Speaker Links": "LinkedIn ID Github Lin", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kumar Abhijeet (~kumar80)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-beats-and-melodies-with-lstms-using-python-and-tensorflow~ejgya/", - "title": "Generating beats and melodies with LSTMs using Python and Tensorflow" - }, - "118": { - "Content URLs": " https://www.djangoproject.com/ http://www.celeryproject.org/ https://sensu.io/", - "Description": "Monitoring is a key aspect for any business. It enables us to find and be notified about the problem way ahead our customer notices it, which enables us to keep our businesses running and making customers happy. I will be talking about how we SREs at Opentable Inc, tries to solve the good old monitoring problem, sensu with puppet, using Django, Sensu and Celery. If you are fed up with the limitations of what current monitoring tools offer, this is the talk you wanna look out. At the end of talk, audience would have an alternative approach for monitoring using python. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce monitoring and how we use currently at Opentable Inc. Describe limitations we have with our previous monitoring stack. Alternate new generation monitoring architecture using python tools Django and Celery, keeping sensu intact. How we developed a site using Django, which help us to maintain the checks and add new check definition. How we used Celery distribution system to run checks on multiple worker nodes and send results to sensu. I will talk about how we scaled celery worker nodes by setting up different queues, and prioritising the tasks and by using Flower.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic knowledge of Sensu. Basic knowledge of Django and Celery. Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-infrastructure-and-application-using-django-sensu-and-celery~e0o5d/", - "title": "Monitoring infrastructure and application using Django, Sensu and Celery." - }, - "119": { - "Content URLs": " https://github.com/errbotio/errbot http://errbot.io/en/latest/", - "Description": "The wikipedia definition of ChatOps is, a collaborative, conversation-centric way of working that brings people, discussions, bots, tools and files together in one central location: the workplace messaging app. That's it! That's what exactly I am gonna talk about. I am gonna talk about Chatops bot, Errbot which is written in python and can be used across various messaging apps like Hipchat, Slack, telegram, skype, etc. Using chatops one can automate the tedious, boring tasks and let the bot do the work for you. It also enables various engineering teams to collaborate and exchange information easily at one place: their official messaging app. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce chatops - culture, uses, possibilities. I will talk about the possible scenarios where we could use chatops in our daily tasks. I will then introduce Errbot and its plugin architecture. Tell audience about various features of errbot and its builtin plugins. Demonstrate errbot to audience by creating a command and using it in Slack. How to set up a alternate storage for errbot. I will conclude the talk explaining the ACLs(Access control List) in errbot.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic Python Passion for automation Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatops-using-python-bringing-developers-and-operations-together-making-tasks-easier~e9AJe/", - "title": "Chatops using Python - Bringing developers and operations together, making tasks easier!" - }, - "120": { - "Content URLs": "https://github.com/aj-jeste", - "Description": "Google Cloud Platform Deployment Manager (GCP DM) allows you to codify your infrastructure with minimal setup, just need to download the gcloud library and you're off to the races. While its simple to get started with GCP DM, its a whole 'nother ball game to write extensible and reusable DM code. In this talk I will show you how to scaffold your code into two distinct groups: configs and templates. By separating these out you can reuse the same templates across multiple deployments with different configs and make your codebase a little bit smaller. How to write a basic DM deployment. Convert the basic DM deployment into a template. Launch multiple deployments with different configs but same template. Create custom helper functions in DM Best practices when using DM", - "Last Updated": "30 May, 2018", - "Prerequisites": "Understanding of Google Cloud Platfor", - "Section": "Developer tools and Automation", - "Speaker Info": "As a freelance Site Reliability Engineer and Cloud Architect, AJ has traveled all over the world helping startups setup and manage Cloud infrastructure. He has also architected and deployed large Hybrid on-prem/cloud infrastructure for existing well established companies that wanted a taste of the cloud but needed to keep their physical data-centers as well. This is his 11th year as a SRE/CA and has automated, scaled and monitored infrastructure anywhere from 150 to 3500+ nodes, both physical and virtual. Currently he is looking for his next challenge, perhaps its this pycon talk. Brought up and currently lives in New York City but travels all over the world in search of the best train journeys and awesome foods which seems to bring him back to India again and again", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "aj", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-cloud-platform-deployment-manager-scaffolding~b8zje/", - "title": "Google Cloud Platform Deployment Manager Scaffolding" - }, - "121": { - "Content URLs": "I will share the slides after my talk as a Github repository", - "Description": "If you are working in the field of research than you might be wondering about symbolic solutions which must be needed while working in such arduous fields like Mechanical Engineering or Computer Science or Quantum Mechanics. Sympy is the solution for that. Sympy deals with the computation of mathematical objects symbolically. This means that the mathematical objects are represented exactly, not approximately, and mathematical expressions with unevaluated variables are left in symbolic form. This talk will cover Introduction and Uses of Sympy Library", - "Last Updated": "30 May, 2018", - "Prerequisites": "Basics of Python is good. \nDon't know Python? It's still okay. You will definitely find something new", - "Section": "Core python and Standard library", - "Speaker Info": "Nikunj Parmar is a Sophomore year student at Nirma University. His major field is Flexible Robotics. He has been working with Python for last 2 Years as a Researcher. As a Junior Undergraduate student, He has worked on many projects focused on Robotics, Machine Learning, and Core OS Programming. His interests lie in the fields of Robotics, Design and Control Engineering, Computational Engineering, and its applications in a broad range of circumstances", - "Speaker Links": "https://www.linkedin.com/in/nikunj-parmar-b87739138/ https://github.com/nikunjparmar82", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Nikunj Parmar (~nikunjparmar828)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sympy-symbolic-computation-with-python~b6xOe/", - "title": "Sympy : Symbolic Computation with Python" - }, - "122": { - "Content URLs": "https://docs.google.com/presentation/d/1PZ56AYSH6GZ8s-V8rfxHuZ16UCmDg03Y1L2EiTCBiUs/edit#slide=id.p \n(Subjected to changes, not final one)", - "Description": "Talk is about how python is useful in web development, what are the most powerful and popular python frameworks used i.e., Django, Pyramid, Flask and how they are used in making web applications. My talk covers : What a web framework means Why to choose python frameworks over the normal other frameworks Explanation on Django, Pyramid, Flask. Which framework should be chosen based on dependencies. Starting Web development with python. Django, Pyramid, Flask will be explained in short with the help of small code snippets. Examples of organizations using these frameworks will be given. Uses of one framework over the other will be told in detail", - "Last Updated": "29 May, 2018", - "Prerequisites": "No prerequisite is required. Desire to learn is enough to attend this talk", - "Section": "Web development", - "Speaker Info": "About Me I am Jameer, a third year Computer Science and Engineering undergrad at Amrita Vishwa Vidyapeetham, Kerala, India. I love to code in Python. So, I started my open source career by contributing to Coala organisation. Due to my open source enthusiasm, I started learning how python is useful in Web development and using Django, Flask etc., I am also an OSFY author and published an article related to how Hadoop is being used in Big Data Analysis. I am also a ACM-ICPC Regional participant at Amritapuri. I also have a keen interest in Chatbots", - "Speaker Links": "https://github.com/JameerBabu https://www.linkedin.com/in/jameer-babu-0199a2137", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Jameer", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-web-development~e5wYb/", - "title": "Python - Web Development" - }, - "123": { - "Content URLs": " https://fasttext.cc/ https://github.com/PacktPublishing/Learn-fastText https://github.com/facebookresearch/fastText/tree/master/python", - "Description": "FastText has been open-sourced by Facebook in 2016 and with its release, it became the fastest and most cutting edge library in Python for text classification and word representation. It is to be seen as a substitute for gensim package's word2vec. It includes the implementation of two extremely important methodologies in NLP i.e Continuous Bag of Words and Skip-gram model. Fasttext performs exceptionally well with supervised as well as unsupervised learning. The tutorial will be divided in following four segments : 0-10 minutes: The talk will begin with explaining common paradigms that are present right now. Are deep learning really necessary? 10-15 mins: what are word representations 15-25 minutes: The code will be shown and explained line by line for both the models (CBOW and Skip-gram) on a standard textual labelled dataset. Showing how you can do fast prototyping with minimal code. 25-30: How to use the pre-trained word embeddings released by FastText on various languages and where to use them. Why python3 is the best language for multi-language support and a note on general deep learning using fasttext. 30-40 minutes: For QA session. ", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic python knowledge. Some Knowledge on common NLP techniques.", - "Section": "Data science", - "Speaker Info": "Joydeep is a machine learning engineer/python developer and is a Principal Engineer at Nineleaps. 5 years back he saw the Zen of Python, fell in love with Python and has been in love with it since then. Apart from his day to day work is involved in blogging and podcasting on medium and flawcode. Teaching is another passion of his and he is a python/ML trainer at tecmax", - "Speaker Links": " Medium: https://medium.com/@joydeepubuntu/latest Github : https://github.com/infinite-Joy LinkedIn : https://www.linkedin.com/in/joydeep-bhattacharjee-934a1157/ Machine Learning Podcast: https://flawcode.com/episode/show/12 twitter: https://flawcode.com/episode/show/12", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Joydeep Bhattacharjee (~infinite-Joy)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cutting-edge-nlp-classifiers-in-one-hour-with-python-and-fasttext~b4v7e/", - "title": "Cutting edge NLP classifiers in one hour with Python and fastText" - }, - "124": { - "Content URLs": "I'll be sharing the slides after my talk as a Github repository. Soon will be sharing a gist", - "Description": "Abstract One of the feature people love about Python is how it\u2019s dynamically typed. A lot of people are very reluctant on hearing this idea of static typing, they will come back bashing on what's the use of Python then when we introduce static typing in it. With the torch bearers of Python in the industry like Google, Quora, Instagram, and a lot of others retaining their stack on Python and introducing static checking there have to be some non-superficial benefits, which are worth discussing. This is Python class Employee(NamedTuple):\n name: str\n id: int = 3\n\ndef fib(n: int) -> Iterator[int]:\n a, b = 0, 1\n while a < n:\n yield a\n a, b = b, a+b Contents of the talk What's static typing Need of static typing Static typing in Python 3.6 Type checkers Demo mypy vs pytype Pros and Cons QnA and discussion", - "Last Updated": "29 May, 2018", - "Prerequisites": "Basic Python knowledge and a little overview of what is dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Harshil Rastogi is working as a backend software engineer @Innovaccer, previously he has worked as an NLP Scientist @Evalueserve", - "Speaker Links": "Find me on github , ohh you like QnA forums stackoverflow . Oops were you looking for a professional platform? Okay, LinkedIn it's", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harshil Rastogi (~harshil9968)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/static-typing-with-python-what-why-and-why-not-to~e3rAd/", - "title": "Static typing with Python. What? Why? and Why not to." - }, - "125": { - "Content URLs": "Content will be shared on github after the workshop. I will share detailed plan for the workshop in a while for the review", - "Description": "Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero ( https://deepmind.com/blog/alphago-zero-learning-scratch/ ). \nOpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms. In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding. Content Introduction to Reinforcement Learning (~ 15 mins) Introduction to Reinforcement Learning algorithms (~ 15 mins) Setting up OpenAI Gym and other dependencies Implementing simple algorithm using one of the atari games from OpenAI Gym (~ 1 Hr 15 mins) Quick overview of deep reinforcement learning and important papers in the area (~ 15 mins)", - "Last Updated": "29 May, 2018", - "Prerequisites": "Participants must be well versed with python. Some exposure to analytics libraries in python such as numpy, pandas, keras, tensorflow, pytorch would help", - "Section": "Data science", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company. I have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures. Since past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "saurabh1deshpande", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-reinforcement-learning-using-openai-gym~b2qMa/", - "title": "Introduction to reinforcement learning using OpenAI Gym" - }, - "126": { - "Content URLs": "https://github.com/hasura/gitkub", - "Description": "Gitkube is an open-source project that brings the developer experience of Heroku, on your own kubernetes vendor within 60 seconds . This means that you can take your python app, deploy it with a git push & scale it massively all on infrastructure you own at a fraction of the cost on Heroku. After a brief introduction, this talk will be a live-coding demo + tutorial. \nAudience members are encouraged to bring their own laptops with python apps and follow along in the talk to deploy their app. Permitting time, the talk will cover how gitkube works and how developers can contribute", - "Last Updated": "29 May, 2018", - "Prerequisites": "Python\nGi", - "Section": "Developer tools and Automation", - "Speaker Info": "Tanmai runs a startup, Hasura, where they're building tools to make it easier for developers to move to GraphQL and Kubernetes. \nThey were early adopters in the container ecosystem (pre-1.0 adopters for both Docker and Kubernetes) and have grown and contributed to the ecosystem as a company especially in India. Before this, Tanmai ran a consulting firm where their work included everything from MVPs for startups to helping one of the largest banks in the world migrate from legacy monoliths to containerised microservices. Tanmai has been building applications for over 8 years with a variety of frameworks. He is a firm advocate of democratising the power to develop applications and is the proud teacher of one of the largest tech MOOCs in India, imad.tech", - "Speaker Links": "Kubecon talk on gitkube: https://www.youtube.com/watch?v=gDGT4Gf_4JM Hasura: https://hasura.io LinkedIn: https://www.linkedin.com/in/tanmaig/ Twitter: https://twitter.com/tanmaig", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanmai Gopal (~tanmai)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demo-tutorial-git-push-to-deploy-your-python-app-to-kubernetes-heroku-style~e1pZd/", - "title": "Demo + tutorial: Git push to deploy your python app to kubernetes - heroku style!" - }, - "127": { - "Content URLs": "Slides Repositor", - "Description": "I'll be sharing how Python has been of help in my transformation from a hobby developer to a researcher.\nCoding and in particular, simulations are used extensively in the field of research to verify results and sometimes serve as experiments when it is physically not feasible. I'll describe step by step, how to design a real-time simulator using the example of an aerial swarm of drones in a survivor rescue scenario with the help of common Python libraries", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic understanding of Python classes and objects Enthusiasm to learn something new Love for Python", - "Section": "Core python and Standard library", - "Speaker Info": "Aniq Ur Rahman, Final year undergraduate student from NIT Durgapur. Summer '18 Research Intern at CERN GSoC '17 Intern at RoboComp Summer '17 Research Intern at SWAN Labs, IIT Kharagpur", - "Speaker Links": "Linked In Blo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aniq Ur Rahman (~Aniq55)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-research~eZGQa/", - "title": "Python and Research" - }, - "128": { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "Artificial Intelligence is spreading in the modern world and it has changed the face of technologies in past several years, especially Information technology. Today we are much engaged with using and developing so-called intelligent computing systems and devices. This paradigm has evolved in many sub-areas likewise Machine Learning, Deep Learning & Neural Networks. These sub-areas of AI have a greater role in solving Vision problems( e.g. image recognition, object & activity detection etc.), Speech problems( e.g. ASR, trigger word detection, language translation etc.) and many more complex problem domains with help of robust algorithms & models. this talk will be focused on Sequence Neural Models used for solving the Speech and text problems and we will be introduced to real-world applications. topics covered during the talk Introduction Recurrent Neural Networks Word embeddings Attention Models(Trigger word detection) Real World Applications", - "Last Updated": "29 May, 2018", - "Prerequisites": "Machine Learning\nBasics of Neural Networks\nPython Programming Machine Learning( Basics) Basics of Neural Networks Python", - "Section": "Data science", - "Speaker Info": "The speaker, Prashant Kumar Rai, is a final year M.C.A. student at Department of Computer Science (Pondicherry University, Puducherry) who has been working on Machine Learning and data science for quite a while. he pivoted from C to Python in his first year of Master's and currently using this for his projects. He used to blog at his leisure time. Prashant is also a course mentor for 'Sequence Models' part of Prof. Andrew Ng' s Deep Learning Specialization on Coursera, where he helps learners who need in-course assistance and feedback to successfully complete a course", - "Speaker Links": "Github Twitter Quora LinkedIn Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "PRASHANT KUMAR RAI (~pkraison)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/follow-the-sequence-in-deep-way-introducing-sequence-models~bYYAb/", - "title": "Follow the Sequence in Deep way - Introducing Sequence Models" - }, - "129": { - "Content URLs": "https://docs.microsoft.com/en-us/python/api/overview/azure/?view=azure-pytho", - "Description": "Python SDK for Azure is natively available. We would explore how this SDK can be used for automation and management of Azure. Python makes it easier for IT Pros and Developers to build a rock solid DevOps pipeline with simple script", - "Last Updated": "28 May, 2018", - "Prerequisites": "Basic understanding of Azure or any cloud\nBasic Python knowledg", - "Section": "Developer tools and Automation", - "Speaker Info": "Wriju works for Microsoft as Cloud Solution Architect. He is with Microsoft for more than 13 years and total of 17 years of industry experience. He is one of the first to play with Azure in its very early stage back in 2008. His day to day job is to help a big Oil and Gas Enterprise to adopt cloud as the strategic platform. His key area of focus is to help customer migrate their line of business applications to Microsoft Azure. Application modernization is another aspect. This involves designing and implementing Serverless workflow and Microservices. He helps Architects to design and implement the solutions which are cloud scale", - "Speaker Links": "Twitter handle: @wrijugh\nBlog: https://blogs.technet.microsoft.com/wriju\nLinkedIn: https://www.linkedin.com/in/wrijughosh", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Wriju Ghosh (~wriju)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-and-automating-azure-with-python~eXXve/", - "title": "Managing and Automating Azure with Python" - }, - "130": { - "Content URLs": "I will share the slides on my github repo for the evaluation by the team in some days.\nOther content will be shared on github after the talk", - "Description": "Training a machine learning / deep learning model is one thing and deploying it to a production is completely different beast. Not only you have to deploy it to a production, but you will have to retrain the model every now and then and redeploy the updates. With many machine learning / deep learning projects / POCs running in parallel with multiple environments such as dev, test prod, managing model life cycle from training to deployment can quickly become overwhelming.\nIn this talk, I will discuss an approach to handle this complexity using Docker and Python.\nRough outline of the talk is, Introduction to the topic Problem statement Quick introduction to Docker Discussing the proposed architecture Alternative architecture using AWS infrastructure Demo", - "Last Updated": "28 May, 2018", - "Prerequisites": " Basic Python Basic Docker", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company.\nI have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures.\nSince past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "saurabh1deshpande", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-devops-and-ab-testing-using-docker-and-python~bWKEb/", - "title": "Machine Learning DevOps and A/B testing using docker and python" - }, - "131": { - "Content URLs": "https://speakerdeck.com/aravindputrevu/introduction-to-application-performance-monitorin", - "Description": "Often late, the time to debug that particular bug/issue occurring in production with respect to your application is increasing. It might also cause business disruption and affect your organization financially. In this talk, I'd explain how you could use Application Performance Monitoring to understand your application. Application Performance Monitoring (APM) is a solution built on Elastic Stack. APM helps you to build/store data points in Elasticsearch and visualize. It automatically collects information from your python application/service. This talk mainly targets at introducing the solution, why it is needed and what you can do with data. It ends with once data is stored within Elasticsearch, what else you can use the same data for (ex. Infrastructure Monitoring, Machine Learning)? Agenda What is APM?\nWhy APM?\nWhat it can do to your Application?\nDem", - "Last Updated": "28 May, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "Aravind is a loquacious person, who has something to talk about everything. He is passionate about evangelising technology, meeting developers and helping in solving their problems. He is a backend developer and has six years of development experience. Currently, he works as a Developer Advocate At Elastic and interact with developer community in South East Asia and India. He has deep interest in Machine Learning, Security Incident Analysis and IoT tech. In his free time, he plays around Raspi or a Arduino", - "Speaker Links": "https://aravindputrevu.in will have links to all my social accounts. I have been doing community work for last 3 years. Presenting the same talk at PyCon Bangkok on June 16-17. https://th.pycon.org/talks/#monitoring-your-python-applicatio", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aravind Putrevu (~aravind34)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-your-python-application~eV2ze/", - "title": "Monitoring your Python Application" - }, - "132": { - "Content URLs": "https://tools.ietf.org/html/rfc7047\nhttps://github.com/openstack/ovsdbapp\nhttp://www.openvswitch.org/support/dist-docs/ovsdb-server.1.htm", - "Description": "OpenvSwitch is an OpenFlow virtual switch implementation. It has its own database implementation based on JSON-RPC (https://tools.ietf.org/html/rfc7047) to store its internal state and data.\nThis session gives an overview of this database implementation and how it used in OVN, an SDN controller from the OpenvSwitch community and in OpenStack networking. This session will look\ninto how it is different from other traditional SQL databases and the python clients available to interact with the OVSDB server and the APIs it provides to carryout the CRUD operations with the OVSDB server", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of databases", - "Section": "Core python and Standard library", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": " https://numans.blog/about http://stackalytics.com/?metric=commits&release=all&user_id=numansiddique https://github.com/openvswitch/ovs/commits?author=numansiddique", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/openvswitch-database-based-on-json-rpc~dRKVe/", - "title": "OpenvSwitch Database based on JSON-RPC" - }, - "133": { - "Content URLs": "https://en.wikipedia.org/wiki/OpenFlow\nhttps://www.openvswitch.org/\nhttps://3vf60mmveq1g8vzn48q2o71a-wpengine.netdna-ssl.com/wp-content/uploads/2014/10/openflow-switch-v1.5.1.pd", - "Description": "Networking is a key aspect of any cloud infrastructure solution. All the VMs and containers\nspawned in a cloud deployment should have seemless layer 2 and layer 3 connectivity. All this is\npossible because of virtual switching and virtual routing. This session talks about what is OpenFlow specification, OpenvSwitch (which implements OpenFlow)\nand how it is used as an important SDN layer in cloud infrastructure solutions (taking OpenStack and OVN as an example)", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of networking", - "Section": "Networking and Security", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": "https://numans.blog/about/\nhttp://stackalytics.com/?metric=commits&release=all&user_id=numansiddique\nhttps://github.com/openvswitch/ovs/commits?author=numansiddiqu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-introduction-to-openflow-and-openvswitch~aQKGd/", - "title": "An introduction to OpenFlow and OpenvSwitch" - }, - "134": { - "Content URLs": "The repository where I have implemented concepts related to this talk https://github.com/tanayseven/http_quiz Contents for the presentation for the talk https://github.com/tanayseven/pycon_2018_python_web_app_tes", - "Description": "Abstract One of the first projects that I worked in the industry was in Flask . This talk is based on my experiences in the project with respect to the test suite and different things that I learnt in that. On the bases of those learnings, I started my own open source project on Github and enhanced on those ideas on how all the things necessary for testing are done. This is based on Flask as the web framework and all the ideas are implemented in it. The topics it covers are those things that you can do to achieve a robust set of tests in your code. Outline of the talk Pushing for 100% code coverage Making your test execution fast! The evil of \u2018over mocking\u2019 The necessity of using dependency injection Test Pyramid or Test Cone? TDDing while making changes Layers that make the web app architecture How does this map to UI testing", - "Last Updated": "27 May, 2018", - "Prerequisites": "Although most of the things are implemented in Flask, it is not necessary to know it, although it is very much recommended to know some web framework or having some knowledge of web app programming", - "Section": "Web development", - "Speaker Info": "A passionate developer with Python as his primary language. Have worked with Flask in the industry in the past. Passionate about testing and writing the code in a way that is very clean and maintainable. A strong believer in TDD and massive test coverage", - "Speaker Links": "https://tanayseven.com https://github.com/tanayseven https://www.linkedin.com/in/tanay-prabhudesai/ https://twitter.com/tanayseve", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanay PrabhuDesai (~tanay)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/having-a-robust-test-suite-for-your-python-web-app~dPKAb/", - "title": "Having a robust test suite for your Python web app" - }, - "135": { - "Content URLs": " Github reposistories: Keras_aud Audio-Vision Drive links: Content link : (Slides to be uploaded soon)", - "Description": "In this workshop, we will try to teach how to understand Deep Learning, various paths to follow, Domains to explore and the most important part- how to start with the paper selection and implementation. We will also learn how to deploy a simple model into production. This workshop aims at providing the attendees of all level a foundation of research and further prospectives in deep learning. Contents Paths and prospects in Industry and Academia (10 minutes) Difference between AI, ML, and DL. (5 minutes) Introduction to Deep Learning frameworks (Hands-on) (5 minutes) Paper selection (10 minutes) Implementation (Hands-on) (60 minutes) Understanding the dataset Feature Extraction Model Selection Data Formatting Comparison Demonstration of our work (General Overview) Audio Tagging Acoustic scene classification Visual Question Answering Publish/Deploy (Hands-on) (30 minutes) Stay Motivated Opportunites to explore The participants should have interest in Research. Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first-time learner\u2019s of AI to comprehend", - "Last Updated": "27 May, 2018", - "Prerequisites": "Preferred Basic Python concepts Basic knowledge about Machine Learning Algorithms. Preferred (but not necessary) Interest in working on Research problems Installed libraries: Keras Theano or Tensorflow", - "Section": "Data science", - "Speaker Info": "Aditya Arora and Akshita Gupta are currently final year semester exchange students at Indian Institute of Technology, Roorkee. They have been working on research problems using deep learning specifically in Audio processing and visual Q&A. Aditya is a member of various open source societies such as rust-community while Akshita has experience in Academia research and is a selected as an Outreachy intern at Mozilla 2018. They have been working in python for the past 4 years and have been moving forward working on Computer Vision and Audio processing problems", - "Speaker Links": " Twitter : https://twitter.com/imaarora Twitter : https://twitter.com/akshitac8 Linkeldn: https://linkedin.com/in/aditya-arora145/ Linkeldn: https://www.linkedin.com/in/akshita-gupta152/ Github : https://github.com/channelcs Blog : http://channelcs.github.io/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Akshita Gupta (~akshitac8)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-into-the-world-of-deep-learning~aOXRb/", - "title": "Deep Dive into the world of Deep Learning" - }, - "136": { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "The era of Artificial Intelligence is moving quite rapidly across the globe. It's being used in almost every application we know , from medical diagnosis to self driving cars and it's use is still growing exponentially. But should we blindly trust AI ? Is this technology robust enough? Are we capable enough to handle it's power? In this talk we will step back for a moment and look forward about the security issues and robustness of this technology. I'll be discussing the problems we can face , the precautions we have to take, etc. with the help of a famous problem, known as One Pixel Attack ", - "Last Updated": "25 May, 2018", - "Prerequisites": " A bit of Python Some knowledge of Machine Learning And a broader perspective ", - "Section": "Data science", - "Speaker Info": "The speaker, Srajan Kant Jha, is a final year B.E. student who has been working on Machine Learning and Data Science from quite a while now. Nonetheless, he pivoted from C/C++ to Python and during the transition, has also developed some projects on the same. He used to blog at his leisure time and is still on a venture to provide the knowledge of ML and Data Science to enthusiasts through a project site. Srajan is also the City Ambassador (and one of the speakers) of AI-Saturdays, which is a community of over 5000+ students(over 100+ cities) that helps people try their hands on Deep Learning and Artificial Intelligence, free of cost. Inspite of this, he still has a lot to discover in this growing industry. (Follow him on social media to know more", - "Speaker Links": " LinkedIn : https://www.linkedin.com/in/srajan-jha Github : http://github.com/srajan23 (not much updated) Facebook : https://www.facebook.com/srajan23", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Srajan Jha (~srajan)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-robust-is-artificial-intelligence-ai-using-python~dNK2e/", - "title": "How ROBUST is Artificial Intelligence ? ~ AI using Python" - }, - "137": { - "Content URLs": "Fo now, I just have a gist: But I will create a proper package before the event: https://gist.github.com/dhilipsiva/3d7586e7bb941919f28afa70ccc39dd", - "Description": "Microservices are fun. But what would make them even more fun to work with, is if we can avoid duplicating the data layer across your micro-services. Django ORM is amazing. Let's share the joy of Django ORM with other languages. I have written a tool to automatically expose Django ORM to other languages and which can also generate respective client libraries in other languages. I heavily rely on Protobuf and gRPC and a lot of AST parsing", - "Last Updated": "25 May, 2018", - "Prerequisites": "You will need to know basics of: Django ORM Protobuf gRPC (or cap'n proto or any other RPC framework) Microservices", - "Section": "Developer tools and Automation", - "Speaker Info": "Wannabe Astrophysicist. Full Stack + DevOps. I code for fun and profit. Mostly in Python. FOSS. Dad of 2. Environmentalist. Atheist. Story Teller", - "Speaker Links": " http://dhilipsiva.com/ https://twitter.com/dhilipsiva https://github.com/dhilipsiva/", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "dhilipsiva Dhilip (~dhilipsiva)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automagically-exposing-djagno-orm-over-grpc-for-microservices-written-in-other-languages~aMKmd/", - "title": "Automagically Exposing Djagno ORM over gRPC for microservices written in other languages" - }, - "138": { - "Content URLs": "will be sharing the slides after my talk as a Github repositor", - "Description": "AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment. CloudFormation allows you to use a simple JSON or YAML file to model and provision, in an automated and secure manner, all the resources needed for your applications across all regions and accounts. This file serves as the single source of truth for your cloud environment. In this talk, I will be using Python to generate the JSON and YAML files with which AWS CloudFormation can be done. During this talk I will be covering the below points What is AWS CloudFormation? Library in Python for AWS CloudFormation. What are S3 and EC2 AWS services. Creating basic S3(Simple Storage Service) and EC2(Elastic Compute Cloud) instance using Python. Installing MySQL in the EC2 instance.", - "Last Updated": "25 May, 2018", - "Prerequisites": "Basic Understanding of Python and how to use Libraries", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Mohan currently working as a Software Engineer at Amzur InfoTech Visakhapatnam.I have been in to Python Programming for the past 1 year. I have 2 years of experience as a Developer. I had worked on Data Migration. I am currently working on Data Science,MicroGrids Automation and AWS", - "Speaker Links": "www.linkedin.com/in/mohan-pavan-kumar-bailapudi-5628a296 https://github.com/MohanBailapud", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Mohan Bailapudi (~mohan57)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-cloudformation-with-python~dL1De/", - "title": "AWS CloudFormation with Python" - }, - "139": { - "Content URLs": "I'll share my slides after my talk as a GitHub repository", - "Description": "This talk is for Python enthusiasts who are interested in building test automation framework and test suites for REST API functional testing. It would throw a light on how to write useful, business-oriented and maintainable functional API test suites in Python on top of existing test frameworks like lemoncheesecake . Contents: About myself REST API and it's testing - A quick introduction Choosing a test framework to write your tests on Making API requests from Python Writing suite configuration and teardown code Introduction to the \"component-tests\" model for structuring the test code JSON parsing, use of matchers, asserts for writing test case validation criteria Importance of logging and reporting - How logs and readable reports can ease the job of debugging bugs found using tests Bringing everything together", - "Last Updated": "24 May, 2018", - "Prerequisites": " Python basics REST API basics Basics of test frameworks like pytest Passion for test automation", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm currently working as a SDET Lead with AgroStar, India's largest agri-tech platform for the Indian farmer. I'm passionate about technology and automation, I'm willing to contribute in building robust software test frameworks accompanied with some of the best industry practices like CI/CD that would help ensuring the best possible software quality from time-to-time. The \u201calways exploring and learning\u201d attitude is something that keeps me going", - "Speaker Links": " LinkedIn Facebook Twitter", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Akshay Maldhure (~akshay61)", - "created_on": "24 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rest-api-functional-testing-with-python~aK7Ga/", - "title": "REST API functional testing with Python" - }, - "140": { - "Description": "The Talk will focus on the importance of satellite image processing with main focus on the utilisation of GDAL library to conduct various operations on satellite data. Datasets will include Optical imagery and Synthetic Aperture Radar Imagery. The power of GDAL library alongwith numpy and matplotlib will be demonstrated. Brief analysis of satellite images using python will be given", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of numpy and matplotlib libraries", - "Section": "Data science", - "Speaker Info": "Shubham Sharma is a Junior Research fellow currently working on a collaborative project with Calibration and Validation Division of Space Applications Centre, ISRO, Ahmedabad. He has a rich experience in handling and processing of Synthetic Aperture Radar Images. Also, he has experience in building software tools in python for satellite Image analysis", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "shubham_thb", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/satellite-image-processing-with-python~dJKKe/", - "title": "Satellite Image Processing with Python" - }, - "141": { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Python is a versatile, powerful, and general purpose language, its easy and clear syntax makes it very popular for the beginner as well as the advanced programmer. Malware is one of the top threats to today's digital society. Due to heavy financial loss along with other infrastructure losses, the software industry is investing hue money for malware research and at the same time due to the wide need of effective and efficient anti-malware solution, the anti-virus industry is emphasizing on malware research.\nThis talk will focus on the array of python resources (script, modules, library, frameworks etc.) available for various dimensions of malware research. During the talk, I will share my experience with various tasks or problems related to malware research and how with the use of Python, those were solved. This talk will try to draw a parallel connection with various tasks related to malware research and suitable Python resources available for achieving those tasks. The talk will be supplemented with the brief explanation of concepts and python snippets for the same. \nSome of the modules and topics that I will touch upon are: yara Accessing VirusTotal API with Python Cuckoo-sandbox Androguard pefile pyew file type filtration ClamAV and pyClamd etc.", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general", - "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-arsenal-for-malware-research~dGXKe/", - "title": "Python Arsenal for Malware Research" - }, - "142": { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Malware is a serious threat to all kind of Cyberinfrastructure. Since the first known malware (formerly or generally known as Virus) there have been malware detection techniques. There is the arms race between new incoming of Malware and defense against it. Traditionally, anti-virus software uses signature-based techniques to detect malware and protect the underlying system. Due to some critical limitations of signature-based techniques, anti-virus, and security agency looking for alternative techniques and investing in machine learning based techniques for malware detection.\nThis workshop aimed to train the participants through various steps involved in building malware classifier based on machine learning algorithms. Python is very suitable for the task due to its large number of useful modules suitable for each and every step. During this workshop, following topics will be explained with proper hands-on using Python. Explanation of the topic and draw out the various required steps. Data collection: How to collect Malware and Benign samples for the experiment. Pre-processing: How to carry out various pre-processing tasks\n (duplicate removal, file type identification etc.) to prepare the suitable dataset for the experiment. Labeling: How to label the sample i.e. malware v/s benign. (Required\n for supervised learning.) Feature extraction: How to extract features from the sample and\n build the proper representation of features to be used with various\n Machine learning algorithms. (We will restrict to static features\n for this workshop). Model training and Testing: How to train various machine learning\n algorithms and test their performance to select the best model. Making model persistence: How to make the selected model persistence\n to further use. ", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general. Required module/library:\n1. pefile\n2. androguard\n3. scikit-learn\n4. CS", - "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-malware-classifier-from-sample-collection-to-persistance-model-using-python~eEXWd/", - "title": "Building Malware Classifier: From Sample Collection to Persistance Model using Python" - }, - "143": { - "Content URLs": " The main sunpy website - SunPy.org The code repository - sunpy My Experience with working on the SunPy project - Blog SunPy Gallery - Examples My Contributions to the SunPy Project - Code + Examples Contribution", - "Description": "There is plenty much research going on locating sunspot regions or potential regions of high solar density from the solar data collected from observatories like AIA or SDO. Solar Physicists mainly use IDL as a programming language for analyzing such solar data, but using IDL has its demerits due to its less popularity and complexity. So how using python we can benefit the astrophysics and helio-physics community to query solar data and analyze them much more efficiently and produce much more insightful results ? In this talk we will be discussing how we can analyze sunspots and solar flares through image-processing tools using a python package called sunpy . A small example Locating Solar Spikes in the solar Map Original observed AIA image After locating such region", - "Last Updated": "22 May, 2018", - "Prerequisites": " Knowledge of Python (Beginner/ Intermediate) Little bit knowledge about the sunpy package (not mandatory) Python modules like scipy and matplotlib since there is heavy use of this two modules. A lot of excitement and passion for open science", - "Section": "Data science", - "Speaker Info": "Prateek has been an open source enthusiast for the past 2 years with a deep love in the field of astronomy and helio-physics . He is currently an undergraduate in computer science also a GitHub Campus Expert working directly with GitHub Education to build open source communities and support them on campus. He is a core contributor to the SunPy project which is lead by researchers at the NASA Goddard Space Flight Center. He has worked with the community for past 1 year and has his name published for more than 10 releases along with researchers at NASA and others in the community", - "Speaker Links": " GitHub Profile - prateekiiest Twitter - prateekiiest Website - prateekiiest,github.io GitHub Campus Expert - prateekiiest @campus_expert Blog - Medium", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Prateek Chanda (~prateekiiest)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/predicting-sunspots-and-solar-flares-with-a-tinge-of-python~dBXQa/", - "title": "Predicting Sunspots and Solar Flares with a tinge of Python" - }, - "144": { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "RabbitMQ is a powerful messaging broker based on the Advanced Message Queueing Protocol (AMQP). Microservices do what they say on the tin. They\u2019re small, isolated services that represent an equally small portion of your business domain. Recently there's a trend to build an application using Microservices which place an emphasis on small processes. As an increase in Microservices, we need to a mechanism where we could use some channel(Pub-Sub) to talk between these Services. Contents 1) Introduction to RabbitMQ and Its Terminology 2) Microservices using Pub-Sub 3) Sample Execution At the end of this session, participants will be able to use the rabbitMQ for there application(Could be ETL's/ MicroServices etc", - "Last Updated": "22 May, 2018", - "Prerequisites": "1) Basic Pytho", - "Section": "Others", - "Speaker Info": "My name is Jigar Shah. I have completed my BTech from Walchand College of Engg Sangli. I am currently working as a Software Developer @Browserstack. Interests: Building Backend Architecture, System Design, Data Structures, Algorithms More Inf", - "Speaker Links": "Github Linkedl", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Jigar Shah (~jigarshahindia)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rabbitmq-in-python-for-event-based-communication-between-microservices~az4qd/", - "title": "RabbitMQ in Python for event-based communication between MicroServices" - }, - "145": { - "Content URLs": " Will share my slides after my talk as a Github repository.", - "Description": " Abstract This talk is for Python web developers interested in learning what are\nthe core ideas behind microservices, what problems they try to solve,\nand what are the viable options to implement them in Python, both from\ntechnical and teamwork point of views. Some of the topics that will be\ndiscussed include the role of APIs, the improvements microservices\nbring to application scalability, upgrades, and maintenance, and the\nchallenges in breaking up a monolithic application. Contents of the talk About me - Basic introduction of myself. What are Microservices? Monolithic Python Web Application. Problems with Monoliths. Microservice Example. Advantages of Microservices. Disadvantages of Microservices. How to refactor a monolithic application into microservices? ", - "Last Updated": "22 May, 2018", - "Prerequisites": " Basic Python", - "Section": "Core python and Standard library", - "Speaker Info": " My name is Kasam Sharif (Passionate Programmer | Startup Enthusiast |\nProblem Solver). I am currently Software Engineer at Agrostar, Pune.\nPreviously was working at Symantec having 3 year of experience in IT\nindustry. In free time love to learn new things.", - "Speaker Links": " Linkedln : https://www.linkedin.com/in/kasam-sharif-2027628b/ Twitter: https://twitter.com/kasam_sharif94 Github: https://github.com/kasamsharif", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kasam Sharif (~kasamsharif)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-microservices~dyA6d/", - "title": "Python Microservices" - }, - "146": { - "Description": "Many at times, we need to encapsulate our core logic in order to protect it from being reverse engineered and being exploited. Having a strong IP may not be the only protection. Once the code is open for the analysts, they can easily implement a modified version to achieve their goals. Some areas where the code obfuscation plays an important role are financial domain, security, web/mobile. Many times developers / teams fail to achieve the right level of code obfuscation which in turn fails to provide the level of protection to their code. We will be walking through the existing code obfuscation techniques in python and the level of protection they offer. I will be sharing my experiments and learnings during the journey to achieve a better obfuscation mechanism for python code", - "Last Updated": "22 May, 2018", - "Prerequisites": "Required : None. As we will be covering the required basic for code obfuscation in the talk it self. Good to have : Understanding the python run time process and how the code gets converted to executable binaries can be helpful", - "Section": "Core python and Standard library", - "Speaker Info": "I am Kailash, currently working as a Senior Software Engineer in Visa. I have been into python programming for the past 6 years now. I had worked on multiple levels of python projects ranging from scripting and automation, DevOps, Machine Learning, Computer Vision, Algorithmic Trading, Website Backends", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Venkata Naga Kailash Anantha (~avnkailash)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/effective-code-obfuscation-protecting-your-python-code-from-being-copied-reverse-engineered~axzld/", - "title": "Effective Code Obfuscation : Protecting your python code from being copied / reverse-engineered" - }, - "147": { - "Content URLs": "wikipedia article on the brain computer interface Text Summarizer neural network model code is in the following lin", - "Description": "Brain Mapping Using Python: Over the past few years, machine learning and artificial intelligence has been making headlines and advancing quickly by creating products that can make optimistic decisions. Now this machine learning technology can be implemented in making a machine which can perform complex actions just like in brain which can make human life easier. Now the real challenge is can we create a neural network model which can perform complex\nactions like human brain? How Python can be used to accomplish this task and how far we can achieve this feat?\nThis talk will be focusing on the methods approached by brain to generate conclusions or make decisions which can be replicated in computers and generate results. Contents of the talk About me - Basic introduction of myself. What is Brain Mapping? Functionalities of Human Brain. Neural Networks Using Python. Types of Data Summarisation techniques in Python. How Computers can make decisions. What can we expect from Brain Mapping in future.", - "Last Updated": "21 May, 2018", - "Prerequisites": " basic syntax knowledge of python basic machine learning terminology neural network models functionality", - "Section": "Data science", - "Speaker Info": " ROHITH PUDARI Rohith is a B Tech student who is passionate about integrating the most complex organ known to human which is brain with computers. He is winner of the Hyderabad best coder championship conducted by JNTUH. He is one of the few persons in India who is selected for the google Udacity scholarship. He is always interested in decreasing the interaction gap between computers and humans and started his research in creating an interface which will allow humans to interact with computers in a more natural way. He created a neural network model which generates a summary of a given essay which won the title \"Best innovative idea\" at IIT Kanpur", - "Speaker Links": "you can see the projects and previous work of Rohith in the following link to his github profile. and linkedIn profile Rohith contributed to the following open source projects: Atom- open source code Editor OpenWISP- software platform that implements a complete Wi-Fi service Sugar Labs- desktop environment and learning platform Sustainable Computing Research Group (SCoRe)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "dvlpr_rohith", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/brain-mapping-with-python~bonYa/", - "title": "Brain Mapping with Python" - }, - "148": { - "Description": "In this talk the main aim is to demystify data science and introduce the audience with the concepts of data science and machine learning in python. Goals : What is Data Science ? What is Machine Learning ? Why Python for Data Science ? How to solve a Real world problem with data science ?", - "Last Updated": "21 May, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Data science", - "Speaker Info": "Jatin Ahuja is a self taught data scientist and machine learning practitioner. He's currently working in Data Science domain . He's the core team member (designated as PR Director) and city ambassador of AI Saturdays which is a community of over 5000+ students(over 100+ cities) to spread the knowledge of AI free of cost. He actively blogs about machine learning in his personal blog site named as everythingai . He mentors the aspirants in their journey to become a successful data scientist , machine learning engineer or deep learning engineer at MentorCruise.com ", - "Speaker Links": " Website ; https://everythingai.co.in Github : https://github.com/A-Jatin LinkedIn : https://linkedin.com/in/jatin-ahuja-89677614a/ ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "JATIN AHUJA (~jatin)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-science-with-python~enm5d/", - "title": "Data Science with python" - }, - "149": { - "Content URLs": "https://github.com/atulsinghphd/NL", - "Description": "In this hands-on course using Python, we will learn how to use machine learning for Natural Language Processing (NLP) through interactive notebooks. Natural Language Processing (NLP) is a field that covers computer understanding and manipulation of human language. Machine learning is a branch of Artificial Intelligence that focuses on the ability to automatically learn from existing information. Language processing uses models that attempt to understand and represent the information at various levels that includes morphology, syntax, semantics, pragmatics and discourse. In this training, we will learn how to use machine learning to build these models. This training includes the following topics: Representing text as a vector using count, TF-IDF and co-occurrence matrix Detecting similar documents Sentiment Analysis Identifying the themes in a set of documents Extracting the entities and the relationship between the entities (stretch goal depending on time) The course will introduce the participants to NLP libraries such as nltk, gensim and Spacy", - "Last Updated": "21 May, 2018", - "Prerequisites": "This is an advanced machine learning course. To benefit from this course the participants are expected to have:\n1. Understanding of supervised and unsupervised machine learning \n2. Knowledge of python, or a high-level programming language like Java or C#.\n3. Using jupyter Python notebook environmen", - "Section": "Data science", - "Speaker Info": "Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), geo-spatial analytics, and reinforcement learning. Sasidhar Donaparthi I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company", - "Speaker Links": "Linkedin Profiles https://www.linkedin.com/in/sasidonaparthi https://www.linkedin.com/in/atulsinghphd/ Twitter Profiles @sdonapa", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Atul Singh (~atul98)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deciphering-human-language-using-machine-learning~bm0Ra/", - "title": "Deciphering human language using Machine Learning" - }, - "150": { - "Content URLs": "I will post presentation and Relevant codes soon on github. For reference please find the code here :\nhttp://magneplane.readthedocs.io/en/latest/index.htm", - "Description": "Content of My talk will have : Hyperloop : An Introduction How Python plays an Important role? Python Applications in the Project: Project Management, \nScripting the repeating processes, \nPython - ML in CFD, \nRaspberry Pi in Communications.", - "Last Updated": "20 May, 2018", - "Prerequisites": "An intermediate level knowledge of Python Knowledge of a Python and basic Math", - "Section": "Others", - "Speaker Info": "Suyash Singh is post graduate Student of Indian Institute of Technology, Madras Chennai. He is Head of Team Avishkar Hyperloop More Details about Avishkar Hyperloop : http://avishkarhyperloop.com/ He carries 4 years of work experience in Big Data and Data Science. Later his interest in fifth mode of transportation took him to IIT Madras. He has been pure pythonist. He has been a adviser to two small scale startups based out of Indore which deals with data science. He has a vision of transforming Transportation making it more efficient. He thinks Python will be an important tool to make it possible", - "Speaker Links": "LinkedIn Profile: https://linkedin.com/in/suyashao", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Suyash Singh (~suyash_singh)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hyperloop-how-python-helps-building-fifth-mode-of-transportation~el6jb/", - "title": "Hyperloop : How Python helps Building fifth mode of Transportation?" - }, - "151": { - "Content URLs": " Slides on Introduction to NLP : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction%20to%20NLP%20%26%20Spacy.pdf Jupyter Notebook : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction.ipynb Note : The above slides are not complete and are suited for a quick introduction to NLP in 20 mins I will be introducing the following Libraries (and use them to create chatbots) NLTK : https://www.nltk.org/ SpaCy : https://spacy.io/ I will be developing a bot on the following Chat Platforms with emphasis on Messenger: Messenger : https://developers.facebook.com/docs/messenger-platform/ Slack : https://api.slack.com/ Telegram : https://core.telegram.org/bots", - "Description": "Introduction to NLP Natural Language Processing is a prominent field in Artificial Intelligence that deals with parsing and understand Natural language, (an ordinary language such as English is any language that has evolved naturally in humans through use). NLP lies at the core of Google Duplex and other smart assistants that respond to questions in English and natural languages. I will be explaining the following : Corpus and Datasets Processing and tokenizing Text Tagging, Stemming and Lemmatizing Words WordNet Introduction to libraries NLTK Spacy Sentiment Analysis Word Embedding using BOW and word2vec Developing Chatbots With rising need for customer support, Chatbot are one of the most common applications of NLP. These are applications that are trained conversation with a human by answering some preset list of questions. I will be developing a chatbot on three platforms : Messenger (Facebook) Slack Telegram These will be deployed locally using Django with ngrok for tunneling. Additionally, due to the immense popularity of Messenger, I'll be also explaining the different message templates and other features that Messenger has. If you'd like to see me cover another platform such as Discord, Skype, Google Assistant or Alexa, feel free to drop a commen", - "Last Updated": "20 May, 2018", - "Prerequisites": "Basic knowledge of Python, English Grammar and HTTP Requests", - "Section": "Others", - "Speaker Info": "About me Hello world. I\u2019m Vishal Gupta, a 3rd yr CSE undergrad at SSN, Chennai, India. \nWhile most people generally pick up a topic, or a concept (like say Computer Vision, Big Data, or just Algorithms), understand it and aspire to excel at it\u2026 I fell in love with a language, Python. As someone who has started out by learning C++ in school, learning Python was as easy as surprising. The speed at which I could translate ideas to code was amazing, and oh boy, all I wanted to do was make things, write simple scripts to automate everyday tasks. And hence I continued to explore Python, the countless modules and possibilities with Python. I went to Hackathons, won some but more importantly made something that others could use. Chatbots and me UI/UX has never been my strong suit but Chatbots made it simple to use serve any application in a conversational manner. Over the last 2 years, I have developed over a dozen chatbot for a variety of purposes, from fetching torrent links to code education to keeping track of events. One of my best messenger chatbots is still functional with nearly ~500 subscriptions. PyGeon , scrapes a number of sites everyday for developer events such as meetups, hackathons and contests in 7 indian cities. Newly added events are sent to users every day. Experience : Chatbot intern at GoBumpr , Chennai CV intern at XR Labs , Chennai NLP intern at BicycleAI Google Summer of Code participant with Debian", - "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Vishal Gupta (~vishal11)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-nlp-and-chatbots~bkMJe/", - "title": "Introduction to NLP and Chatbots" - }, - "152": { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "Abstract In this talk, I would be telling people how to write better and faster Python. I've been developing Python programs, scripts and softwares for over 2 years now and I come across people who have a problem of Python being slow. \nWhenever someone has to write a faster python code they are left with one option of just shifting their entire code from Python to C or C++. This talk will clear that misconception. People can actually write faster codes in Python, the only missing fact is how? . And this is exactly why I am interested to give this talk. Contents of the talk The talk will start with a basic introduction of myself as a Python developer. I will then talk about the misconception about shifting the code to C or C++. Then I will proceed onto some basic usage of Python Programming Language. Introduction to optimization techniques in Python. Then I will talk about when and why should one optimize their application. I will introduce the basic concepts of optimization in Python. Tell people about the available/built-in functions that can come in handy. Then I will proceed onto giving a demonstration on 'Writing better functions'. The talk will conclude with some examples of optimized code that performs better than conventional approaches. The talk will be open to questions, to make it more interactive and fun. The slides will be shared to the audience after the talk", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Will to learn See, It does not require much", - "Section": "Core python and Standard library", - "Speaker Info": "My name is Manish Devgan . I am a second year Information Technology student at Netaji Subhas Institute of Technology, Delhi . I am an Open Source Contributor and a learner . I have contributed to various different open source projects and won many hackathons . I was FOSSASIA Codeheat 2017 - Grand Prize Winner and Google Code-In 2017- Mentor . Currently I am a GSoC 2018 Student under FOSSASIA and RGSoC 2018 - Coach . I have contributed to Python's ChatterBot Machine Learning Engine , variety of FOSSASIA's Projects , and a wide variety of OSS projects like Github Linguist etc. Python is my favourite programming language . From writing small scripts to building small Machine Learning libraries , I've tried a lot :", - "Speaker Links": " https://github.com/gabru-md https://twitter.com/gabru_md https://facebook.com/gabrumd https://www.linkedin.com/in/gabru-md/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Manish Devgan (~gabru-md)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-faster-python-optimizing-your-code~ejJye/", - "title": "Writing Faster Python : Optimizing your code" - }, - "153": { - "Content URLs": "Few resources that I will be using in the workshop. https://github.com/koshikraj/proof-of-ownership https://github.com/koshikraj/neo-python-contracts", - "Description": "Bitcoin has been gaining popularity in the recent years due to its market value. But more importantly, the underlying technology is gaining the attention among the developers. Many developer communities inspired by bitcoin have created their own platform to use the underlying technology widely known as \"blockchain\" to achieve decentralization. Ethereum is one such platform that has created a blockchain platform which allows developers to develop their own decentralized applications (dApps) in the ethereum network by coding the logic in the execulatable contracts called \"smart contracts\" . Although ethereum has gained a huge fame due to its smart contract implementation to create decentralized applications, it imposes developer to write the logic in an ethereum's domain-specific language called Solidity. In addition to coding in a new language, it mandates the developer to set up a new develop environment. NEO blockchain platform provides a convenient way to develop smart contracts in general purpose programming language. NEO achieves this by providing compilers to compile code written in most of the languages to bytecode that can be executed in NEO virtual machine. Currently, NEO allows compilation of python smart contracts through neo-python project. This is the first blockchain project to provide such a freedom to the developer. NEO project provides plenty of benefits over other blockchain platforms out there. \nIt plans to achieve smart economy by creating a strong digital identity. It achieves faster transaction rate which is the key to scale any platform. NEO is being referred to as the \"New Ethereum\" due to its increasing popularity. I plan on conducting a workshop to create a decentralized application by developing and deploying smart contract using neo-python. Following would be the agenda of the workshop. Introduction to Bitcoin, Blockchain, and consensus to achieve decentralization. (30 mins) Introduction to NEO and Setting up a NEO platform (30 mins) Creating and deploying Hello World contract using Python (15 mins) Creating a Proof of Ownership system (30 mins) Creating a user interface to create a complete Proof of Ownership DApp. (20 mins) Creating an Initial Coin Offering (ICO) using an existing template and Q&A (25 mins) ** This is a rough estimation of time and topics as of now. I will try to fit more topics if possible. An attendee will be able to create an asset management DApp such as document ownership system or launch a basic ICO after attending the workshop", - "Last Updated": "20 May, 2018", - "Prerequisites": " Novice level experience in python programming. Basic knowledge of how bitcoin or blockchain technology is\n implemented would help to grasp the topic pretty well. Although I will be using Ubuntu Linux distribution for the demo, Attendees can use any platform which has python 3.6 installed. Windows users might have to install a docker container manager as installation might create some issues.", - "Section": "Networking and Security", - "Speaker Info": " I completed my masters in Computer science and Information Security after getting fascinated by the security and cryptography field. I have a demonstrated history of working in the computer and network security industry (RSA Security) where I had worked for more than a year. I worked as a senior fullstack developer for a start-up called CoWrks. In the meantime, I got involved in the blockchain and decentralized application. I started devoting my entire time to blockchain and I'm currently writing a research book on the blockchain technology called Foundations of Blockchain", - "Speaker Links": " My Linkedin profile. Few of my opensource contributions. My semi active social profile. Check out my detailed bio at koshikraj.com", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Koshik Raj (~koshikraj)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-decentralized-smart-contracts-using-python~egXra/", - "title": "Creating decentralized smart contracts using Python" - }, - "154": { - "Content URLs": " https://github.com/rahulkumaran/Telegram-Syntaxdb-bot There will be some slides that I'll prepare too but most of it is going to be an explanation from the GitHub repo and my talk https://github.com/python-telegram-bot/python-telegram-bot https://syntaxdb.com https://syntaxdb.com/api/v1 https://core.telegram.org/api", - "Description": "In this particular topic, I'll basically be telling people about how easy it is to create a Telegram Bot. The reason I'm interested in taking this up is because there are people who develop beautiful things and might want to let people to use it even on a mobile interface. The problem is not everyone's good with app development. So in such cases, deploying the beautiful things in the form of a bot would be a great idea. Bots can be of 2 types : Conversational Command based I'll be taking up the command based bot to help people get a feeling of this topic. Also, through the example I'll be giving, I'll try to make people understand as to what APIs are and how to use existing one. Later I'll show them how to create your own Python APIs because APIs make lives easier for programmers and it's always a good practise to know how to create an API as you never know when someone else might need it. CONTENTS AND ORDER OF THE TALK I'll be starting off with an introduction about myself and then I'll move on to what are bots. I'll then be explaining about why we could probably use these bots on Telegram, Discord, Slack and so on. Thereafter I'll be talking about the Telegram API for Python to help you interact with the bot and telling you how to use it. Before this, I'll show them how to prepare a bot on Telegram and get the Token. After this, I'll be talking about the importance of an API and utilizing existing ones as it makes your job much simpler. Slowly, I'll shift my focus on to how to build an API. I'll be explaining this using an example. Then using the Telegram Bot API and the API we build for Syntaxdb.com, we'll be creating a Telegram bot. Lastly, I'll summarise and entire talk and will take up a couple of questions. The entire talk will be based on a GitHub repository. The code links will be given to everyone for future reference", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Usage of libraries in Python", - "Section": "Others", - "Speaker Info": "The speaker, in this case is me, Rahul Arulkumaran . I'm an engineering undergrad currently going into my 3rd year. I'm also the Founder of the startup Free Flow . We still haven't registered it yet though. I started learning how to code when I came into engineering and Python was the first language I learnt. I never really developed anything until last year. It was after creating my first application that I got the interest to develop more using Python. From then to now, I've learnt a lot. I might not be an expert but yes, for my age, I think I'm better than most others. I'm also the President of the Computer Science Club, Enigma in my college Mahindra Ecole Centrale . I'm a Python developer and an open source enthusiast . I also am a Contributing and Managing member of PSF . I work on a lot of open source projects I love learning anything and everything related to coding. I'm also a Machine Learning and Data Science enthusiast ", - "Speaker Links": " https://rahulkumaran.github.io https://github.com/rahulkumaran https://www.linkedin.com/in/rahul-arulkumaran-101a63127", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-and-working-with-apis-to-develop-a-telegram-bot~dwgXd/", - "title": "Creating and working with APIs to develop a Telegram Bot" - }, - "155": { - "Content URLs": "(Slides to be uploaded soon", - "Description": "In computer vision, object detection is scanning and searching for an object in an image or a video (which is just sequence of images). Whereas, object tracking is like you are spying on someone and following it. Done in motion images like in animated gifs or videos, we want to track how an object is moving, where is it going, or its speed. Although it has been studied for dozens of years, object detection and tracking remains an open research problem . The difficulty level of this problem highly depends on how you define the object to be detected and tracked. If only a few visual features, such as a specific color, are used as representation of an object, it is fairly easy to identify all pixels with same color as the object. On the other extremity, the face of a specific person, which full of perceptual details and interfering information such as different poses and illumination, is very hard to be accurately detected, recognized and tracked. Thus, I believe it is important to address such challenges via a comparative study of object tracking and object detection in python. Here, I aim to present my own experience in tackling the problems while I tested different algorithms for the same", - "Last Updated": "19 May, 2018", - "Prerequisites": "Basic understanding of pytho", - "Section": "Data science", - "Speaker Info": "Anand Zutshi is currently pursuing his undergraduate B.E. degree from Netaji Subhas Institute Of Technology, Delhi. He has experience in developing and testing basic as well as advanced algorithms in C, C++. He has experience in developing a Learning Management System which uses dynamically trained neural network for scoring its users, and a LDA based tagging in its queries. He has in depth knowledge of Natural Language Processing, mainly with emphasis on word sense disambiguation and language models. His recent work of interest primarily focusses on object detection and object tracking in Python and sound classification and recognition. Currently, he is working on testing a biometric database management system along with predicting self and non-self processes in Operating system using Neural Networks", - "Speaker Links": "https://github.com/zutshianan", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "anand zutshi (~anand09)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-tracking-vs-object-detection-a-comparative-analysis~avJna/", - "title": "Object tracking vs Object detection- a comparative analysis" - }, - "156": { - "Content URLs": " https://pytorch.org/docs/stable/index.html Slides (to be uploaded soon)", - "Description": "Talk Abstract This talk aims to introduce Facebook's Deep Learning library - PyTorch. PyTorch is increasing becoming popular due to it's powerful features and shallow learning curve, making it accessible and easy to use to a larger community. This talk discusses about the 'Autograd' package, which is central to all neural networks in PyTorch. It also entails details about the different features and functionalities of PyTorch as well as equip the audience on how to create simple and complex Neural Networks in PyTorch. PyTorch helps to create dynamic computation graphs that allow you to change how the network behaves on the fly unlike static computation graphs. It offers modularity which enhances the ability to debug or see within the network. Outline of the Talk The talk will be broadly divided into 3 broad parts. Part 1 will be an Introduction to PyTorch. This part will focus on the use and need for PyTorch as a deep learning framework. This will be followed by instructions on how to setup PyTorch and a look at the basic building blocks behind the framework. Part 2 will dive more into the features of PyTorch, mainly it's AutoGrad package which lies at the heart of all Neural Networks created in PyTorch and PyTorch's ability to create dynamic computational graphs as opposed to the static computational graphs offered by some of it's counterparts (such as TensorFlow and Caffe). Part 3 will be a more 'hands on' part where the talk will focus on how to create and build simple as well as complex neural networks (such as Convolutional Neural Networks) with the framework", - "Last Updated": "19 May, 2018", - "Prerequisites": " A basic understanding of how Neural Networks work would be beneficial. Some knowledge about Numpy.", - "Section": "Data science", - "Speaker Info": "I am Rahul Baboota, a 3rd Year Undergraduate in India studying Computer Science and Engineering. I have an avid interest in the domain of Data Science, Machine Learning and Deep Learning. I have worked at various Data Science and Machine Learning based startups and labs. In my freshmen year, I worked at a data journalism startup to create and analyze smart data stories. I was also a part of a project funded by the Government of India for the development of a social media based analytics tool for the analysis of healthcare and nutrition in India. I am currently working at the Center for Artificial Intelligence at IIITD in the Autonomous Vehicle Lab 'Swarath'", - "Speaker Links": " https://www.linkedin.com/in/rahulbaboota/ https://github.com/RahulBaboota", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "rahul baboota (~rahul93)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/throwing-light-on-pytorch~er7La/", - "title": "Throwing Light on PyTorch" - }, - "157": { - "Content URLs": "This talk is going to be based on a series of blog posts I have written about the same topic - Python Project Workflows - Part 1 Python Project Workflows - Part 2 (Pipenv) Python Project Workflows - Part 3 (pylint)", - "Description": " Have conflicting dependencies (unpleasantly) surprised you? (Darn: It worked on my laptop!) Do deterministic builds matter? What about those run-time errors, which were a typo while accessing an attribute of a class? Has the codebase already started smelling a bit? Unit tests and what about Dockerization? Typically, when your Python project grows beyond a few modules and your team size is more than a couple of developers, having the right tools built into your project development workflow saves one from a lot of surprises (and perhaps late night calls). In this talk, we start with challenges typically seen in Python Projects and look at ways of overcoming them, so that the velocity of code deployment increases. Specifically we are going to be looking at tools that are out there that allow you to - Properly track dependencies ( pip , virtualenv and the new Pipenv ) Have a separate Dev and Production environment - so that dependencies in Dev environment don't spill into Production environment. Ensure that the builds are deterministic (across developer/build machines and time.) Enforce certain coding guidelines and capture the potential 'run-time' errors right during the development ( pylint ) and Eventually Dockerize your application.", - "Last Updated": "19 May, 2018", - "Prerequisites": "It's an intermediate level talk where you have already done some Python development and are at a point where you want to package, distribute or deploy your pet Project. If you are a beginner in Python, but have been involved in build/release of packages in any other languages, likely this talk is for you. If you do an equivalent of sudo pip install or sudo apt-get install when you want to download and use package foo , chances are you will benefit from this talk quite a bit", - "Section": "Developer tools and Automation", - "Speaker Info": "Running a Consulting Company 'hyphenOs Software Labs' in Pune, India. Python/Go programmer - Mostly for things that pay the bills and ideas that I want to try out. Datacenter Networking Enthusiast (hacking a yet another Container Networking technology, borrowing ideas from different Projects) Eternally grateful to whoever wrote tcpdump and the new Wireshark . Number of problems solved using these tools could run into triple digits. Hates trailing white spaces in a file.", - "Speaker Links": " Stack Overflow Github LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Abhijit Gadgil (~gabhijit)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-project-workflows-continuous-deployment-friendly~bq8ya/", - "title": "Python Project Workflows - Continuous Deployment Friendly" - }, - "158": { - "Content URLs": ">>> import thi", - "Description": "Tim Peters preached and we memorized that Explicit is better than implicit, but how many understood the deeper meaning enough to imbibe the essence of the zen? In this 20 min talk, we shall go through the zen and look at live examples where the golden words make a programmer's life easy", - "Last Updated": "19 May, 2018", - "Prerequisites": "Familiarity with the syntax of Python", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has spent countless hours wading through utterly un-pythonic, non-modular codebases that contain > 8000 lines in one file and >500 in one function, with nested try-except statements and has almost mastered the skill of keeping his calm and understanding even that", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-python-with-real-life-examples~epVyb/", - "title": "The Zen Of Python: with real life examples" - }, - "159": { - "Content URLs": "Slides: https://docs.google.com/presentation/d/1aE0QmLDffyGRvChqhxaSUWEtBkDqZH5NR3in5FBOPlc/edit?usp=sharing Most of the snippets and concepts to be discussed are taken from various resources I came across during my 6 months long research about Python. I have collected such snippets in a project called \"What the f*ck Python!\". Here's the source: https://github.com/satwikkansal/wtfpytho", - "Description": "Do you know that, 'a'[0][0][0][0][0] is a semantically valid statement in Python. print(r\"\\ some string\") is a valid statement, but print(r\"\\ some string \\\") raises a SyntaxError . print('wtfpython''') is valid but print(\"wtfpython\"\"\") raises SyntaxError . Do you know why, >>> a = \"some_string\"\n>>> id(a)\n140420665652016\n>>> id(\"some\" + \"_\" + \"string\")\n140420665652016 the id of both the objects in above snippet is same? And do you know why, >>> timeit.timeit(\"s1 = s1 + s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.25748300552368164\n# using \"+=\", three strings:\n>>> timeit.timeit(\"s1 += s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.012188911437988281 s1 = s1 + s2 + s3 is much slower than s1 += s2 + s3 . And finally, >>> 'a' * 20 is 'aaaaaaaaaaaaaaaaaaaa'\nTrue\n>>> 'a' * 21 is 'aaaaaaaaaaaaaaaaaaaaa'\nFalse\n\n# one last attack!\n>>> a = \"wtf\"\n>>> b = \"wtf\"\n>>> a is b\nTrue\n\n>>> a = \"wtf!\"\n>>> b = \"wtf!\"\n>>> a is b\nFalse\n\n>>> a, b = \"wtf!\", \"wtf!\"\n>>> a is b\nTrue Do you know the reason behind all the above-discussed facts and snippets? Some of them are really puzzling, right? I felt the same when I first came across all these intricacies. But don't worry, such behaviors, are mostly the consequences of strings being [immutable] [sequences] in Python. In this talk we'll be going through the concepts behind such snippets in detail, so that next time when you see such examples, the answer seems natural to you. Finally, we'll try to answer some interesting questions like, How does string concatenation work? What's the best way of building large strings in Python? (It may actually depend on your use-case) What happens when you multiply a string by a boolean? How strings in Python differ from strings in other languages like JavaScript, C++? and many more", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic familiarity with programming. Prior experience with Python would make the talk more interesting for the attendee", - "Section": "Core python and Standard library", - "Speaker Info": "I'm a Software Developer experienced with Decentralized Applications and Data Science. In my leisure time, I love doing pointless things with programming. Currently on a quest to learn as much as I could about Computer Science. And lastly, I prefer all things Python! (A humble brag ", - "Speaker Links": "Website | Github | Archives Past Speaking Experience PyCon India 2017 (Speaker for a DevSprint ) EuroPython 2017 ( Invited as a Speaker for a workshop , unable to attend though) IWD-Delhi 2018 ( Speaker ) OSS DTU (Instructor and moderator)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Satwik Kansal (~satwik)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/do-you-really-think-you-know-strings-in-python~boJLa/", - "title": "Do you really think you know strings in Python?" - }, - "160": { - "Content URLs": " https://docs.julialang.org/en/release-0.4/ https://julialang.org/ Ppt (soon)", - "Description": "Julia Programming Language The Julia programming language is proving to be a new paradigm shift in the data science community due to it's easy to pick up syntax like python but and execution speed equivalent to C , this is possible due to flexible types and JIT compiler. The speed and user-friendliness are only some of its good parts. This talk delves deeper into understanding, how can Julia be the next language on your learning list. Outcomes of the talk What is Julia? How can I get it into my daily workflow What Julia offers that Python does not Understanding benefits of shifting to Julia How can a python-ista shift to Julia", - "Last Updated": "18 May, 2018", - "Prerequisites": " Laptop with Julia up and running", - "Section": "Others", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a recently born Julia-n, I do a lot of code in Julia and move back and forth from Julia to Python to C. I'm a deep learning practitioner and loves Astronomy. I recently got selected into Google Summer of Code under OpenAstronomy org and my project's fundamental language is Julia. I'm a computer science by day and dancer by night. Currently, I'm fiddling with Julia and it's awesomeness and I'll offer you nothing less than awesome", - "Speaker Links": " http://prsr.me https://linkedin.com/in/prakharcode https://github.com/prakharcode", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/julia-an-upgrade-to-python-programming-language~enJpe/", - "title": "Julia. An upgrade to Python Programming Language" - }, - "161": { - "Content URLs": "Coming up soon (related to this workshop", - "Description": "Convolution Networks - Framework = Vision in vanilla python. This workshop aims at providing the attendees an experience of implementing convolution neural from scratch without any big framework working in the backend supplementing the need for computation. This would give the attendees an overall understanding of what are Convolution Neural Networks and why do they work so exceedingly well! One does not simply code in vanilla python. What can you expect from this workshop! You'll understand what are convolution neural networks Why they work so well on image data? All the different implementation of Convolution network and how they improve the vanilla network What are the best ways to implement convolution network on a given data What this workshop is not! Just another workshop telling you to use frameworks Maths will not be looked over. (It's important) This workshop is not any other university lecture where you'll not understand anything. I find this image to be so apt given all the abstraction provided by frameworks", - "Last Updated": "18 May, 2018", - "Prerequisites": " Command over Python Familiarity with Numpy and basic math packages Intermediate Mathematics Familiarity with algorithms common in machine learning", - "Section": "Data science", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a deep learning enthusiast who loves mathematics and astronomy. I've been exploring machine learning/deep learning for about 2 years now and fiddling with the basic mathematics and scratch implementations always excite me. I'm currently mentor of deep learning in a Delhi based startup Greatech Soft Solutions and interning at Startup labs and a Google Summer of Code '18 student under the organization OpenAstronomy", - "Speaker Links": " http://prsr.me https://www.linkedin.com/in/prakharcode https://github.com/prakharcode", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/convolution-neural-networks-without-any-frameworks~bmX3a/", - "title": "Convolution Neural Networks without any frameworks" - }, - "162": { - "Description": "Sometimes it can be a laborious task for developers to build android apps using Java. Though Java supports Android apps in a powerful way but it also increases the code complexity for a high end app. Now, if you are a python enthusiast and also want to develop Android apps then Kivy comes to your rescue. Kivy is an open source python library for rapid development of cross platform apps. Using the Kv design language and the Kivy framework for Python, you can build amazing interactive multi-touch apps in just a matter of minutes. Kivy framework solves the complexity problem any android developer face while writing complex codes. It also serves the advantage of being cross platform which saves a great amount of time for any app developer. If you love Python, you will also love Kivy", - "Last Updated": "18 May, 2018", - "Prerequisites": "Python Basic Knowledge of Androi", - "Section": "Web development", - "Speaker Info": "The speaker goes by the name amanraj209 all over the web. I've been interested in learning new technologies since high school and I've been developing apps using Python, Javascript, Java, Go since the last 3 years. I've also done some small projects in Machine Learning. Being a developer gives me a great sense of feel to build apps for the users and contribute to the community. It has always been my passion to dive into the technology and contribute to the community something useful", - "Speaker Links": "Github: https://github.com/amanraj209 LinkedIn: https://www.linkedin.com/in/amanraj209 Facebook: https://www.facebook.com/amanraj20", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aman Raj (~amanraj209)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/developing-android-apps-using-kivy~el61b/", - "title": "Developing Android apps using Kivy" - }, - "163": { - "Content URLs": "Shall be updated soon", - "Description": "You have got this super awesome REST API served through Django/DRF based project and suddenly these requirements come in: We need to have a local support for Chinese language! In case, you've not written your application with localization and internationalization in mind, then \"Boy! You're in danger! You should better start praying to almighty to give you strength and endurance to support yet another language in your app\". In this talk, we'll see how do we support localization and serve our app in different languages, based on what language the client wants to communicate in. As a backend, we should be language agnostic and allow all clients to communicate with us in one of the languages we support. We'll see how to support translation for static data (using makemessages / compilemessages) and dynamic data, using various third-party services such as django-translations and transifex. Here, static data is translations for all the fields, error messages etc. that the app already has and dynamic data is the custom data input by the user in the app. This would enable you to have your admin panel, as well as RESTful APIs, served in different languages", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic knowledge of Python and Django", - "Section": "Web development", - "Speaker Info": "Why do you want this person to speak? Sanyam is a self-taught programmer with a \"can-do\" attitude who developed his interest in Computer Science and Software Development over the years. He mostly goes by CuriousLearner all over the web and you might run into him at various Python Conferences and local meetups. In his free time he contributes to FOSS. Some of his noticeable contributions are in Gecko Engine from Mozilla and CPython. You can read about his latest hacking CPython and other projects at http://www.SanyamKhurana.com/blog & http://medium.com/@CuriousLearner Highlights : Goes by CuriousLearner all over the web. Bug Triager and contributor to CPython (bugs.python.org) GSoC 2018 Mentor for Debian RGSoC 2016 Mentor Mozilla Reps Mentor and contributor to Mozilla's GeckoEngine, Add-ons ecosystem, and other few projects. Core-organizer for PyCon India 2016 & PyCon India 2017 Volunteer for PyCon India 2015.", - "Speaker Links": "Blog: http://www.SanyamKhurana.com/blog Website: http://www.SanyamKhurana.com Github: https://github.com/CuriousLearne", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sanyam Khurana (~CuriousLearner)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-multilingual-superhero-in-django~bkMve/", - "title": "Becoming a Multilingual SuperHero in Django" - }, - "164": { - "Content URLs": " http://haridas.in https://github.com/haridas", - "Description": "Data-science mainly involves understanding your data and identify suitable models based on the data. Mastering the standard tools like pandas and seaborn will be key to gain insights about ML problems. This tutorial coverers, Basics of pandas and seaborn Different plotting patterns using seaborn for your data. Plotting Single and bivariate distributions, categorical plots with distribution. Understand two variable behaviour using regression plots. One usecase:- How I decided to buy a petrol car instead of diesel car by analysing my fuel spending.", - "Last Updated": "17 May, 2018", - "Prerequisites": "Lapatop with following packages installed. pip install seaborn pand", - "Section": "Data science", - "Speaker Info": "Haridas is a Principal Engineer in Pramati Technologies, part of Labs team. He has 8+ years of experience in multiple domains like, Web development, SOA, ML, Devops. He has been working extensively in different ML use-cases and applying them in real scenarios", - "Speaker Links": " http://haridas.in Twitter @haridas_n", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "haridas n (~haridas)", - "created_on": "17 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/find-patterns-in-your-data-using-seaborn-and-pandas~ejJ4e/", - "title": "Find patterns in your data using Seaborn and Pandas" - }, - "165": { - "Description": "DevOps is gaining momentum and we at Microsoft want our users to have great CI/CD story for any language targeting any platform. In this session, we will be talking about how easy is to get started on Cloud and DevOps for Python developer in this new generation of Microsoft We're going to start from scratch and before we're done we will use Visual Studio Team Services (VSTS) to setup Continuous Delivery for Python Applications on Cloud and demonstrate the DevOps strategy in action. The solution grows up to the most demanding needs of a modern software developers powered by VSTS. Whether you are starting new, bringing your own tool chain or inter-operating with existing tools and assets, you can accelerate your delivery of value with Azure and VSTS", - "Last Updated": "16 May, 2018", - "Prerequisites": "N", - "Section": "Developer tools and Automation", - "Speaker Info": "Alok Agrawal is Product Manager for Microsoft Visual Studio Team Services where he and his team are building next generation cloud based developer tools. He has been with Microsoft for over 7 years. Previously he has worked with Windows Application Compatibility and Azure Application team. Alok has Bachelor's degree in Computer Science and completed his business management from IIM Calcutta", - "Speaker Links": "http://www.imalokagrawal.com https://twitter.com/imalokagrawal https://github.com/imalokagrawa", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Alok Agrawal (~imalokagrawal)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-plumber-building-deployment-pipeline-in-minutes~e03Nd/", - "title": "Becoming a Plumber: Building deployment pipeline in minutes" - }, - "166": { - "Content URLs": "Workshop Content: https://github.com/openfaas/workshop OpenFaas Docs: https://docs.openfaas.com/ OpenFaas Website: https://www.openfaas.com", - "Description": "OpenFaaS makes Serverless Functions simple with any programming language through the use of Docker containers. The project can be hosted on any cloud, or on your own hardware - even your laptop. Learn how to build Serverless functions with OpenFaaS and Python in this self-paced workshop lead by the community behind the project. Start by deploying OpenFaaS to your laptops with Docker for Mac or Windows and then learn how to build, deploy and invoke serverless functions in Python. Topics will include: Managing dependencies with pip, dealing with API tokens through secure secrets, monitoring functions with Prometheus, invoking functions asynchronously and chaining functions together to create applications. We\u2019ll finish by building a GitHub bot that puts all of what we\u2019ve learnt together into a single application. The issue-bot will respond to issues raised by analysing the text and deciding whether to label them positive or for review. The workshop will have following labs: Prepare for OpenFaas Test things out Introduction to functions Go Deeper with functions Create a Gitbot HTML for your functions Asynchronous functions Advanced feature - Timeouts Advanced feature - Auto Scaling Advanced feature - Secrets", - "Last Updated": "16 May, 2018", - "Prerequisites": " Basic knowledge of Docker Functions will be written in Python, so prior programming or scripting experience is preferred. Requirements: Install the recommended code-editor / IDE VSCode MacOS, Windows 10 Pro/Enterprise, Ubuntu Linux For Windows install Git Bash Docker CE for Mac / Windows Edge edition Docker CE for Linux As a last resort if you have an incompatible PC you can run the workshop on https://labs.play-with-docker.com/ . ", - "Section": "Web development", - "Speaker Info": "Vivek Singh: Currently working as Software Engineer - II at Akamai Technologies. Been an active contributor to OpenFaaS project. Loves to code in Python and Golang. Contributes to Open Source projects in free time. Vivek Sridhar: Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "My contributions: https://github.com/viveksyngh LinkedIn Profile: https://www.linkedin.com/in/viveksyngh/ Twitter: https://twitter.com/viveksyngh Website: https://www.viveksyngh.info Blog: https://www.viveksyngh.info/blog", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Vivek Kumar Singh (~viveksyngh)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-serverless-with-openfaas-and-python~e9Xzd/", - "title": "Hands-On Serverless with OpenFaaS and Python" - }, - "167": { - "Description": "The human voice is becoming an increasingly important way of interacting with devices, but current state of the art solutions are proprietary and strive for user lock-in. Mozilla\u2019s DeepSpeech and Common Voice projects are there to change this. In contrast to classic STT approaches, DeepSpeech features a modern end-to-end deep learning solution. Based on Baidu's Deep Speech research paper, it trains a model by machine learning techniques. This model directly translates raw audio data into text - without any domain specific code in between. To train systems like DeepSpeech, an extremely large amount of voice data is required. Most of the data used by large companies isn\u2019t available to the majority of people. That's why Mozilla launched Common Voice, a project to help make voice recognition open to everyone", - "Last Updated": "16 May, 2018", - "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune, and a Mozilla TechSpeaker. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": "Mozilla Research machine learning home page: https://research.mozilla.org/machine-learning/ Speaker's LinedIn: https://www.linkedin.com/in/shaguftagurmukhdas/ Speaker's twitter: https://twitter.com/shaguftamethwa", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mozillas-deepspeech-and-common-voice-projects~e7JBd/", - "title": "Mozilla's DeepSpeech and Common Voice projects" - }, - "168": { - "Description": "You only look once (YOLO) is a state-of-the-art, real-time object detection algorithm. The model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image. It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. This makes it extremely very fast. This talk teaches you to develop your own real-time object detection python application to detect and classify objects in images as well as videos in real-time, which you can use in your next self driving car", - "Last Updated": "16 May, 2018", - "Prerequisites": " Knowledge of basic Python and its syntax Idea/Overview of deep learning as a technology", - "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune. I'm currently working in HSBC Technology India, as a software developer. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": " LinkedIn Twitter Recent talk on WebVR", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-object-detection-coz-yolo~b6VNb/", - "title": "Real-time object detection coz YOLO!" - }, - "169": { - "Content URLs": "https://github.com/sdonapar/data_analysis_pytho", - "Description": "Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data. Data Visualisation helps to get hidden insights quickly . Data Visualisation is key for summarising and communicating your insights. This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis and visualisation Following will be covered as part of this session How does data analysis fit in the life cycle of data science project Dealing with numpy arrays - quick overview Reading data using various formats and sources Data scrubbing/cleansing - dealing with missing values, data transformation Introduction to data visualisation and quick overview of libraries available Using visualisation to understand and communicate results Analysing one of the open source data set By the end of the session Audience will have very good understanding of how to apply numpy, pandas to analyse, visualise understand and communicate the results Scrub/Cleanse the data and prepare data set required for machine learning", - "Last Updated": "16 May, 2018", - "Prerequisites": "Hands on exposure with basic python programming language Software requirements: Please install Anaconda ( https://www.anaconda.com/download/) with Python 3.6 Download the git hub repo - https://github.com/sdonapar/data_analysis_pythonwe would be using jupyter notebooks for this worksho", - "Section": "Data science", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company. I have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar linkedin profile - https://www.linkedin.com/in/sasidonaparthi twitter handle - @sdonapa", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-visualisation-using-python~e50Xd/", - "title": "Data Analysis & Visualisation using Python" - }, - "170": { - "Description": " Understanding Neural Networking using NumPy Implementing CNN using Keras & understanding foundations Using Pretrained models. Transfer training for doing dog breed identification", - "Last Updated": "15 May, 2018", - "Prerequisites": " Python Basics NumPy Machine Learning Basics", - "Section": "Data science", - "Speaker Info": " 10 + Industry Experience. Machine Learning & Deep Learning Trainer/Consultant for more than 20 companies https://www.linkedin.com/in/awantik/ Co-Founder EdYoda & Zekelabs", - "Speaker Links": "https://www.linkedin.com/in/awantik", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Awantik Das (~awantik)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-using-python-from-scratch-image-classification~b4KJa/", - "title": "Deep Learning using Python from Scratch - Image Classification" - }, - "171": { - "Content URLs": "https://games.renpy.org/category/rpg https://www.renpy.org", - "Description": "Ren'Py is one of the most versatile and easy-to-use frameworks, written in Python, for the development of Visual Novels and smaller Role-playing games. The talk will explore the details about creating your own development environment for development of visual novels, writing a script and developing GUI, porting your game to Android and iOS and how you can get help for issues in development process. The talk will also explore some of the games which have been developed in Ren'Py like Katawa Shoujo, Doki Doki Literature Club, Imre's Curse: The Prologue etc. The talk will be an interactive one and have a very light and humorous note", - "Last Updated": "15 May, 2018", - "Prerequisites": "No prerequisites required. An open mind and familiarity with Python is all what is needed to attend the talk", - "Section": "Others", - "Speaker Info": "I am currently involved with Lernr Project, a startup based in Ahmedabad and have been working with Python for 3+ years, certified as a\nSoftware Carpentry Instructor and one of the organizers of Django Girls Bangalore. Contributor to Biopython, Galaxy Project, bioconda and conda-forge communities. My interests are in the field of Bioinformatics, High-Performance Computing and am working under Prof. V.K. Jayaraman in the field of Proteomics", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sourav Singh (~sourav)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/make-your-own-visual-novel-in-renpy~b2JAb/", - "title": "Make your own Visual Novel in Ren'Py" - }, - "172": { - "Content URLs": " Talk at PyCon India 2017 Talk at PyCon Pune 2017 Talk at PyCon India 2013 Django on Steroids -- Slides Lessons from Scale: Django", - "Description": "Take it from someone who has introduced an exorbitantly high number of bugs in empty files for most of his life: debugging is hard indeed. But since the dawn of time, developers have been debugging code: there's no escaping that. Software testing, as the elders would tell you, is one of the greatest weapons in your arsenal against those bugs. It's easy to write tests. It helps you write more robust software. And it really helps you sleep at night: and your on-call ops team would love you! But testing is also deeply mystified, unfortunately. Beginners, and sometimes even seasoned developers, generally have a difficult time just to get started: so they eventually miss out on this easy way to attain peace of mind. This talks aims at removing all the mystery around software testing in Python, and give the attendees a head-start into the easiest way of writing tests for their code. As part of being a Python developer for the past 8 years and leading a team of developers building enterprise-grade software for the past 4 years, I've learnt immensely about the important role of software testing in building scalable, durable software; and also a better, pragmatic way of thinking about testing in Python. This talk aims at providing a distilled version of my learning to the audience: both beginners to Python, and seasoned Pythonistas. The talk would broadly cover these topics: A formal way of thinking about software testing / Why you should even bother about writing tests? Writing the simplest of tests in Python / Brief exploration of unittest and pytest Introduction to mocking in Python / In-depth exploration of mock and how to effectively use it for mocking any type of scenario in your code Writing tests for complex applications / working code examples from real life A few (opinionated) recommendations about testing Apart from providing to the audience an easy-to-grasp framework of thinking about software testing, this talk aims to teach by examples from real world. Complex and not so straightforward concepts would be explained with code samples and tests from production, so it's easy for the audience to truly grasp them. The talk also features anecdotes from my own experience in building software to give the audience better context", - "Last Updated": "15 May, 2018", - "Prerequisites": "This talk is intended for newcomers to Python (who might never have written a test yet), as well as experienced developers (who might not be writing tests effectively). There are no technical pre-requisites for this talk. The key takeaways would be patterns you can directly start using in writing tests for your own code", - "Section": "Developer tools and Automation", - "Speaker Info": "Sanket ( @sanketsaurav ) is co-founder and Chief of Geeks at DoSelect . He\u2019s 50% developer and 50% designer. He\u2019s been dabbling with computers since the age of 10, and had started his first venture at 18. He loves the Web and likes building cool stuff that matter. His languages of choice are Python, Go and JavaScript, and he\u2019s been building production apps using these for the past two years. He\u2019s also spoken at more than 50 events and hackathons across the country on open source technologies including Python, HTML5 and web applications in general. Sanket also contributes extensively to open-source, with contributions to projects like Django, Celery and Docker, and original Python modules like S3Tree and mimelib ", - "Speaker Links": " GitHub Website DoSelect", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sanket Saurav (~sanket)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-is-hard-testing-is-easy~e17qb/", - "title": "Debugging is hard, testing is easy!" - }, - "173": { - "Content URLs": "I will soon share presentation, resources, and code soon on GitHub", - "Description": "Abstract Think of wireless internet, but has the wire somewhere. Serverless architecture still has the server behind :P. What serverless actually means that developer should focus on the code rather than thinking about the servers. As a technique, it removes most of the manel parts of an application, so you can actually spend your day coding. This means that you, developers, can quickly create apps that handle production-ready traffic. You do not have to actively manage scaling for your applications. You do not have to provision the server, or to pay for resources that are unused. The serverless movement started with the release of AWS Lambda, a Function-as-a-Service (FaaS) compute service. But serverless is much more than just FaaS Chatbots have been around for quite a long time. But why this sudden surge and interest in chatbots now? Well, there are various reasons. Unlike the earlier days, many AI and NLP capabilities are now available as consumable services. Also, serverless technologies make chatbots easier to build and scale. The question is, how is the backend served? Would you set up a dedicated server (or a cluster of servers)? That\u2019s costly, painful, and time-consuming! or You will deploy it to Heroku, which will eventually sleep (only happens in the free tier) if no one uses your chatbot. Imagine suddenly, traffic increased your chatbot is used by thousands of people at a time. When Heroku free tier is over, the application crashed or you exceeded memory limit. What would you do now? That\u2019s where serverless technology can help. Benefits of serverless No Administration - We can deploy our code without provisioning anything beforehand, or manage anything afterward. There is no concept of a fleet, an instance, or even an operating system. Scalability - One doesn't have to care about auto-scaling, No need to show alerts or write scripts to scale up and down. With serverless, we can handle quick bursts of traffic. Cost - Function-as-a-service (FaaS) compute and managed services charged based on actual usage rather than pre-provisioned capacity. This means one pay the amount we use, so if we use service for 10 sec then we pay for 10 sec. Faster Development - Now loop between having an idea and deploying to production is shortened because no one need to manage anything after deployment, smaller teams can ship more features. It's easier than ever to make your idea live. Easy Integration With Other Services Going serverless allows a seamless integration to various other cloud services from the same provider. For example, if you are using the AWS platform for chatbots, then you can use DynamoDB for the database, write programming logic as Lambda functions, and expose them through the API Gateway. Session key Takeaways The main question is how to write code which is serverless compliant. This is where this session will help you. This talk will help people to move a step ahead of the traditional way of writing code as some of you had already developed chatbot, I will share how can you can write the simple chatbot in python and can take leverage of serverless to deploy and publish. I will cover Serverless Framework principals AWS Lambda, Amazon Lex and API Gateway How to write a chatbot in python and create a Lambda function How to troubleshoot in a serverless world", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic knowledge of python and development in general", - "Section": "Others", - "Speaker Info": "Vaibhav Singh is an undergrad final year student of BML Munjal University, Gurugram. He had worked with AWS services as a solution architect intern in Amazon and he is also open source enthusiast and contributed to many open source organization like Fossasia, coala, etc. He is now Google Summer Of Code intern with FOSSASIA. Previously, He was the finalist winner in Codeheat competition. I write mostly in python ;). I had written various small scripts to make my life easier :", - "Speaker Links": "Website GitHub Twitter Facebook Linkedin Mai", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vaibhav Singh (~vaibhavsingh97)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-serverless-framework-build-a-chatbot~eZXgb/", - "title": "The Serverless Framework - Build a Chatbot" - }, - "174": { - "Content URLs": "Sensor Fusion Introduction\nhttps://youtu.be/C7JQ7Rpwn2k Sklearn Quick Tutorial\nhttp://scikit-learn.org/stable/tutorial/basic/tutorial.htm", - "Description": "Abstract The primary purpose of this talk to describe how we are using python and Sklearn to model and analyse time series sensor data. In particular, I will walk through how we use Python to process data from an IoT enabled sensor attached to a cricket bat, build machine learning models on the data, and use open source tools to deploy our models in the sensor device as a smart IoT application. Description With the steep increase in the number of smart-things connected to the internet, the amount of data that is being generated by such devices is increasing exponentially. However, much of that data is not useful and therefore filtering unuseful data is an important task. How do we filter the important part and remove the noise from sensor data streams to generate actionable insights? To demonstrate the problem we are placing a sensor device on a cricket bat. The IoT device is a miniaturised, wireless MEMS inertial measurement unit (IMU). The IMU incorporates three-axis sensing of bat acceleration and angular velocity with a low-power Bluetooth to transmit this data to a mobile. First, we gather event-based data rather than storing the entire stream. This again poses the question: how do we define an event? What makes an event unique from the surrounding \u2018non-event\u2019 context? These are some of the questions that need to be answered in order to define an event. Watching a cricket batter stand and prepare to swing, the human brain continuously filters its visual perception and is able to detect and differentiate a swing from the pre- and post-swing activity. We need to be able to automate that same process. Some data instances can be tagged while other can\u2019t be. This helps in training and evaluating machine learning models later. Secondly, After we have extracted time series data based on the instances, we can start analysing these event-based sets of data to understand the language of sensor data. For this, we are using Jupyter Lab to interactively work with data. How does an accelerometer data depict the real world physical motion? This step helps us find the relation between the real world actions and the sensor data set. Well, the extraction process will be prone to noises. The data comes in CSV files, python seems the right choice for us to read and analyse the data. Pandas and offer data frames that come handy to rapidly form and validate hypothesis interactively in Jupyter notebooks. Any analysis is incomplete without visualisation, that's where Matplotlib helps us understand the data better. We quickly test the machine learning models by using Sklearn, which has most of the standard algorithms already implemented. This keynote will describe some of the analysis (along with python code) to show how we have taken several steps right from forming the hypothesis to implementing a solution in the device level layer. All of this demonstrates how Python and its rich set of libraries are helpful in forming solutions to some of the product related features. Thirdly, we need to automate the task of classifying a particular instance from the stream. For this to happen, we can either feed a machine learning model or create a rule-based algorithm which can classify the events into buckets. Now every step has its own set of challenges, firstly the application we are working on involves using motion sensors attached to the back of a cricket bat. There are network constraints in the field. If a sportsperson wants to know real-time analytics from the device, the segregation needs to happen offline. We have to deploy the models on the miniature sensor devices because sometimes the players don\u2019t even carry their mobile phones to the playing area. Therefore our objective is to enable the devices to remain independent in running machine learning algorithms by themselves", - "Last Updated": "14 May, 2018", - "Prerequisites": "Participants should have an understanding of python basics", - "Section": "Data science", - "Speaker Info": "Sanjiv Soni is a data scientist at Str8bat, Bangalore. He currently an international fellow at University of San Francisco for Deep Learning Programme. Sanjiv has experience with Software and product ecosystem. He has interests in building software devised solutions to problems solved by humans", - "Speaker Links": "https://twitter.com/sanjivsoni7 https://www.linkedin.com/in/sanjiv-soni", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "sanjiv soni (~sanjiv)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/swing-and-a-miss-deploying-machine-learning-models-for-iot-enabled-devices-using-python~bYXYa/", - "title": "Swing and a Miss: Deploying machine learning models for IoT enabled devices using Python" - }, - "175": { - "Content URLs": "https://atad.xyz\n[ Will share the GitHub repo during the talk with sample web crawlers ", - "Description": "Introducing to Web Scraping. A complete walkthrough the below items: Challenges in scraping websites and parsing the data, Introducing Scrapy, a widely used framework to extract data Dos & Don'ts Usage of Proxies & IP Rotation Crawling hundreds of websites, running and scaling them to huge volumes", - "Last Updated": "14 May, 2018", - "Prerequisites": "Laptop with Ubuntu or a similar OS. \nPython and MySql latest versions Basic understanding of Python and MySql\nGood to have knowledge in writing Xpaths and usage of proxie", - "Section": "Data science", - "Speaker Info": "I am Raja Emmela, \nI Run Headrun Technologies, Bangalore - helping clients in Data Scraping and Web Applications We are in this space for the last seven years, extracting data and parsing them. My experience helps do share the challenges we faced with domestic and NA & APAC clients while scraping websites and the don'ts in particular", - "Speaker Links": " LinkedIn Twitter Blog", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "rajaemmela", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-intro-to-web-scraping-dos-donts-and-the-challenges-in-scaling-it-to-huge-volumes~eXVVb/", - "title": "An intro to Web Scraping, dos & don'ts and the challenges in Scaling it to huge volumes" - }, - "176": { - "Content URLs": "https://github.com/devxp", - "Description": "My talk is related to my work on ZProc , a library for doing multiprocessing in python Its provides a high-level wrapper over zeroMQ, the distributed messaging library. I will provide a basic introduction to the ways we can natively implement concurrency/parallelism in our applications and how ZProc is a better way to do multi-tasking", - "Last Updated": "14 May, 2018", - "Prerequisites": " A good knowledge of basic python. Some knowledge about the python Process/Thread interface is appreciated If you ever had your hands on the zguide , I have a hunch you'll like this. ", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm 19 year old python programmer, picked up python when I was around 15. My adventures with multi-tasking applications started when I was 17, trying to build a concurrent youtube downloader. I am since, trying to find ways to make writing concurrent, multi-core applications simpler in python", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Dev Aggarwal (~devxpy)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/zproc-process-on-steroids~bWBoa/", - "title": "ZProc - Process on steroids" - }, - "177": { - "Description": "A lot of budding programmers use print() function or logging module to display the state of the program. However, it soon becomes untenable to reason about the program in a barrage of print statements. At that time, a debugger is a must. Debuggers are a better and structured way to inspect a program. A practical and basic understanding of debuggers will help in locating bugs easily and save developer's time and unnecessary frustration. In this talk, we are going to learn the terminology associated with debugging and explore the most commonly used commands of pdb", - "Last Updated": "14 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college students or people who just started programming in Python", - "Section": "Core python and Standard library", - "Speaker Info": "I'm currently a Senior Web Developer and Curriculum Designer at Pesto Tech. I've programmed in Python and Flask since the last 3 years. Open source enthusiast, and frequent blogger", - "Speaker Links": "Medium - https://medium.com/@arfatsalman Twitter - https://twitter.com/salman_arfat GitHub - https://github.com/ArfatSalman LinkedIn - https://www.linkedin.com/in/arfatsalman", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Arfat Salman (~ArfatSalman)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-basics-and-debugging-python-scripts-with-pdb~eVZoe/", - "title": "Debugging basics and debugging python scripts with pdb" - }, - "178": { - "Description": "Millions of visitors visit business websites every day and each one of them takes different set of steps in order to seek the right information/product. Yet most of them leave disappointed or dejected for some reason and very few get to the right page within the website. In this kind of situation, it becomes difficult to find out if the visitor actually got the information that he was looking for? Also, the individual journeys of these visitors can\u2019t be compared to each other since every visitor has done different set of activities. So, how can we know more about these journeys and compare these visitors to each other?\nSequence Embedding is a powerful way that offers us the flexibility to not only compare any two distinct visitors entire journey in terms of similarity but also to predict the probability of visitor\u2019s conversion. Sequence embeddings essentially helps us to move away from using traditional features to make predictions and considers not only the order of the activities of a user but also the average time spent on each of the unique pages to translate into more robust features and used in Supervised Machine Learning across multiple use cases (next possible action prediction, converted vs non-converted, product classification)\u00a0.Using traditional Machine learning models on the advanced features like sequence embeddings, we can achieve tremendous results in terms of prediction accuracy but the real benefit lies in visualizing all these user journeys and observing how distinct are these paths from the ideal ones. This session will unfold the process creating sequence embeddings for each user\u2019s journey in python and use them to build machine learning classification model to predict visitor conversion along with comparing all the user journeys in terms of similarity score", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic understanding of Machine Learning ,\nPython Basic", - "Section": "Data science", - "Speaker Info": "Co-Founder of DataScienceBridge and currently Sr. Data Scientist at SapientRazorfish core Data Science Team has around 8 years\u2019 experience in the industry, ranging from large scale IT enterprise business development to building complex Machine Learning models by applying state of the art techniques. He has completed his Master\u2019s in Business at Symbiosis International University and certified professional in Machine Learning from IIM-Calcutta.\nHis core expertise involves Machine Learning, Deep Learning, Recommendation Systems using python, spark and Tensorflow for various projects. He is president of Data Science meet up group at SapientRazorfish and conducts multiple webinars on Machine Learning. Along with that he is also a speaker and recently presented a talk at \u201cGreat Indian Developer Summit \u201c(GIDS 2018).\nIn his spare time, he likes to read, code and help aspiring Data Scientists", - "Speaker Links": "https://www.youtube.com/watch?v=Nbpz79v2y5", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pramod Singh (~pramodchahar)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sequence-embeddings-in-python-classification-user-journey-comparison~dRBwd/", - "title": "Sequence Embeddings in Python: Classification & User journey Comparison" - }, - "179": { - "Content URLs": "For workshop home here and here such as to get sample data, Jupyter notebooks, slides etc For workshop slides pls see her", - "Description": "Geospatial representation are so prevalent in day to day life, such as even in simple travel related conversation to maps, aerial/satellite images etc. In digital era, geospatial data is extensively produced and consumed in ever growing proportion. Python with its free and open source libraries are giving wide variety yet simple and effective set of tools to visualise and analyse geospatial data. The current workshop is directed for beginners of Python programming language, who have basic understanding on computing and data formats. The primary objective of the workshop is to introduce and give hands on training on selected list of FOSS libraries for geospatial analysis. The workshop as a do it yourself fashion tries to solve two real world problems in Geographical Information System (GIS) and its geospatial data sources. The workshop comprised of three components: Component 1 Python environment and work flow setup, an assisted task of setting up the Docker and Jupyter notebook setup. Setting up the Geographical Information System (GIS) environment with extended discussion. Setting up of GIS tools such as FOSS QGIS and Google earth. This component is comprised of four exercises. 1. Introduction to vector data, 2. Introduction to raster data, 3. binary and text file formats of geospatial data, 4. Introduction to tools of GIS, 5. Introduction to literal programming- Jupyter notebook Component 2 Find characteristics of road network(type of road network, length of the type) within a 1X1 km grid. The data source is Open Street Map (OSM) road network data on a city level (60X60km size). This operation is operationally simple such as measure a line feature but computationally intensive as the operation comprised of geometry within operation on dense road network seen in urban setup. Libraries such as Shapely, Fiona, Geopandas and rtree index will be used for the fast processing of this operation. This component comprised of three exercises 1. Find distance between two points 2. Find distance between two points constrained by another vector 3. Find distance between large number of points in for loop Component 3 Find cloud cover percentage over area of interest. The data source is Landsat satellite imagery. Searching cloud free Landsat images over an Area of Interest for a temporal extent of a year or more is manual and time consuming. Applying cloud cover detection algorithm could make this operation automatic. Libraries such as rasterio, Geopandas, Fiona, and libraries related to landsat algorithms will be used for this task. This component comprised of two exercises 1. Convert the imagery in geotiff into numpy arrays 2. Apply the algorithms to find the cloud cover Workshop Plan Introduction and setup- 30 minutes Component 1- 30 minutes Component 2- 45 minutes Component 3- 45 minutes", - "Last Updated": "12 May, 2018", - "Prerequisites": " Laptop 32bit/64 bit Workshop material is tested on 64 bit computer, it is said to be working in 32 bit, lets experiment! A copy of Docker container image from here , file from the link foss-pt-gsa_v3.tar.gz is 2.5 GB in size, will be using this container for DIY Local copy of Docker toolbox from here for windows 64 bit, for 32 bit Windows, follow this link , if any issue, don't worry, we have a session for setting up the docker! Local copy boot2docker.iso from here , we will be following old method of docker toolbox instead of docker native software for Windows.", - "Section": "Data science", - "Speaker Info": "I am a research associate at UrbanEmissions.info . My doctoral study was related to interoperable management of data from air pollution monitors and atmospheric models. I used free and open source libraries of Python for the study, especially on geospatial data compilation, analysis and visualization. Freedom and customization of free and open source languages such as of R and Python were immense. After Conda python package manager came into existence, the world of Python was so easy and I started to use Python for most of computing", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "nishadhka", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/free-and-open-source-libraries-of-python-for-geo-spatial-analysis-and-visualisationmaps-and-satellite-imageries~aQL5e/", - "title": "Free and Open Source libraries of Python for Geo spatial Analysis and Visualisation(Maps and Satellite imageries)" - }, - "180": { - "Content URLs": "https://github.com/bhagvank https://ingeniopythonis.wordpress.co", - "Description": "Video content management, AI, Blockchain and Virtual/Augmented reality technologies are changing the learning management platforms. Customer focused learning systems are emerging in enterprises. Enterprises are structuring their curriculum products to help solve the high value use cases of their customers. Members of the LMS system (python/ Django stack) can tailor their educational experience by choosing courses based on their learning styles. The courses are becoming more effective and helping members retain information. Platforms are differentiating by providing better, faster ways to find relevant content, whenever and wherever learners need it. Modern learning management platform is an end-to-end eLearning solution which has capabilities to create, distribute, edit and manage entire courses from start to finish independent of the content. Educational success and fulfilment are achieved through personalization and optimization of the learner\u2019s path through courses and gaining of competencies. This new class of learning technology vendors is making it possible to augment their systems with cloud-based applications which can be easily integrated with an enterprise-scale technology ecosystem. Enterprises are now tracking and analyzing learning experiences with incredible precision which can be used to improve ongoing program and business outcomes. Tracking and reporting comes in learner-oriented dashboards and reports built for the staff", - "Last Updated": "12 May, 2018", - "Prerequisites": "python, djang", - "Section": "Data science", - "Speaker Info": "Co-Founder of Architect Corner, Bhagvan has around 18 years experience in the industry, ranging from large scale enterprise development to helping incubate software product startups. He has completed a Masters in Industrial Systems Engineering at Georgia Institute of Technology, and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras", - "Speaker Links": "https://www.youtube.com/channel/UChu9J4M85CC7C8hMYp5cgRg/video", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhagvank", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-management-next-generation-platform~dPJ6a/", - "title": "Learning Management : Next Generation Platform" - }, - "181": { - "Content URLs": "https://nim-lang.org http://slides.com/akapatkar/nim-for-python-programmer", - "Description": "Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org As Python programmers, we are used to a language which is expressive, intuitive and versatile. Python is widely lauded for its productivity, minimalistic syntax, standard library feature set and is an inspiration to newer languages like Go, Swift, and Julia. However, there are some areas like speed, distribution, and multicore processing where it lacks a good solution. Nim is a statically typed and high-performance garbage-collected language which builds upon Python\u2019s strengths and addresses someone its weakness in an innovative way. This talk introduces Nim to Python programmers by diving into powerful language design, syntax, data and control structures, static analysis, metaprogramming, portability/distribution and standard library features. At the end of this talk, you should have learned enough to a) get started with Nim on a project b) get familiar with Nim\u2019s growing ecosystem c) leverage/extend existing Python skills on a Nim project. Timeline breakdown: 1) Intro to Nim (10mins) 2) Language tour from Python\u2019s point of view (20 mins) 3) Things you can do with Nim + ecosystem (5 mins) 4) Q&A (5mins", - "Last Updated": "12 May, 2018", - "Section": "Others", - "Speaker Info": "I am a language enthusiast and a Python developer at Netflix. I\u2019ve been learning and using Nim for over a year now and I have benefited immensely from its learnings. There is a strong correlation between Nim and Python and I would like to explain that to the audience and show them a way to think problems using Nim\u2019s construct which I am sure will help them improve their Python skills. I am currently using Nim to write an interpreter for \u2018lox language\u2019. More details here https://github.com/cabhishek/nimlo", - "Speaker Links": "International Conference Talks: PyCon Ukraine 2018 https://2018.uapycon.org/#schedule PyCaribbean 2018 http://pycaribbean.com/schedule.html Python San Sebastian 2017 http://pyss17.pyss.org/", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Abhishek Kapatker (~abhishek69)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/nim-for-python-programmers~aO9Ed/", - "title": "Nim for Python Programmers" - }, - "182": { - "Content URLs": "https://github.com/DL4Jets https://docs.google.com/presentation/d/1dDxxsMkfg8vwMi7QDkDaVwCQnxsaXVh9-6xrgrkLvnY/edit?usp=sharin", - "Description": "Ever wondered if you could build your own deep learning framework for hundreds of users? Well, we did build one and turns out it's not as hard as it sounds. With thousands of people working towards democratising artificial intelligence (AI) , we have seen an explosion in the availability of machine learning libraries that make it simpler to build and deploy models for a wide range of tasks. From finance to art, every field has been revolutionised by the introduction of AI. At the European Organisation for Nuclear Research (CERN) we work on understanding the fundamental particles that constitute the universe by performing various experiments in particle physics. Of late, we have experienced a stratospheric rise in deep learning applications to various problems - RNNs, CNNs, and GANs - that have yielded promising results. Like, this stuff is craaazy, dude. It works! We delve into the development of one such project as it evolves from a set of scripts into a full-blown framework with multifarious applications in high-energy physics. In this talk we will detail the evolution on the DeepJet Python environment. Specifically, we will start with the problem(s) we were facing and how we evolved from a set of scripts hastily patched together to a structured, cross-platform framework built on top of Tensorflow and Keras. The library is a WIP so we're shipping updates on a daily basis with the goal of improving usability with focus on documenting our existing code base. Initially envisaged to support the development of the namesake jet-tagger in the CMS Experiment at CERN, it has grown to encompass multiple purposes within the collaboration. It is aimed at outlining how to go from a set of scripts to building a library that is used by hundreds of scientists in the world's largest physics research collaboration. The presentation will describe the major features the environment sports: simple out-of-memory training a with multi-threaded approach to maximally exploit the hardware acceleration, simple and streamlined I/O to help bookkeeping of the developments, and finally Docker image distribution, to simplify the deployment of the whole ecosystem on multiple datacenters. The talk will also cover future development, mainly aimed at improving user experience. ", - "Last Updated": "12 May, 2018", - "Prerequisites": "Preferred (but not necessary): Experience working with virtual environments or anaconda Basic knowledge of concepts in machine learning", - "Section": "Data science", - "Speaker Info": "Swapneel is a computer scientist working at Compact Muon Solenoid (CMS) Experiment at the European Organisation for Nuclear Research where physicists and engineers are probing the fundamental structure of the universe. They use the world's largest and most complex scientific instruments to study the basic constituents of matter \u2013 the fundamental particles. His work at CERN encompasses the creation of a framework that can facilitate the use of deep neural networks and provide a suite of functions to serve multiple use-cases such as jet classification, particle reconstruction, and so on. He is an open-source enthusiast, writing and contributing to various projects in his free time", - "Speaker Links": "https://opensourceforu.com/author/swapneel-mehta/ https://medium.com/@swapneel_mehta http://www.ccdev.in/swapneel-mehta/ https://github.com/swapneel", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Swapneel Mehta (~SwapneelM)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-deep-learning-framework~dN18b/", - "title": "Building a Deep Learning Framework" - }, - "183": { - "Content URLs": "", - "Description": "A short and crisp interactive session for the first time attendees of PyCon India to help them navigate through the conference and make the most of the next 4 days. 2011 was my first PyCon and in hindsight was a major turning point in my professional life. The experiences I had, the people I met and the friends I made during the conference are still shaping the choices I make and the decisions I take even today. PS: This will be a heavily opinionated talk and the attendees will be requested to weigh the advice being shared and adapt the ones that suit them the most. The audience will be implored to introspect and answer the following and more for them Which talks to attend? How to decide which talks to attend. Can I walk out of a talk in the middle? Should I attend every talk? What is the hallway track? Should I talk to strangers at the conference? How to start talking to strangers? Can I volunteer now that the conference is already happening? The volunteers are awesome people will they accept my help? How can I help? Should I help the volunteers? What is the dev-sprint? How to make the most of the dev sprint? I just started learning python, will people make fun of me if I speak? i need a job, what should I do? I need to hire, what can I do?", - "Last Updated": "12 May, 2018", - "Prerequisites": "A ticket to the conference, willingness to learn, un-learn and re-learn", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has been a part of PyCon India since 2011 where he found enlightenment and confidence to take charge of his education and steered his career in a direction that feels like success at least to him. These days, along with his team at https://essentiasoftserv.com he consults for companies that need assistance maintaining, scaling, and sanitizing their python based codebase", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-make-the-most-of-pycon-india-2018~dLBva/", - "title": "How to make the most of PyCon India 2018" - }, - "184": { - "Description": "So you started learning python, and you have been able to stitch few lines of code together and it worked, but you do not know why, then this is the talk for you. We will delve into elementary yet obscure concepts that are more often than not skipped by beginners eg why is if _ name_ == _ main_ required in python scripts. et el. In a 3 hour power packed interactive and fully-hands on workshop we shall be learning python from ground up using examples from the real world. Basics of python will be covered with less emphasis on the basics of programming itself. The topics to be covered during the workshop shall include but not be limited to: Hello World Variables Loops and conditionals String Lists, Dictionaries and Tuples. functions File handling classes modules and imports lambda, map and reduce decorators and generators raising and handling exceptions sample exercises for the attendees to work on based on the concepts covered in the first half of the workshop.", - "Last Updated": "12 May, 2018", - "Prerequisites": "The person should be familiar with a *nix based operating system, and the shell should not be alien to them. Attendee should be familiar with the concepts of a hierarchical file system and at least be able to find where their editor saved the file they just created. Knowledge / experience of at least one other programming language will give them an unfair edge", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat, along with his team at https://essentiasoftserv.com consults for python based projects which need help in maintaining, sanitizing and scaling to achieve their true potential.\nHe was one of the four who revamped the https://pydelhi.org community and volunteered for over a dozen https://pythonexpress.com workshops", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/yet-another-introduction-to-python~aKE8d/", - "title": "Yet another introduction to Python" - }, - "185": { - "Content URLs": "The work in progress repository of all the associated code - fromscratchtoml . The official website of fromscratchtoml . The work in progress python notebooks . The author's github profile ", - "Description": "Each step we take we are closing in into a world of Artificial General Intelligence . All these so called modern inventions ignite a feeling of astonishment among newbie developers across the globe - seeking answers to how these things work from the very basic level. There are myriad resources available on the internet theorising machine learning algorithms. But - what these resources lack is something that can bridge the gap between the theoretical concepts and the actual coding aspects. When a relatively novice developer skim through the code of these libraries he can barely understand what exactly is going on behind the recondite code. In the midst of making the code efficient these libraries often come up with chunks of code which are barely comprehensible. fromscratchtoml The primary goals of this library is - to bridge the gap between the theoretical and coding aspects of machine learning algorithms. To write intuitive blogs as python notebooks so as to juxtapose theory and code . Explaining the fundamentals of the algorithm from the very basics. To minimise the use of external dependencies except the fundamental ones like numpy and matplotlib . To make sure that the developed algorithms are coherent with already existing machine learning frameworks. The library is still in a nascent stage but will take shape in a couple of months. Given that the commit frequency is huge. The audience is requested to be patient. LIME (Local Interpretable Model-Agnostic Explanations) - When you are writing a machine algorithm from scratch you want to make sure that your results are coherent and your model is learning the features it is meant to learn. LIME explains why your model behaved the way it did. I will quote excerpts from their blog below - Imagine we want to explain a classifier that predicts how likely it is for the image to contain a tree frog. We take the image on the left and divide it into interpretable components (contiguous superpixels). As illustrated below, we then generate a data set of perturbed instances by turning some of the interpretable components \u201coff\u201d (in this case, making them gray). For each perturbed instance, we get the probability that a tree frog is in the image according to the model. We then learn a simple (linear) model on this data set, which is locally weighted\u2014that is, we care more about making mistakes in perturbed instances that are more similar to the original image. In the end, we present the superpixels with highest positive weights as an explanation, graying out everything else. Even from a human's perspective these explanations do make sense. BONUS - MrMark (A personal customisable assistant integrated with Google assistant ) - I am going to use Mr. Mark to vocally invoke commands like ' open LIME explanations for RNN , train CNN for face recognition ` etc.. TODO Write timelines. prepare content specific for presenting. DISCLAIMER - All the content related to LIME belongs to their respective owners", - "Last Updated": "11 May, 2018", - "Prerequisites": "Novice level experience of python and development in general. Acquaintance with basic machine learning will be a plus", - "Section": "Data science", - "Speaker Info": "I have graduated from IIT ISM Dhanbad in 2017. In daytime I work for a London based startup - ALIS labs , at night I am a bug buster vigilante working for my organization jellAIfish where I am the author of fromscratchtoml . I am also RaRe's incubator program member - the same organization which looks after the reputed topic modelling library gensim . I will be giving a demo prep-talk for this proposal in Hyderabad Python Meetup group on 2nd June 2018", - "Speaker Links": "Author's open source contribution can be seen at his github profile where it all started. Author's current blog where he discussed a 'bit' about the impact of AI. Author's old blog archive where he talked about random developer stuff. Author's another delusional repository which he has trouble explaining to people. Author sometimes also blogs for RaRe technologies . Author is omnipresent on the web by the handle markroxor ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Mohit Rathore (~markroxor)", - "created_on": "11 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/from-scratch-to-ml-the-machine-learning-library-you-really-understand-and-explaining-its-predictions-with-lime~dJXya/", - "title": "From scratch to ML - The machine learning library you really understand and explaining its predictions with LIME." - }, - "186": { - "Content URLs": "Repository for the content", - "Description": "Orbital Mechanics/Astrodynamics is one of the most difficult things to understand and take care of! For this simple reason it is called \"Rocket Science\". poliastro is a python package intended to make Astrodynamics Open Source, and easy to understand and visualise. Through the talk, various modules of the poliastro package will be introduced. I will show how we can solve very complex Orbital Mechanics problem in 2 minutes that takes years for a scientist to solve manually! The talk will cover some parts of AstroPy, numba and a bunch of plotting libraries such as matplotlib and plotly", - "Last Updated": "09 May, 2018", - "Prerequisites": "Basic introduction to plotly , matplotlib . Knowledge of some core packages like numpy, etc is beneficial. Knowledge of some of the core Astronomy libraries such as AstroPy is also beneficial", - "Section": "Data science", - "Speaker Info": "I am Shreyas Bapat, half \"Electrical Engineer\" and a passionate developer. I study at Indian Institute of Technology Mandi and constantly contribute to open-source projects. I have contributed to some projects like plotly, dash, poliastro and astroquery. I like Astronomy and related fields a lot and hence keep searching for projects related to that. Also, I am into Deep Learning from quite a time and love tweaking Neural Networks to get amazing results. I am the co-ordinator and maintainer at STAC-IITMandi . I have mentored the Astronomy Code Camp organised by Nehru Planetarium and Astronomical Society of India", - "Speaker Links": "GitHub Profile : shreyasbapat Find my contibutions in Poliastro at #4 : https://github.com/poliastro/poliastro/graphs/contributor", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shreyas Bapat (~shreyasbapat)", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/through-python-to-the-stars-orbital-mechanics-made-easy-and-open-source~dGK5d/", - "title": "Through Python to the Stars! - Orbital Mechanics Made Easy and Open-Source" - }, - "187": { - "Content URLs": "Github and presentation will be uploaded shortly", - "Description": "Functional programming is an essential part of any programming language. It allows you to harness the language, performing tasks which can replace tens of lines with just one. This is one programming paradigm which enables the programmer to give more importance to functions than classes. Instead of the traditional approach, we shall solve problems by using functions. A ramp up with Collections and a little bit of Object Oriented concepts in python, Functional Programming can be a great curve to harness python's usability and simplicity. At the end of this session, participants will be able to use the collections library in python, list comprehensions , deal with classes , objects and write anonymous functions , lambda expressions and resolve traditional snippets to reduce , map and filters for each of the use case", - "Last Updated": "09 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college folks", - "Section": "Core python and Standard library", - "Speaker Info": "Currently working as a Software Development Engineer at Olacabs. http://sameera.me https://www.linkedin.com/in/sameera-sy During my freetime I try the below. https://stackoverflow.com/users/4303216/sameera-sy https://www.hackerrank.com/sameerasy https://leetcode.com/sameerasy https://doselect.com/@sameera.sy", - "Speaker Links": "Below are some of my sample works. https://github.com/sam95 I have also conducted a webinar on JS for JavaScript Meetup Bangalore group. https://github.com/sam95/js-for-newbies-3 https://www.youtube.com/watch?v=JXg1GT6zDGQ", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sameeras", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/functional-programming-with-python~eEQle/", - "title": "Functional Programming with Python" - }, - "188": { - "Description": "React has been out there for quite some time now and its arguably one of the hottest front end frameworks out there. But MERN architecture hasn't caught up. And that's what I want to teach/discuss in my talk at pycon. How MERN could be the hottest kid on the block in the upcoming days", - "Last Updated": "08 May, 2018", - "Prerequisites": "Javascript\nBeginner level React.\nLittle to no knowledge of Node, Express and Mongo", - "Section": "Web development", - "Speaker Info": "https://himanshuc3.github.io/\nSolving problems bit by bit. After all, computer is just bits. Cracking PJs and living life to not make the most of it but make the most of me", - "Speaker Links": "https://github.com/himanshuc3\nhttps://medium.com/@himan\nhttps://drive.google.com/file/d/1wzhC56jvrriO6XOogapWE2aOMN8Afsiz/view?usp=sharin", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "08 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mern-could-be-the-buzz-word~bDEkd/", - "title": "MERN could be the buzz word" - }, - "189": { - "Content URLs": "https://github.com/rahulbajaj0509/Automation-with-Ansibl", - "Description": "Ansible is software that automates software provisioning, configuration management, and application deployment. Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications\u2014 automate in a language that approaches plain English, using SSH, with no agents to install on remote systems. This workshop introduces a beginner to basic fundamentals of Ansible with easy to do hands-on exercises. The workshop introduces basic use cases of Ansible followed by an introduction to Ansible Inventory, Playbooks, Modules, Variables, Conditionals, Loops and Roles. Each mentioned topic is accompanied by a set of coding exercises giving the attendees a hands-on experience in developing Ansible Playbooks. Introduction to configuration management [15 mins] What is configuration management?\nAgent vs Agent-less\nPush and Pull configurations.\nImperative vs Declarative DevOps Concepts [10 mins] Infrastructure as code.\nDeterministic Builds/Deployments.\nIdempotency.\nCommunications channels \u2013 Message Queueing vs SSH Introduction to Ansible [30 mins] Requirements\nInstallation\nConfiguration Working with Ansible [100 mins] Ansible Inventory\nPlaybooks\nModules\nVariables\nConditionals\nLoops\nRoles\nAnsible Galaxy Ansible in DevOps environment [20 mins]\nQuestions and Answers [10 mins", - "Last Updated": "07 May, 2018", - "Prerequisites": "Pre-Requisites Basic Linux Administrator Skills\nOpen mind and spirit to learn. Software Requirements We will be using two centos7 vagrant machines for the workshop. Make sure you are using a Linux distribution and have vagrant configured with any of the providers like libvirt, virtual box, etc.\nIf you are unable to install vagrant on your Linux systems, then you might want to install Fedora operating system and come for the workshop, we can do the rest together", - "Section": "Developer tools and Automation", - "Speaker Info": "Rahul is an Associate Software Engineer, Red Hat. He is a part of the official foreman organization(https://github.com/rahulbajaj0509). He contributes mostly to the Foreman project and is a \u2018Red Hat Certified Specialist in Configuration Management\u2019. He is also the organizer of Foreman Pune Meetups", - "Speaker Links": "Blog: https://rahulbajaj05.wordpress.com/\nGithub: https://github.com/rahulbajaj050", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Rahul Bajaj (~rahul56)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automation-with-ansible-beginner-to-advanced~azY2e/", - "title": "Automation with Ansible: beginner to advanced" - }, - "190": { - "Content URLs": "https://docs.google.com/presentation/d/1DE-_l9N8Scu-M8d_bFxuKQak3TYipEDsGX5HIsB59s0/edit?usp=sharing PS: First Draft, need to organize it better and improve the demos", - "Description": "Dask is a general purpose parallel computing system capable of Celery-like task scheduling, Spark-like big data computing, and Numpy/Pandas/Scikit-learn level complex algorithms, written in Pure Python. Dask has been adopted by the PyData community as a Big Data solution. This talk focuses on the distributed task scheduler that powers Dask when running on a cluster. We will start by comparing Dask with the other solutions that are available for big data ETL and analytics . We will talk about how easily you can parallelize the work loads that you do with your favourite scipy libraries for eg Numpy, Pandas etc. Lastly we will also talk about how you can integrate Dask with your existing code and parallelize it's work load", - "Last Updated": "07 May, 2018", - "Prerequisites": " Good understanding of Python Programming Must have used any scipy library before Nice to have some idea regarding the big data tools available for analytics and ETL", - "Section": "Data science", - "Speaker Info": "I am an enthusiastic developer and aspiring entrepreneur who holds a particular passion for the intersection of web development and emerging technologies. I am constantly exploring innovative ways to solve real world problems and improve existing solutions. I genuinely enjoy working with people, taking risks, and developing new applications. I am currently working at Dubizzle as a Associate Software Engineer. Previously I worked at Corridor Funds as a Technology Architect where I built and Architected a data driven Loan valuation and Portfolio Management tool for retail and institutional lenders. I am open source contributor at Gluster, FOSS Asia, NGUI and GDG. Previously I lead a GDG Chapter in Gujarat. I have also spoken at tech meet ups and conferences like Women techmakers, Google Devfest, Google Cloud Next Extended, Mozilla Gujarat, Local GDGs and Startup Gujarat. In addition to that, I am always experimenting with new and interesting side projects", - "Speaker Links": " Github: http://github.com/smitthakkar96 Linkedin: http://linkedin.com/in/smitthakkar96", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "smit thakkar (~smitthakkar96)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/dask-distributed-data-science-in-a-pythonic-way~axLPa/", - "title": "Dask: Distributed Data Science in a pythonic way" - }, - "191": { - "Content URLs": "Will be uploading soon", - "Description": "Almost all developers spend countless hours on configuring, tweaking and micro-managing their dotfiles with an obsession to exactly have them like one wants them to be. I do too . Dotfiles are just configuration files like .vimrc and .gitconfig on your OS, that stores the settings you have for applications/environments/tools to make life easier while giving you more portability. Well, do you have to use bash scripts for initial setups of your dotfiles? or do you want to setup your dotfiles but don't want to learn or be limited by Bash? Do you forget to update/maintain your dotfiles periodically? Do you struggle with the installation of applications later on? \n Well, Python could be the answer to all of your problems. With Python, one can easily manage , maintain and do a lot more with their dotfiles. My talk would start with a basic intro of what exactly are Dotfiles? and what is the common way of setting them up? This helps beginners who are new to the topic, get interested and a quick recap of why dotfiles are important for all developers. Building up the momentum by visual queues and comparisons through slides, I would show how exactly Python does the same using Homely as Bash does. Later, work through the more intricate details by talking about the features one can implement using Homely and Python highlighting limitations of bash. Like Automation , Logging , git control , debugging , installation of applications and so much more . Summing up by demonstrating a number of scripts that I will be preparing in-advance to showcase the same features that we just talked about. This helps people grasp the talk, the topic, and \" the why we are doing, what we are doing \" part. Ending the talk , with a round of questions and showing the setup I use after months of searching through dotfiles repositories to leave them open to all the options they can choose from for setting up their dotfiles and pick the best setup from the knowledge they just gained. Sub Category : Developer Tool", - "Last Updated": "07 May, 2018", - "Prerequisites": "A laptop computer running any flavor of Linux. It would help if python 3 is already installed. Coming without a laptop is also fine. The presentation would be enough to understand", - "Section": "Others", - "Speaker Info": "I am a student who also happens to be Linux enthusiast, loves to code in Python, currently, part of Google Summer of Code 2018 under Sugar Labs and an active volunteer at PyDelhi and ALiAS . I friviously collect C&H comic strips because I like to... When I am not busy, I devote my time towards closing issues on GitHub and scooping through my twitter feed. Also, sometimes I like to write my thoughts and the things that I have learned on my blog, Mixster . Check it out", - "Speaker Links": "Professional Profile @ LinkedIn , Contribute @ GitHub , Blog @ Mixster I go by vipulgupta2048 all over the web. Feel free to connect/talk with me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vipul Gupta (~vipulgupta2048)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/keeping-your-dotfiles-in-check-with-python~dw7Xd/", - "title": "Keeping your Dotfiles in check with Python" - }, - "192": { - "Description": "DNS is a non-encrypted protocol. DNS responses which are sent over UDP or TCP lack confidentiality, privacy and security. DNS often contains password files, geolocations, email service and fax numbers, certificate identity and pinning for TLS and much more. Parsing DNS without encryption would lead to different vulnerabilities such as eavesdropping and spoofing. DNS over HTTPS(DoH) is a web protocol that argues for sending DNS requests and receiving DNS responses via HTTPS connections, hence providing query confidentiality. DoH provides more than just privacy \u2013 it also helps guarantee the integrity of the response users receives their requests. Because the DNS response is invisible between responder and user, ISPs and others in the end-to-end network chain can't interfere with the responses. Moreover, Responses from the use of recursive resolvers to clients are the most vulnerable to undesired or malicious changes, because generally recursive resolvers do not encrypt any of your queries. Henceforth, we would be discussing the implementation and parsing of DNS over HTTPS. Further, we provided added support for handling IPv4 and IPv6 DNS packets (A + AAAA records) as well as support for EDNS for edns-client-subnet usage. The integration with HTTP provides a transport suitable for traditional DNS clients seeking access to the DNS. In the end, we will discuss how our client will be sending DNS queries and get DNS responses over HTTP using https:// and implies TLS security integrity and confidentiality. Furthermore, I plan to put some light on how DNSSEC validation is getting involved here with DNS resolution through HTTP to provide ultimate privacy and security support for \n the DNS packets", - "Last Updated": "06 May, 2018", - "Section": "Networking and Security", - "Speaker Info": "I\u2019m currently in my sophomore year, pursuing an undergraduate degree in Computer Science and Engineering from Amrita University. I\u2019m an active member of a FOSS club in our university(FOSS@Amrita). I started actively contributing to various open source organizations from the year 2016. Initially, I started my career in Open Source by contributing to KDE. I was selected for Season of KDE(KDE-SoK) 2016-17 in which I worked on an astronomy software named called Kstars. Further, I was selected for Google Summer of Code 2017 under KDE, where I worked on a project for a libre graphics software, Krita. My work involved introducing a data sharing module in it. The module enables communication between Krita and a remote KDE server in order to help users save and publish their data online. This also required modifying the underlying framework to enable client/server communication. I have been selected for Google Summer of Code for the 2nd time, where I am working on the project Wget2 under GNU organisation. I GSoC project involves adding support for DNS over HTTPS in Wget2. I was invited as a speaker for KDE India Conference 2017 in IIT Guwahati, where I gave a talk on the topic \u201cObject tracking using OpenCV and Qt\u201d. Further, I will be travelling to Austria on August to give a talk in KDE conference, Akademy and will be talking on the topic \"Strengthen Code Review Culture: rm -rf \u2018Toxic Behaviors", - "Speaker Links": "http://anikethfoss.wordpress.com http://gitlab.com/aniketh01/ https://conf.kde.org/en/Akademy2018/public/speakers/1", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Aniketh Girish (~Aniketh01)", - "created_on": "06 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/privacy-concerns-how-dns-resolves-over-https~avLnd/", - "title": "Privacy concerns: How DNS resolves over HTTPS" - } -} \ No newline at end of file From fc64312694fb0a347e65f34b8a701814969bb27a Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Fri, 13 Jul 2018 20:03:18 +0530 Subject: [PATCH 07/17] latest cfp json --- cfp_crawler/proposals.json | 6697 +++++++++++++++++++++++------------- 1 file changed, 4387 insertions(+), 2310 deletions(-) diff --git a/cfp_crawler/proposals.json b/cfp_crawler/proposals.json index 4760e24..b9ec0a7 100644 --- a/cfp_crawler/proposals.json +++ b/cfp_crawler/proposals.json @@ -1,2833 +1,4910 @@ -{ - "1": { - "Content URLs": "Would be uploaded soo", - "Description": "My talk would be starting from the very grounds of machine learning . What is it and how is it connected with our biological brain. I will be introducing some biological concepts and infrastructure of our brain to explain to them how our natural ability of thinking and deduction work, because at last the whole field of artificial intelligence is just an attempt to mimic our brain. Isn't it?\nThis will be through a series of fun QnA . Then we will see the mathematics core which enables us to lay down the logic and basics of the brain as formulas . \n- Then we will start with the classic linear regression . Will study the basic idea behind it and also see what kind of problems we should apply it.\n- Next will be the logistic regression , a classification algorithm. Learn the difference between these two and how logistic regression could be implemented and study the beautiful mathematics behind it. \n- Then we will go for a clustering algorithm, that is, Knn . Study the simple dynamics and application of this algorithm\n- Then a glimpse over the structure and mathematics of neural network . As this talk is for the novice I would keep the mathematics to the minimum and would no go deep into \"deep\" learning.\nWe will wrap up seeing some of my projects in action so that the audience could feel the power of AI", - "Last Updated": "27 Jun, 2018", +[ + { + "Content URLs": "Will add slides later. Have added links to papers in my description", + "Description": "Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources. Compression of Neural Networks (NN) has become a highly studied topic in recent years. The main reason for this is the demand for industrial scale usage of NNs such as deploying them on mobile devices, storing them efficiently, transmitting them via band-limited channels and most importantly doing inference at scale. A number of papers have been published in last few years, proposing different approaches to minimize the footprints of neural networks. The aim of my talk will be to summarize recent developments and techniques in this field, by quoting benchmarks, algorithms and results from papers. On a superficial level, there are two basic types of compression are Network Pruning and Quantization. Network Pruning The motive behind network pruning is to selectively nullify or remove some nodes in order to reduce the size of the NN without losing much accuracy. Not only does this reduce the space required to store the model but also reduces the number of computations for sample. A number of papers in the last 2 years have suggested using Bayesian inferences and Variational Dropout , a probabilistic approach to estimating deterministic weights and selectively pruning some of them after sparsifying respective weight matrices. Quantization Conventionally, weights are stored and operations are performed with 32bit floating point numbers but with the rising need for running models on constrained devices, neural networks can be further compressed by either reducing the number of unique weights by clustering or by reducing the number of bits required represent weights , which also adds a regularizing effect, often resulting in higher accuracy than raw models", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Knowledge of Bayes Theorem, Convolution Neural Networks and common Image Classification datasets", + "Section": "Embedded python", + "Speaker Info": "Hello world. I\u2019m Vishal Gupta, a final year CSE undergrad at SSN, Chennai, India. A Python programmer by heart and ML enthusiast by inspiration, I have worked on a number of different projects, some out of boredom and some for startups. This summer I had to chance to work at Microsoft Research India (Bangalore), on using Bayesian Compression on Object Detection Networks (tiny-yolo) and deploying it on an FPGA board. I was working with a team from IIITD guided by Prof. Saket Anand. I'm also participating in Google Summer of Code 2018 under Debian. Past Experience : Chatbot intern at GoBumpr, Chennai CV intern at XR Labs, Chennai NLP intern at BicycleAI, Banglore", + "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Vishal Gupta (~vishal11)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/compression-of-neural-networks~dBmNb/", + "title": "Compression of Neural Networks" + }, + { + "Content URLs": " Winning Solution for Analytics Vidhya Hiring Hackathon Winning Solution for TechGig Machine Learning Hackathon Feature Engineering by Kaggle Expert Organization for learning competitive data science solutions - MLByte ", + "Description": "With advancements in machine learning and artificial neural networks, the answers to previously unknown questions are surfaced. It is the data and the feature engineering aspect that makes this development a great hype of the 21st century. Albeit the algorithm being super complex and extraordinary at solving a task there is always need of feature engineering and crunching the numbers right that help models and neural networks understand the trend and classes better. This proposal shall cover the feature engineering for competitive machine learning problems that are used at platforms like Kaggle, Analytics Vidhya, and HackerEarth. Additionally, this will cover a case study of a winning solution and the inferences from the competitions", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Python Pandas Scikit-learn", "Section": "Data science", - "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", - "Speaker Links": "udayupreti.m", + "Speaker Info": "Mohammad Shahebaz is a data scientist intern at Analytics Vidhya. He is also India's finalist in Microsoft World Championship 2013, the finalist at Master Orator Champion 2016, and has bagged a regional gold medal in International Maths Olympiad (IMO). Currently pursuing out the latest trends in Machine Learning and Artificial Intelligence while winning a competitive position at National level competitions and on Kaggle platform. He loves open-source and have contributed to organizations like Google Web Fundamentals, Scikit Learn, FOSSASIA and is serving as Social Committee Lead at Oppia.org in Google Summer of Code. On a path to set machine learning and artificial intelligence to Indian masses, he open-sources his code and approaches at GitHub and organization MLBYTE", + "Speaker Links": " LinkedIn Profile GitHub Profile - shaz13 Rank 2 at Analytics Vidhya overall leaderboard Mentions Master Orator Champion 1st runner-up of TechGig Machine Learning Hackathon - June 8, 2018", "Target Audience": "Beginner", "Type": "Talks", - "author": "uday1201", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/evolution-and-basics-of-machine-learning~bWzxa/", - "title": "Evolution and basics of Machine Learning" + "author": "Mohammad Shahebaz (~shaz13)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/feature-engineering-for-kaggle-and-machine-learning-competitions~e0Pye/", + "title": "Feature Engineering for Kaggle and Machine Learning Competitions" }, - "2": { - "Content URLs": "http://www.thedurkweb.com/automated-anonymous-interactions-with-websites-using-python-and-tor", - "Description": "Need to get some repetitive task done on your web browser? Want to automatically fill boring forms? Or maybe you want to crawl pages that annoyingly check whether you are a browser or a robot. Or maybe you want to repeatedly bias an online poll in your favour (as long as you don't harm anyone). Circumvent all of that with Selenium, the browser automation tool. And if want you want to protect your IP while doing it then just fire up tor-selenium browser, which gives you the power of tor and browser automation. In this talk: I'll show you how to set up the browser. How to access the website through code. How to design your script to navigate through the pages and button clicks. How to effectively do your activity, like filling up text fields etc. And then a demo of it working completely.", - "Last Updated": "27 Jun, 2018", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", + { + "Description": "draf", + "Last Updated": "10 Jul, 2018", + "Section": "Core python and Standard library", + "Target Audience": "Advanced", "Type": "Talks", - "author": "Ved Mathai (~ved47)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automate-anything-on-the-web-using-python-bindings-for-tor-selenium-and-hide-your-ip-while-doing-it~eVyXd/", - "title": "Automate anything on the Web using Python bindings for Tor-Selenium and hide your IP while doing it." + "author": "bhanu546", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/repurposing-yolo-for-detecting-country-stamps~e72yd/", + "title": "repurposing yolo for detecting country stamps ." }, - "3": { - "Content URLs": "in progres", - "Description": "Data classes have been introduced in Python 3.7 (Refer to PEP 557 -- Data Classes). This talk is to introduce data classes to the audience. Talk about why data classes and how they are different from other alternatives like named tuples, et", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Knowlede of Object Oriented Programming with Pytho", - "Section": "Core python and Standard library", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.\nI have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delhi I have done a talk \"How import works in Python\" at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar\nlinkedin profile - https://www.linkedin.com/in/sasidonaparthi\ntwitter handle - @sdonapa", - "Target Audience": "Intermediate", + { + "Description": "IBM came up with PowerAI Vision to grab its share - out of available AI Vision 1.2$ billion market opportunity.\nPowerAI Vision Minimum Viable Product (Vision 1.1.0) was GA'ed on May 25th, which can run on standalone Linux and Ubuntu OS, on Nimbix cloud and can also run on IBM Cloud Private. This was an important achievement for IBM as it is expected to accelerate IBM latest Power processor P9 revenue.\nIBM PowerAI Vision is a video and image analysis platform that is built for IBM Power Systems servers, which includes tools and interfaces for anyone with limited skills in deep learning technologies. One can use PowerAI Vision to easily label images and videos that can be used to train and validate a model and perform image / video inferencing. The first regular PowerAI Vision release was MVP. Vision MVP is composed of different Docker images maintained and managed by Kubernetes", + "Last Updated": "10 Jul, 2018", + "Section": "Data science", + "Speaker Info": "Durgarao Simhadri, Sourav Biswas, Madhuri Katragadda - All are working for IBM PowerAI Vision Project in IBM Hyderaba", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/what-you-need-to-know-about-data-classes-in-python-37~dRrEd/", - "title": "What you need to know about data classes in Python 3.7" + "author": "Sourav Biswas (~sourav31)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/ibm-powerai-vision~b2Q1a/", + "title": "IBM PowerAI Vision" }, - "4": { - "Content URLs": "Tutorial Series https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-2 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-3 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-4 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-5 Github Repo (Most starred repo for a Python implementation of YOLO v3, at 589 stars at the time of speaking) https://github.com/ayooshkathuria/pytorch-yolo-v", - "Description": "The workshop will walk the audience on how to implement a state of the art object detector (YOLO: You only look once) from scratch using the PyTorch deep learning framework. The main The aim is not to merely show the audience how to implement the detector that can work on videos, but give them a deep insight about the problems that rear their heads only when one is implementing a deep architecture. Some of these issues include, Rapid Prototyping with PyTorch : Which PyTorch classes and abstractions to use to quickly code up neural network. How to implement a layer if it doesn't already ship with PyTorch. Our detector has 3 such layers! How to deal with complex architectures efficiently : What if your network has more than a 100 layers? Our detector certainly has 106 ! Do we write 106 lines of code for each layer? What if we want to run our detector over a folder containing 100000 images that we can't fit into our RAM at once. Best PyTorch practices to get around problems like these will be discussed. Speeding up Python code with Vectorisation : Python can be a slow language, but PyTorch does provide a lot of functions that are merely wrappers for super fast C code under the hood. Vectorisation and broadcasting will be covered in great detail. Using vectorised code instead of loops to do iterative tasks can give speed ups as much as 100x. Our detector can not work in real time without these optimisations. Managing GPU resources : How to write device-agnostic code, parallelize GPU/CPU ops, practices to reduce redundant GPU memory usage, and how to time GPU code. We will review the entire code base, and spend much time on justifying design decisions. A lot of non-critical code will be provided as it is to the audience, while they are expected to code along when it comes to the critical parts. These parts would be discussed in greater detail. Important PyTorch features might also be demonstrated using toy examples outside the detector code base, which the audience is also expected to code along. A docker image as well as Jupyter notebook will be provided to the audience. Google Colab may also be considered with notebooks provided. Most of the tutorials online demonstrate how to write code that is more proof-of-concept rather than being performant. When it comes to learning to code complex architectures, especially when we are transitioning from beginner to intermediate stage, most of us have to rely on the laborious process of reading open source code. The idea of this workshop is to help audience move along this journey", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Knowledge of Python Basic understanding of convolutional neural networks, image classification and preferably, but not necessarily object detection (Will spend 15 min or so giving an overview of YOLO algorithm) Basic understanding of PyTorch (the level that can be reached by taking the official 60 min tutorial)", + { + "Content URLs": "https://github.com/Imaginea/i-tagge", + "Description": "This talk focuses on below two points Software architecture which helps to try different models on different data sets. In the end we will take a real world use case where our architecture helped in speeding up the development process. Bi-Directional LSTM with CRF. ", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Knowledge of Python, ML and DL", "Section": "Data science", - "Speaker Info": "I'm currently an research intern at a DRDO Lab where I work on video semantics, detecting violence as well as unusual activity in surveillance footage. My other interests include weakl supervised, unsupervised learning and generative modelling using GANS. I've recently graduated college, and while at college, I founded AI Circle, SMVDU, a club dedicated to helping students get started with machine learning through lectures and hands-on sessions, many of which were conducted by me. I am very passionate about sharing what I've learned, and write articles regularly at Paperspace and Medium", - "Speaker Links": "Paperspace blog: https://blog.paperspace.com/author/ayoosh/ Medium : https://medium.com/@ayoosh Github : https://github.com/ayooshkathuri", + "Speaker Info": "Anil and Gaurish are part of Data Science team at Pramati technologies. They work on building ML and DL models to solve real world problems", + "Speaker Links": "Anil Kumar - https://www.linkedin.com/in/anil-kumar-reddy-309552ab/ Gaurish - https://www.linkedin.com/in/gaurishthakkar", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ayoosh Kathuria (~ayoosh)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-implement-a-yolo-object-detector-from-scratch-using-pytorch-and-opencv~aQq9a/", - "title": "How to implement a YOLO object detector from scratch using PyTorch and OpenCV" + "Type": "Talks", + "author": "Anil Kumar Reddy (~anil_kumar46)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-model-for-sequence-tagging~egNGd/", + "title": "Deep Learning model for sequence tagging" }, - "5": { - "Content URLs": "Slides will be uploaded soon. Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv", - "Description": "There lies a huge gap between a website made as a hobby/college project and that made for professional purposes. The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! My talk is going to be about highlighting the flexibility and power python gives in this case.\nI'm going to share my experience of building a tool for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/). The tool summarizes the contributions of the Wikipedia editors and presents it in a CV-like format. The biggest challenge here was dealing with millions of edits and doing all the related computations within seconds. Without any kind of optimizations, the page took 3 hours to load. Through my talk, I want to bring out the journey from 3 hours to 3 seconds on the table! Broad outline of my talk is as follows: Deciding upon the web framework : In this, Django, Flask and Pyramid will be compared. Reducing the response time : When one is dealing with a dataset as huge as that of Wikipedia's, response time becomes of paramount importance. Optimizations like implementing a cache layer , using cron jobs , sessions etc will be discussed. Also, design choices will be compared - like cache layer using database vs sessions in python. Database Optimizations : In this I'll be covering how database choice and query optimizations can affect the performance when dealing with large datasets. In this, ORM will be discussed in detail. Component based approach with plain javascript : When one component of your website slows down the rendering of the whole page, what should one do? This is going to be another aspect that I'm going to touch upon - dividing page into pagelets without using any javascript framework. Let code speak of professionalism : Lastly, I'll be discussing about the good coding techniques and practices that should be used. (Like making dependency graph of modules for better modularity.) Hope you will find this talk interesting. :)", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic knowledge of Python, Django, Javascript and querying RDBMS is required", - "Section": "Web development", - "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia.\nOther than coding, I love reading, writing and trying out new things", - "Speaker Links": " Blog: https://medium.com/@meghasharma4910 Github: https://github.com/MeghaSharma21 Outreachy project: https://github.com/MeghaSharma21/WikiCV Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018", - "Target Audience": "Beginner", + { + "Content URLs": "https://www.jaegertracing.io", + "Description": "Distributed tracing is a technique for monitoring & profiling systems built on microservices architecture. Distributed tracing is quickly becoming a must-have component in the tools that organisations use to monitor their complex, microservice-based architecture. Jaeger is an open source tool and part of CNCF project released and worked by Uber. Outline: Introduction to Microservices\nDistributed Tracing & OpenTracing standards\nUsing Jaeger to monitor microservices-based distributed systems covering: - Distributed context propagation\n - Distributed transaction monitoring\n - Root cases analysis\n - Service dependency analysis\n - Performance / Latency optimization Implementing Tracing with python library live and transforming existing code to traceable code.\nDemo Jaeger with an (python code) example from a monitoring perspective (specific to solve latency issue).\nDemo of tracing to collect application metrics. And more", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Knowledge of Python and application development", + "Section": "Core python and Standard library", + "Speaker Info": "Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", + "Speaker Links": "https://www.linkedin.com/in/vivsridh/ https://twitter.com/vivek_sridha", + "Target Audience": "Advanced", "Type": "Talks", - "author": "Megha Sharma (~megha480)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/optimizations-in-web-development-journey-from-a-college-project-to-a-product-using-django~dPp4d/", - "title": "Optimizations in Web Development: Journey from a college project to a product using Django" + "author": "Vivek Sridhar (~vivek861)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tracing-http-request-latency-using-jaeger-with-python~e3POa/", + "title": "Tracing HTTP request latency using Jaeger with Python" }, - "6": { - "Content URLs": "Will be updated soon", - "Description": "In this talk, I will provide a concise understanding of Threading and Global Interpreter Lock(GIL) in Python. In the modern era of hybrid cores and processors, there is an in demand need for concurrent and parallel programming paradigms. Python, since its inception has amazing support for single threaded applications. The extensive use of Python in booming fields like Machine Learning has paved the way to constantly improve multi-threaded applications in Python. I will speak from ground level covering very crucial aspects of Threading and Locks which will pave the way for community to develop better Python applications. Program outcomes: How threading can improve performance, its pros and cons. What works best in which environment between threads and processes. Why GIL matters the most in Python How to leverage the power of open source source code to understand the crux of language. Contents to be covered: 1. Threading for noobs: Terminologies: Process, threads, multithreading, multiprocessing, types of threads, locks, mutex, CPU and I/O bound processes. Multithreading in Python: Threading module (with example) Comparative analysis of Sequential vs Multithreaded execution in Python (with example) 2. Understanding the global interpreter lock (GIL): What and why of GIL Impact of GIL on CPU and I/O Bound Processes In-depth understanding of GIL using cpython interpreter source code Reference counting Ticks via context switching 3. Infamous concepts: Cooperative vs Preemptive multitasking Parallelism vs Concurrency Thread Safety in Python 4. Removing the GIL: Famous GIL removal patch Guido on GIL, Larry Hastings Gilectomy 5. Questions Agenda: 0 - 6 minutes : section 1, Threading for noobs 6 - 15 minutes : section 2, Understanding GIL 15 - 25 minutes : section 3, Infamous concepts 25 - 28 minutes : section 4, Removing the GIL 28 - 30 minutes : section 5, Questions ", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basics of Python: Class, objects, list, libraries", + { + "Description": "draf", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "draf", "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself from scratch. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", + "Target Audience": "Advanced", "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-multithreading-by-deciphering-the-cpython-interpreter-source-code~aOora/", - "title": "Understanding multithreading by deciphering the cpython interpreter source code" + "author": "bhanu546", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mlops-in-draft~e5XKd/", + "title": "MLOps in draft" }, - "7": { - "Content URLs": "https://gautam-ankit.github.io/HomeAR", - "Description": "In this project, we are going to create a home finder in which we are going to give an individual marker/bar code to each and every home and going to create a web-app which will tell about the home on starring the camera on the marker/bar code. This idea will help out to find some place way better than the Google maps because one can generate its own marker for his/her home and can edit the details of there home, through which one can recognize the home. For management of this data we are going to use several concept of Big data also. But this is the best way possible to implement and link augmented reality with python", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "HTML and CSS and basic Javascript,\nbasic python ,\nsome programming concepts", + { + "Content URLs": "tes", + "Description": "tes", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "tes", "Section": "Core python and Standard library", - "Speaker Info": "As a Microsoft student partner, I gave several presentations for Hour of code. And as a Mozilla campus club caption, I gave several presentations for Virtual reality and Augmented reality using Aframe web framework", - "Speaker Links": "https://www.linkedin.com/in/ankit-gautam-9b0524108", + "Speaker Info": "tes", "Target Audience": "Advanced", "Type": "Talks", - "author": "Ankit Gautam (~Gautam-ankit)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/home-finder-using-python-and-augmented-reality~dNnvd/", - "title": "Home finder using Python and Augmented Reality" + "author": "bhanu546", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/ner-in-legalcontracts~b64Ve/", + "title": "NER in legalcontracts" }, - "8": { - "Content URLs": "So, Slides can be seen here: https://slides.com/tanayagrawal/efficient-hyperparameter-optimization#/ Full content is available here: https://github.com/tanayag/pycon_18_hyperopt You can also have a look at my article: https://blog.goodaudience.com/on-using-hyperopt-advanced-machine-learning-a2dde2ccece7 In the Repo iris.csv is the dataset that we'll work on. docker folder contains the scripts to setup Environment \"Introduction to Hyperopt.ipynb\" is iPython Notebook which contains the implementation which we'll work on during workshop and understand the concept \"link_to_slides.txt\" contains the link to our presentation", - "Description": "Hands on Experience with Advanced Hyper-parameter Optimization Techniques, using Hyperopt We'll go step by step, starting with the Hyper-parameter optimization with SkLearn's Grid Search, we'll compare it with the more effective Hyper-Parameter Optimization TPE Algorithm implemented in Hyperopt.\nWe'll also go through on how to parallelize the evaluations using MongoDB making the optimization even more effective. A Docker Image will be provided, so that participants won't have to waste time in setting up the environment. The Workflow of the Workshop would be: We will start with a slide presentation so that participants get some insight on what they are going to do. After that we'll shift on to a Juypter Notebook(pre-installed in the docker environment, so you can just focus on the implementation part), here they will implement the code, and see the best algorithms of hyperparameter optimization working. After that we'll show a working demo of a problem that we were working on and solved using Hyperopt during our Summer Intern at MateLabs. After attending this workshop you will be able to apply Hyper-parameter optimization using better algorithms which decides the hyper-parameters based on information. In short much much efficient model training", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic Python Coding and a little familiarity with Machine Learning/Data Science", - "Section": "Data science", - "Speaker Info": "Tanay Agrawal Working on Machine Learning/Deep Learning and also an Open Source Enthusiast. Currently in Final Year of his Engineering. He is working as Deep Learning Intern at Matelabs. He along with team at MateLabs is creating Meta Algorithms, so that user even with minimum or no knowledge of Machine Learning would be able to use it. Also he is a contributor at SymPy. He has previously worked on state of the art Classification and Object detection Models as well. He has previously conducted Python workshop at SFD-SMVDU and also he conduct the session of AI Circle at his College regularly. Anubhav Kesari Currently at fInal year of engineering from IIIT Guwahati. Two worked on the same problem and solved it using Hyperopt. Anubhav is the summer intern at MateLabs as well. He has worked at Cadence Design Systems in summer of 2017 as Software Development Intern. He has also been working on development of blockchain based distributed neural networks at MateLab", - "Speaker Links": "Tanay Agrawal https://github.com/tanayag https://angel.co/tanay_agrawal Anubhav Kesari https://github.com/kesarianubhav https://www.linkedin.com/in/anubhav-kesari-588a03131", + { + "Content URLs": "https://drive.google.com/file/d/18-0JPLC7d8NduXd00DOk9HzaoJYaXLDd/view?usp=sharin", + "Description": "DevOps is evolving fast with the massive growth that chat-based automation and processes has seen in the recent years. We focus on how to leverage the bot-enabled chat platforms like Slack, MSTeams, Mattermost to your advantage in the context of DevOps using various ChatOps techniques. We also focus on the building and deployment of ChatOps using Python, Django, Docker and Kubernetes. An entire array of DevOps processes such monitoring, CI/CD, analytics can be streamlined through different aspects of ChatOps - bots, cross-application workflows and tying together the internal tools, external tools and microservices in any team's DevOps tool-chain. Productivity, speed and transparency in DevOps can be achieved with the use of ChatOps. Our intention with this workshop would be to focus on the development of ChatOps using Python, Django, Docker and Kubernetes. While several tools are available for developers to build and implement ChatOps for their organization, we believe that the combination of these tools allows for the most versatile, scalable, flexible product. Through our talk, the participants will learn to use these platforms for advanced ChatOps development to automate Dev and DevOps in their teams. We will cover various use cases for all stages of Dev and DevOps cycle. This would give the audience a chance to identify their needs and current state. Next comes the ways these requirements can be tackled through various tools like Python, Django, Docker and Kubernetes(we also cover the advantages and drawbacks of the same). After a well-rounded view of how to implement ChatOps for all kinds of DevOps teams - based on requirements, preferable architecture and choice of language, we end with an interactive Q&A session", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic Python \nDjang", + "Section": "Developer tools and Automation", + "Speaker Info": "I am Ankur, founder and CTO at YellowAnt . I take care of Managing the product architecture, system design and infrastructure design. I have been working on Python for 5 years now. I have intensive knowledge of AWS, Scalling application, Kubernetes, Docker, Databases, etc, and have been conducting developers sessions, meetups and workshops for the same. Prior to founding these companies, I worked with Sasken Communication and IBM India Software labs for 5 years. There, I worked on Perl, C/C++, DB2, XML and other technologies. I have also worked with universities in structuring their Data Mining courses to incorporate real-world use cases, and as a judge for events in TGMC (Organised by IBM) and Engineer (Annual TechFest organised by NITK Surathkal). I have also consulted with Banks, Startups and NGOs for their Tech Stacks", + "Speaker Links": "https://github.com/yellowanthq/\nhttps://twitter.com/YellowAntHQ\nhttps://github.com/ankurrawal\nhttps://twitter.com/ankurrawal1987\nhttps://www.linkedin.com/in/ankur-rawal-53230b13/ https://blog.yellowant.com/6-reasons-why-chatops-make-workplace-better-875659187d0c\nhttps://blog.yellowant.com/how-to-build-a-yellowant-application-in-7-easy-steps-c0feb38c3e5d\nhttps://blog.yellowant.com/advanced-chatops-with-microsoft-teams-part-1-1845acdc11a5\nhttps://blog.yellowant.com/advanced-chatops-with-microsoft-teams-part-2-real-world-use-cases-6470975e574", "Target Audience": "Intermediate", "Type": "Workshops", - "author": "tanay_agrawal", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-ml-learn-how-to-improve-accuracy-by-optimizing-hyper-parameters-using-hyperopt~aMmGa/", - "title": "Advanced ML: Learn how to Improve Accuracy by optimizing Hyper-Parameters using Hyperopt" - }, - "9": { - "Content URLs": "Will be uploaded soon", - "Description": "Python - Turing Complete and easy at the same time. Given its simplicity, one may be tempted to use it to solve a problem of any magnitude. But as the codebase scales, so does the difficulty in managing it. And as the applicability scales up, so does the difficulty in maintaining performance. In this workshop, we will walk through how these problems crop up in the first place, and how to tackle them. This workshop will NOT cover scalability from the perspective of distributing data loading and computation across multiple compute units (horizontal scalability). We will focus more on how to write code from the very start that is both efficient in performance and makes a larger codebase manageable. The topics we will go through are: 1.Performance - How should one write \"fast\" code Finding the bottleneck - Profiling Compiling Python to C - JIT vs AOT / Cython vs Numba vs Pythran vs PyPy - How they differ and choosing which one is for you Concurrency - To parallelize or not to parallelize, to sync or not to sync Choosing the right data structures Hacks and bits that can get us the extra performance 2.Design Principles - How should one write \"good\" code, because we have all written code that we have difficulty in understanding ourselves in no time Logging - Keeping track of what happened when and where Type Checking - The why and the how Unit Tests and beyond", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Cython, numba, and pythran installed. All of them are available on pip/conda Working knowledge of Python", - "Section": "Others", - "Speaker Info": "I am a final year student at IIT Madras. I currently lead the CV and AI team at Detect Technologies and have headed the CVI group at CFI, IIT Madras in the past. I love learning new things about how and why things work, and love sharing that knowledge", - "Speaker Links": " Personal Website Github Linkedin StackOverflow", - "Target Audience": "Intermediate", + "author": "Ankur Rawal (~ankurrawal)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/accelerating-devops-with-chatops-using-python-django-docker-and-kubernetes~b80gb/", + "title": "Accelerating DevOps with ChatOps using Python, Django, Docker and Kubernetes" + }, + { + "Content URLs": "https://github.com/RushikeshJachak https://github.com/Heisenberg020", + "Description": "Many people are claiming to learn machine learning using standard libraries while not knowing the math behind it. My objective is clear to implement and give a intuition of linear regression model while at the same time telling what steps makes a model good fit for training sets. It includes:- A. Getting comfortable with libraries by actual implementation Introduction to numpy, pandas and matplotlib Exploring data using pandas Exploring relation between various variables using matplotlib. Knowing what are the problems are for a bad model. B.Exploratory Data Analysis :- Classifying features as continuous or categorical. Handling missing data. Feature Extraction and Selection. Correlation and causation. Dummy Variables Visualizing Data C. Implementation of Model Cost function Gradient Descent Normal Equations ", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Basic knowledge of python like defining function, declaring variables. Knowledge of Matrix Basic Mathematics.", + "Section": "Data science", + "Speaker Info": "I am Rushikesh Jachak, Currently pursuing computer science and engineering in government college of engineering, Aurangabad. I moved towards python from last two months due to my interest in data science field especially machine learning. I am complete novice in python environment, i do not know the hooks and crux of python but i do believe the more you share more you learn.So i would definitely like to share my journey till know and and knowledge of maths and intuition behind the most common algorithm of ML. I also have a bit knowledge of Big-data technologies such as Hadoop hive, and poses a keen interest in field of Data Science", + "Speaker Links": "https://github.com/Heisenberg0203/Kaggle https://github.com/Heisenberg0203/MachineLearning/tree/master/Week1 https://www.linkedin.com/in/rushikesh-jachak-44b723135", + "Target Audience": "Beginner", "Type": "Workshops", - "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-not-break-your-head-or-computer-writing-python-at-scale~dLlrd/", - "title": "How to not break your head (or computer) writing python at scale" - }, - "10": { - "Content URLs": "https://en.wikipedia.org/wiki/Decentralized_autonomous_organization\nhttps://blockchaindevs.github.io/MeetupDA", - "Description": "Open Source Communities and their management. How things work currently A case study of different open source organizations: Advantages and disadvantages of current systems. The issues with Open Source organizations are nothing new, what are the possible solutions available? DAO and automation of majority of the tasks of a \"Open by default organizations\" What part of the organization can be automated, what can't. Important Aspects that usually breed trust among members::\n - Transparency\n - Consistency & Automation\n - Inclusion & support Our Proposal We will be posting codebase and complete websites and mobile apps that offer these solutions: Automated and transparent membership procedure. Transparent Public Elections on Blockchain for a board with automated publication of votes and results. Automate votes based on proposals Automated Procedure to apply for grants: with voting members and results being put up on Blockchain Automated meetings with MOM being recorded and put up on blockchain. Testing Proposal from the ground up: Start Small and test if these methods work locally in meetup groups \n- Automation of Tasks around meetups:\n...\nWe will keep updating here as and when we have deployed solutions on blockchain Tools used for these automation: Blockchain Dapps using : Solidity & Vyper\nPython: Kivy Framework for mobile apps and Web3.js & other such frameworks. Repos:\n They will be made online shortly, currently the experimentation is going on the following repos: https://blockchaindevs.github.io/MeetupDAO please excuse for the alpha quality of the software as they are just experiments as of now. This is a open source initiative based on the needs we feel we have seen arise in open source communities around us. Ultimate Goal Use this proposal as a catalyst and create small Organizations in local communities testing this theory. If things work in local communities, create a National Level Organization for managing the tasks around PyCon India This is just one of the hopefully multiple proposed solutions for moving on post PSSI", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "A willing ness to contribute, ability to learn. \nOpen Mind to experiment even if it leads to failure", - "Section": "Developer tools and Automation", - "Speaker Info": "http://github.com/akshaurora Akkshay is huge open source enthusiast, he has helped bootstrap different communities around Kivy, PyDelhi, ILUGD, BlockchainDevs , HyperLedger Delhi/NCR & chaired conferences like PyDelhiConf, Pycon-India, Global Blockchain Conference. He has been involved and working on blockchain based projects from 2011 onwards, he is one of the core developers of Kivy python framework & Electrum bitcoin wallet that has been built on top of it", - "Speaker Links": "http://github.com/akshauror", - "Target Audience": "Advanced", + "author": "rushikesh jachak (~rushikesh)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/implementation-of-linear-regression-from-scratch-using-numpy-pandas-and-matplotlib~e9PBd/", + "title": "Implementation of Linear Regression from scratch using numpy, pandas and matplotlib" + }, + { + "Content URLs": " Research paper - Vritthi framework for IT recruitment based on machine learning techniques Slides of other talks can be found on Speakerdeck", + "Description": "Abstract Want to learn how you can use the huge amounts of open data available on social platforms like Twitter, GitHub and StackOverflow to build a profile for a software developer? Yes, it's possible using python's sci-kit library. Mine data, extract features, compute quotients and finally, visualize! Detailed description The talk will start with an overview of data mining and machine learning concepts, during the course of which common misconceptions about data science would be cleared. As a real life example, the problem statement of job-seekers and recruitment is introduced. This then leads to the solution Vritthi , an open source project and then the technical aspects follow. Vritthi uses data mining and machine learning to help job-seekers to understand their skill sets and take up courses that would help them improve their technical expertise. Vritthi can automatically calculate a professional quotient by collating data from websites like GitHub, StackOverFlow and LinkedIn. This analysis is a result of parsing thousands of similar profiles available through the APIs of the above websites. GitHub archive is one of our data sources which actually helps set standards to coding competencies of individual profiles. Collection of data from GitHub using its API is explained in detail, along with the feature-set used to analyze profiles. Once the data is collected from the API, it passes through the data cleaning phase after which a set of features are extracted. These features could be as simple as number of commits, number of projects in a particular programming language, and so on. Right after this, python sci-kit is used to build the data model that\u2019s required for analysis. A supervised learning model is used which consists of two phases - clustering profiles and computing quotient values. Once the data model is ready, computing technical quotient values per programming language or skill is focused upon. For example, \u201cprogramming languages used\u201d is one of the attributes of the feature vector. Finally, the computed quotients are visualized using a web application which uses Python\u2019s Bokeh visualization library. Thus, classic data mining and machine learning have been employed on openly available data to solve a specific problem statement. Who is this talk for? Python developers who\u2019d like to explore sci-kit Web developers who\u2019d like to explore python\u2019s bokeh library for data viz. Entrepreneurs who would like to see how a practical use case is solved using open data What will participants take away? Live example of machine learning and how to adopt python sci-kit library in a ML use case A solid understanding of data science and how it can solve problems in real life Deeper understanding of GitHub\u2019s API for data extraction and mining", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic programming knowledge in any object-oriented language would be helpful", + "Section": "Data science", + "Speaker Info": "Abhiram has been a part of the open source world in Bangalore for over 3 years now. As a student volunteer in Bangalore, he started contributing to Mozilla as well as FSMK (Free Software Movement Karnataka). After becoming a Mozilla Rep, he has presented over 40 sessions and workshops on python scripting, web dev, Rust and git version control at various venues all over India. Being an internet activist, he was an integral part of the #SaveTheInternet campaign in India during the fight against net neutrality violations. In 2016, he was invited to Mozilla\u2019s Leadership Summit in Singapore to present a talk on running a successful campus club for ~3 years. Currently, he is a Mozilla Tech Speaker well versed in topics like full stack web development, decentralization, scalable infrastructure set up, open source contribution practices and mentoring web enthusiasts . For the past 2 years, he is working at SAP Labs in Bangalore as a full stack web developer and continues to contribute to Mozilla India on a voluntary basis. Recently, he was invited to record a programming course on Rust by the educational website Lynda.com at Los Angeles, California. The course is titled First Look: Rust and it went live last week", + "Speaker Links": "Events and speaking engagements Mozillians profile - endorsements Mozilla Reps profile - activities and speaking engagements LinkedIn - professional career GitHub - code base & projects Slides.com Speakerdeck.com - presentations and decks Blogs and social media Personal blog Twitter - @abhi12ravi", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Akshay Arora (~akshayaurora)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-open-source-communities-on-blockchain-a-transparent-way-to-manage-organizations~aKkxa/", - "title": "Automating Open Source communities on Blockchain: A transparent way to manage Organizations" + "author": "Abhiram Ravikumar (~abhiram89)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/harnessing-open-data-to-build-user-profiles-using-python-sci-kit~ejNPe/", + "title": "Harnessing Open Data to build user profiles using python sci-kit" }, - "11": { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research \nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "We survey progress in recent years toward developing a theory of deep learning. Works have started addressing issues such as: (a) the effect of architecture choices on the optimization landscape, training speed, and expressiveness (b) quantifying the true \"capacity\" of the net, as a step towards understanding why nets with hugely more parameters than training examples nevertheless do not overfit (c) understanding inherent power and limitations of deep generative models, especially (various flavors of) generative adversarial nets (GANs) (d) understanding properties of simple RNN-style language models and some of their solutions (word embeddings and sentence embeddings", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", + { + "Content URLs": "Coming Soo", + "Description": "While majority of the time is spent in differentiating the programmer and designer, this talk aims to use python to mix the two to produce art. Don\u2019t understand read more: Disclaimer! \nYou won\u2019t be taught: What is art or programming. Writing Python syntax How to start loving python How to live life How to make money How to design You will learn about: How to use python to evolve as a designer Eventually, how to appreciate art and art in nature A different perspective towards art Ease your work as a designer and hence be more productive Make visually compelling art with python Generate complex art that would be exhausting to produce with GUI based softwares How to go beyond just making basic geometry shapes in your Computer Graphics class at University Typographic scripting i.e. Python scripting for font design Scripting with python to edit images Python to design layouts This talk is not just about the technology used. Hence, you might start loving python eventually or at least love for it might increase. Mine increased 10-folds, but you aren\u2019t expected for the same. Still, don\u2019t understand? Come to the talk", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Must know python\u2019s basic syntax Have desire to be creative but technical with code Interested in exploring the thin line between chaos and order", "Section": "Others", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban http://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban \nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", + "Speaker Info": "Tanya Jain has been designing and making art for about 10 years now, and plans to start a design studio of her own with the name of Magvaari. She has previously designed for various conferences including PyDelhiConf. She has publically spoken at tech communities like PyDelhi, LinuxChix India. Tanya is currently in 3rd year of her BTech degree at Amity University, Noida and is an active member at the ALiAS tech club. While out in public places, she has a constant thought on how can a place be evolved with design. And hence it also reflects her love for travel! She has a keen interest in learning computer related technologies. Other than designing, Tanya is interested in Data Science and Machine Learning. Yet whatever she learns, she somehow finds the way to join various topics and that is how this talk proposal emerged", + "Speaker Links": " LinkedIn , GitHub://Tanya-Jain Website: tanya-jain.xyz Blog: stellaradventurer.com", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Parthi", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/toward-theoretical-understanding-of-deep-learning~dJjgd/", - "title": "Toward Theoretical Understanding of Deep Learning" + "author": "Tanya Jain (~Tanya-Jain)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-scripting-for-graphic-designers~bkNNa/", + "title": "Python Scripting for Graphic Designers" }, - "12": { - "Content URLs": "http://www.calmdownkarm.com/2018/clustering (Blog Post)\nhttps://github.com/CalmDownKarm/360classificatio", - "Description": "Quick walkthrough of how word2vec combined with more traditional clustering mechanisms can be used for topic modelling and document classificatio", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Some familiarity with clustering (Kmeans) is helpful, but not required", + { + "Description": "Over the years, machine learning has been on the rise. It is so powerful that it almost tempt us to skip the Exploratory Data Analysis phase. It is not a very good idea to just feed data into a black box and wait for the results.\nExploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods.Pandas is a Python library that provides extensive means for data analysis.In conjunction with Matplotlib, Pandas provides a wide range of opportunities for visual analysis of tabular data", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic knowledge of python", "Section": "Data science", - "Speaker Info": "Recently graduated from BML Munjal University, Developer at Gramener", - "Speaker Links": "calmdownkarm.co", + "Speaker Info": "I am Purva Chaudhari ,3rd year student of computer science and engineering from Government Engineering College ,Aurangabad.I have a bit knowledge of Big-data technologies such as Hadoop,hive,spark etc.I have started python from last 2 months as I'm interested in Data Analytics and Data Science", + "Speaker Links": "https://www.linkedin.com/in/purva-chaudhari-044007165", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Purva_Chaudhari", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploratory-data-analysis-using-pandas-matplotlib~elNgb/", + "title": "Exploratory Data Analysis using pandas ,matplotlib" + }, + { + "Description": "In this hands-on course using Python, participants will learn how to use Python for various aspects of Data Engineering Participants will work on a real-life scenario of Ingesting data Cleaning & Transforming data Perform Exploratory Data Analysis (EDA) on the dataset As part of this exercise participants will be introduced to various useful Python libraries that every Data Engineer should know. The session will cover various other aspects of a robust, scalable data pipeline", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "This is an intermediate level hands-on course on Python. To benefit from this course the participants are expected to have Basic familiarity with Python programming Conceptual knowledge of data pipelines, relational data and big data Using Jupyter Python notebook environment", + "Section": "Data science", + "Speaker Info": "Arijit Saha Arijit Saha is a data professional with over sixteen years of industry work experience in architecting, designing & developing large-scale data products, platforms & solutions for both big & medium size enterprises. Currently he is busy architecting Enterprise AI data platform & products in one of the fastest growing startup Noodle.ai. He is an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Data Architecture, Big Data Analytics, Geospatial Analytics and application of Artificial Intelligence in Enterprises. Sumit Sen Sumit Sen is a software development professional with more than 15 years of development experience in areas of embedded systems, mobile and virtualization technologies. Currently he is working on the architecture of the AI as a Service offerings of Noodle.ai, an exciting startup in the Enterprise AI space. He is passionate about High Performance Computing, virtualization and IoT systems", + "Speaker Links": "Arijit Saha LinkedIn: https://www.linkedin.com/in/arijitsaha/ Twitter: @arijitsaha Sumit Sen LinkedIn: https://www.linkedin.com/in/sumitsenddn", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "arijit.saha", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-for-data-engineers~bmg9e/", + "title": "Python for Data Engineers" + }, + { + "Content URLs": "Body to body movement transfer using GANs: https://github.com/rahulbaburaj/body2bod", + "Description": "The workshop will be divided into two sessions spent learning about generative modelling. Both sessions will touch upon Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). We will be teaching about the different types of GANs and VAEs and their architectures in general. We will conduct a demo at the end of each session, where we will be generating images of new types of Pokemon. At the end of the sessions, we will be comparing the results from the images that each generative model's AI has produced. It will be interesting to witness the unfolding of new Pokemon, and learn the reasoning behind the output.", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Participants should have a basic understanding about how python works. Also, some basic knowledge on machine learning concepts will be useful", + "Section": "Others", + "Speaker Info": "Lovish, Rahul and Vishnu are all Research Fellows at the Center for Visual Information Technology at International Institute of Information Technology, Hyderabad", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Vishnu Sashank (~vishnu59)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gotta-gan-em-all-pokecon~enjWe/", + "title": "Gotta GAN 'em all! PokeCON!" + }, + { + "Content URLs": " Github Repo : https://github.com/raptor419/uavtalk Slides : http://blueraptortech.com/uavtalk", + "Description": "They might not be delivering our mail ( or Pizzas ) yet , but drones are now intelligent, simple, and reliable enough that they cannot be considered as just toys but as formidable business tools. This talk will briefly go into the inner workings of UAV systems and will demonstrate how python tools can be used to make fully autonomous drones for various purposes. The contents of this talk include: Flight Controllers and control theory ( Ardupilot ) MAVLink ( pymavlink , mavproxy ) Real-time computer vision ( OpenCV , Tensorflow ) DroneKit-Python Obstacles and Implications of IoD We will go extensively into the abilities of DroneKit-Python and into the future of the Internet of Drones using real-life examples such as pest control ( ScAIRcrow ), \ncommercial mapping ( Drone Deploy ) and delivery ( Flirtey ) etc. The talk will end with a small drone taking a picture of all of us, autonomously ofcourse, demonstrating the discussed topics and the formidable ability of autonomous drones", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Python Programming, the concept of APIs and libraries Computer Vision basics The IoT concept An eager mind", + "Section": "Embedded python", + "Speaker Info": "Harsh has been tinkering with technology since he was 9, he received the presidential gold award for National Child Award for Exceptional Achievement by Shree Pranav Mukherjee in 2012. A CS undergrad at IIIT Delhi, he is also the Director of the establishment BlueRaptorTech , which is venturing into the field of big data based algorithmic day trading. A CV Specialist for Aurora , the aerial robotics team of IIIT Delhi, and an AI/ML HackerSpace Intern for Flytbase , a US-based Internet of Drones specialized platform, he has worked extensively and is passionate about drones and has attended many AUV events. His expertise in UAVs lies in making intelligent solutions by the intersection of Computer Vision and Precision Robotics", + "Speaker Links": " LinkedIn GitHub Facebook Website BlueRaptorTech", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Karmanya Aggarwal (~CalmDownKarm)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/document-clustering-with-word2vec-and-hierarchial-clusters~dG7Jd/", - "title": "Document Clustering with Word2vec and Hierarchial Clusters" + "author": "Harsh Bandhey (~harsh31)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/making-uavs-autonomous-and-the-internet-of-drones~bokBb/", + "title": "Making UAVs autonomous and the Internet of Drones" }, - "13": { - "Content URLs": "TB", - "Description": "\"Data is the new Oil!\" But, what is the benefit of this oil if you cannot refine (analyse) and sell/use (derive value) it. Big Data has pushed the frontier of analytical processing to gather more actionable insights in the past decade from having separate analytical servers to performing analytics close to the Data Lake/Cloud. A new paradigm of FOG computing has recently emerged which enables analyzing data at the Edge (close to the data capture device). This talk will focus on Edge Analytics enabled by Python & Raspberry Pi. Why attend this session? This session will provide a first hand look into the paradigm of FOG computing and Edge analytics. Model deployment is a critical part of the analytics life-cycle and this talk will provide insights and best practices to ensure seamless and robust model deployment. Also, the audience will get a flavor of python in embedded devices through the live and interactive demonstration using Raspberry Pi. Content The talk will cover the following sections: Evolution of analytics (Dedicated Machines -> Cloud -> Edge) The need of Edge analytics Analytics Life-cycle (ALC): Introduction, Importance of Model Deployment, Adapting ALC for Edge Analytics Model Exchange Formats (PFA, ONNX) for Deployment: Introduction & Need for Democratizing model development process Edge Device Introduction - Raspberry Pi Introduction to Portable Format for Analytics (PFA) Model Deployment on Edge Device (Raspberry Pi) using open source PFA engine implemented in Python Hands-on Application Use Cases - Deployment of Clustering, Regression, Decision Tree, Neural Network/ Deep Learning Models", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Python 2.7.x titus python package (pip install titus)", - "Section": "Embedded python", - "Speaker Info": "A die hard Pythonista, Ankit is a full time open source contributor and a former Google Summer of Code 2013 scholar under Python Software Foundation. Currently, he is developing the open source Portable Format for Analytics (PFA) implementation - Titus on Python 3. Ankit has 4 years of industrial experience in machine learning, quantitative modelling, data analytics and visualization. Over the years, he has developed an expertise in handling the entire data analytics pipeline comprising \u2013 ingestion, exploration, transformation, modeling and deployment. He is a polyglot programmer with an extensive knowledge of algorithms, statistics and parallel programming. He has shipped multiple releases of DB Lytix, a comprehensive library of over 800 mathematical and statistical functions used widely in data mining, machine learning and analytics applications, including \u201cbig data analytics\u201d. An IIT Kanpur alumnus, Ankit is also an active researcher with publications in international journal and conferences. He is actively working in the domain of IoT Analytics and has recently presented his work: \"Discovering Knowledge from Smart Meter Data using Competitive Learning Methods\" in the Data Science Congress 2018. \u201cIn-database Analytics in the Age of Smart Meters\u201d in the 5th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, 2017. \u201cSmart Meter Data Analytics using Orange\u201d in Scipy India 2017, Mumbai. Ankit is an active contributor to the Indian Python Community and has conducted the following workshops in PyCon India and Scipy India: Scientific Computing using Orange in SciPy India 2017, Mumbai. Making Machine Learning Fruitful and Fun using Orange in PyCon India 2017, New Delhi.", - "Speaker Links": "LinkedIn Youtube channel Githu", - "Target Audience": "Beginner", + { + "Description": "DNS is a non-encrypted protocol. DNS responses which are sent over UDP or TCP lack confidentiality, privacy and security. DNS often contains password files, geolocations, email service and fax numbers, certificate identity and pinning for TLS and much more. Parsing DNS without encryption would lead to different vulnerabilities such as eavesdropping and spoofing. DNS over HTTPS(DoH) is a web protocol that argues for sending DNS requests and receiving DNS responses via HTTPS connections, hence providing query confidentiality. DoH provides more than just privacy \u2013 it also helps guarantee the integrity of the response users receives their requests. Because the DNS response is invisible between responder and user, ISPs and others in the end-to-end network chain can't interfere with the responses. Moreover, Responses from the use of recursive resolvers to clients are the most vulnerable to undesired or malicious changes, because generally recursive resolvers do not encrypt any of your queries. Henceforth, we would be discussing the implementation and parsing of DNS over HTTPS. Further, we provided added support for handling IPv4 and IPv6 DNS packets (A + AAAA records) as well as support for EDNS for edns-client-subnet usage. The integration with HTTP provides a transport suitable for traditional DNS clients seeking access to the DNS. In the end, we will discuss how our client will be sending DNS queries and get DNS responses over HTTP using https:// and implies TLS security integrity and confidentiality. Furthermore, I plan to put some light on how DNSSEC validation is getting involved here with DNS resolution through HTTP to provide ultimate privacy and security support for \n the DNS packets", + "Last Updated": "06 May, 2018", + "Section": "Networking and Security", + "Speaker Info": "I\u2019m currently in my sophomore year, pursuing an undergraduate degree in Computer Science and Engineering from Amrita University. I\u2019m an active member of a FOSS club in our university(FOSS@Amrita). I started actively contributing to various open source organizations from the year 2016. Initially, I started my career in Open Source by contributing to KDE. I was selected for Season of KDE(KDE-SoK) 2016-17 in which I worked on an astronomy software named called Kstars. Further, I was selected for Google Summer of Code 2017 under KDE, where I worked on a project for a libre graphics software, Krita. My work involved introducing a data sharing module in it. The module enables communication between Krita and a remote KDE server in order to help users save and publish their data online. This also required modifying the underlying framework to enable client/server communication. I have been selected for Google Summer of Code for the 2nd time, where I am working on the project Wget2 under GNU organisation. I GSoC project involves adding support for DNS over HTTPS in Wget2. I was invited as a speaker for KDE India Conference 2017 in IIT Guwahati, where I gave a talk on the topic \u201cObject tracking using OpenCV and Qt\u201d. Further, I will be travelling to Austria on August to give a talk in KDE conference, Akademy and will be talking on the topic \"Strengthen Code Review Culture: rm -rf \u2018Toxic Behaviors", + "Speaker Links": "http://anikethfoss.wordpress.com http://gitlab.com/aniketh01/ https://conf.kde.org/en/Akademy2018/public/speakers/1", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Ankit Mahato (~ankit60)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fog-analytics-using-raspberry-pi-and-python~eE7gb/", - "title": "Fog Analytics using Raspberry Pi and Python" + "author": "Aniketh Girish (~Aniketh01)", + "created_on": "06 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/privacy-concerns-how-dns-resolves-over-https~avLnd/", + "title": "Privacy concerns: How DNS resolves over HTTPS" }, - "14": { - "Content URLs": "Open weather map https://openweathermap.org/ Twitter API https://developer.twitter.com/en/docs.htm", - "Description": "This talk focuses on demonstrating the power of Python's Statistical and Data Science Libraries. I have been working on a project to classify average human sentiments as positive or negative. Classification is completely based on the prediction made by the ML models, which incorporates the weather of the location. I will try to prove that weather is \"one of the factor\" contributing to the moods/emotions of humans and ultimately affects the decision making ability. I have achieved the accuracy of 60%, which is good enough, with the existing and publically available data. The accuracy will certainly grow along with the data", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basic knowledge of Python Basic understanding of Statistics", - "Section": "Data science", - "Speaker Info": "I am a Python enthusiast, always a keen explorer of the power of python. I have been passionate about Python since my early college days, and then I went on developing many Web Apps, APIs based on Django and Flask, later on, my journey with Python turned towards exploring the magic of Data Science. It has been quite an interesting time spent exploring this field, and I must say that the depth cannot be determined. The more you experience, the more moments of awe occur", - "Speaker Links": " https://omkar-dsd.github.io/ https://towardsdatascience.com/a-simple-word-sense-disambiguation-application-3ca645c56357 https://medium.com/@omkar_dsd/when-killing-humans-becomes-the-right-choice-e3964419e78c https://stackoverflow.com/users/5130528/omkar-deshpande https://www.github.com/omkar-dsd", + { + "Content URLs": " Slides for the talk - DotPython Demo Dotfiles Repository - DotvFiles", + "Description": "Almost all developers spend countless hours on configuring, tweaking and micro-managing their dotfiles with an obsession to exactly have them like one wants them to be. I do too . Dotfiles are just configuration files like .vimrc and .gitconfig on your OS, that stores the settings you have for applications/environments/tools to make life easier while giving you more portability. Well, do you have to use bash scripts for initial setups of your dotfiles? or do you want to setup your dotfiles but don't want to learn or be limited by Bash? Do you forget to update/maintain your dotfiles periodically? Do you struggle with the installation of applications later on? \n Well, Python could be the answer to all of your problems. With Python, one can easily manage , maintain and do a lot more with their dotfiles. My talk would start with a basic intro of what exactly are Dotfiles? and what is the common way of setting them up? This helps beginners who are new to the topic, get interested and a quick recap of why dotfiles are important for all developers. Building up the momentum by visual queues and comparisons through slides, I would show how exactly Python does the same using Homely as Bash does. Later, work through the more intricate details by talking about the features one can implement using Homely and Python highlighting limitations of bash. Like Automation , Logging , git control , debugging , installation of applications and so much more . Summing up by demonstrating a number of scripts that I will be preparing in-advance to showcase the same features that we just talked about. This helps people grasp the talk, the topic, and \" the why we are doing, what we are doing \" part. Ending the talk , with a round of questions and showing the setup I use after months of searching through dotfiles repositories to leave them open to all the options they can choose from for setting up their dotfiles and pick the best setup from the knowledge they just gained. Sub Category : Developer Tool", + "Last Updated": "07 May, 2018", + "Prerequisites": "A laptop computer running any flavor of Linux. It would help if python 3 is already installed. Coming without a laptop is also fine. The presentation would be enough to understand", + "Section": "Others", + "Speaker Info": "I am a student, a Linux enthusiast, loves to code in Python, currently, part of Google Summer of Code 2018 under Sugar Labs, mentoring the GirlScript Summer of Code project, WTF Python and an active volunteer for PyDelhi since 2016 and managing an open-source community in my college, ALiAS . I friviously collect C&H comic strips because I believe everyone should have a hobby and that is mine. I have spoken before at Local User Meetup groups and this would be my first time speaking for PyCon India. When I am free, I devote my time towards closing issues on GitHub and scooping through my Twitter feed. I like to share my thoughts and meet new people. Hence, been writing for a year now, for many organizations such as OpenEBS and TheGeekyWay. Also, I have my own blog, Mixster ", + "Speaker Links": "Professional Profile available @ LinkedIn , Contribute to FOSS projects @ GitHub , Blog @ Mixster I go by vipulgupta2048 all over the web. Feel free to connect/talk with me", "Target Audience": "Beginner", "Type": "Talks", - "author": "Omkar Deshpande (~omkar08)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/analyzing-the-impact-of-weather-on-human-sentiments~bD7Ka/", - "title": "Analyzing the impact of weather on human sentiments" + "author": "Vipul Gupta (~vipulgupta2048)", + "created_on": "07 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/keeping-your-dotfiles-in-check-with-python~dw7Xd/", + "title": "Keeping your Dotfiles in check with Python" }, - "15": { - "Content URLs": "TB", - "Description": "This tutorial is meant to familiarize participants with Tensorflow, generally as a tensor library and particularly as a tool for doing day-to-day machine learning tasks. The ultimate goal of the tutorial is to be able to make participants comfortable enough with it so that they can use tensorflow as a scalable substitute for other ML libraries like sklearn. Why Learn Tensorflow? For the same reason that you should learn NumPy. Tensorflow is to Keras (and many other deep learning libraries) what NumPy is to sklearn (and many other machine learning libraries). It is the underlying data model of many deep learning applications. There are always nooks and crannies in any deep learning application that high level wrapper libraries cannot reach. The tutorial is aimed at making these accessible and debuggable with tensorflow. What will I learn? The focus of the tutorial would be on loss functions - ensuring their fundamental correctness with respect to the machine learning problem at hand, ensuring their differentiability and convergence are critical to solving a deep learning problem. There are many ready-made loss functions in tensorflow, and using these as building blocks, we will see how to make arbitrarily complex loss functions. FAQs: Q. Will I need a GPU? A. No. The beauty of tensorflow is that it can seamlessly deploy code to GPUs, without you needing a GPU to develop that code. Q. What is the format of the tutorial? A. Being a tutorial, this session is meant to be highly interactive in nature. It will be a sequence of units where concepts are first explained and then the audience will have to solve exercises in a Jupyter notebook. Q. I don't know anything about neural networks or deep learning. Should I attend this tutorial? A. Absolutely. The focus is on tensors, which are the domain of tensorflow, and not on network layers, which are domain of keras", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic knowledge of Python data structures and NumPy arrays Basic knowledge of linear algebra Elementary vector calculus", + { + "Content URLs": "https://docs.google.com/presentation/d/1DE-_l9N8Scu-M8d_bFxuKQak3TYipEDsGX5HIsB59s0/edit?usp=sharing PS: First Draft, need to organize it better and improve the demos", + "Description": "Dask is a general purpose parallel computing system capable of Celery-like task scheduling, Spark-like big data computing, and Numpy/Pandas/Scikit-learn level complex algorithms, written in Pure Python. Dask has been adopted by the PyData community as a Big Data solution. This talk focuses on the distributed task scheduler that powers Dask when running on a cluster. We will start by comparing Dask with the other solutions that are available for big data ETL and analytics . We will talk about how easily you can parallelize the work loads that you do with your favourite scipy libraries for eg Numpy, Pandas etc. Lastly we will also talk about how you can integrate Dask with your existing code and parallelize it's work load", + "Last Updated": "07 May, 2018", + "Prerequisites": " Good understanding of Python Programming Must have used any scipy library before Nice to have some idea regarding the big data tools available for analytics and ETL", "Section": "Data science", - "Speaker Info": "Jaidev is a data scientist based in New Delhi, India. He specializes in building data-driven products and the tooling around them for a living. His research interests are in signal processing and computational harmonic analysis. He is obsessed with applications of machine learning in personal productivity and recommendation systems. He blogs about these here ", - "Speaker Links": "Twitter GitHub Blo", + "Speaker Info": "I am an enthusiastic developer and aspiring entrepreneur who holds a particular passion for the intersection of web development and emerging technologies. I am constantly exploring innovative ways to solve real world problems and improve existing solutions. I genuinely enjoy working with people, taking risks, and developing new applications. I am currently working at Dubizzle as a Associate Software Engineer. Previously I worked at Corridor Funds as a Technology Architect where I built and Architected a data driven Loan valuation and Portfolio Management tool for retail and institutional lenders. I am open source contributor at Gluster, FOSS Asia, NGUI and GDG. Previously I lead a GDG Chapter in Gujarat. I have also spoken at tech meet ups and conferences like Women techmakers, Google Devfest, Google Cloud Next Extended, Mozilla Gujarat, Local GDGs and Startup Gujarat. In addition to that, I am always experimenting with new and interesting side projects", + "Speaker Links": " Github: http://github.com/smitthakkar96 Linkedin: http://linkedin.com/in/smitthakkar96", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Jaidev Deshpande (~jaidev)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tensorflow-101~dB7Ye/", - "title": "Tensorflow 101" - }, - "16": { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research\nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "The Python ecosystem is growing and may become the dominant platform for machine learning. The primary rationale for adopting Python for machine learning is because it is a general purpose programming language that we can use both for R&D and in production. In this talk I will discuss 1. Python and its rising use for machine learning, 2. SciPy and the functionality it provides with NumPy, Matplotlib and Pandas.\n3. scikit-learn for machine learning algorithms, TensorFlow and Keras for Deep learning and PyTorch for Natural Language Processing, 4. How to setup your Python ecosystem for machine learning and what versions to use. At the end I will also give case studies on using this Python ecosystem for biomedical applications", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", - "Section": "Data science", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban\nhttp://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban\nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Parthi", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mastering-machine-learning-with-python~azNya/", - "title": "Mastering Machine Learning with Python" - }, - "17": { - "Content URLs": "Will be updated soo", - "Description": "The ELK stack consists of Elasticsearch, Logstash, and Kibana. Although they've all been built to work exceptionally well together, each one is a separate project that is driven by the open-source vendor Elastic\u2014which itself began as an enterprise search platform vendor. It has now become a full-service analytics software company, mainly because of the success of the ELK stack. The session will cover basics of ELK stack for a kickstart", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Passion to Lear", - "Section": "Others", - "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International University", - "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", - "Target Audience": "Beginner", "Type": "Talks", - "author": "Chhavnish Mittal (~chhavnish)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-wih-elk-stack~axNBd/", - "title": "Getting Started wih ELK Stack" + "author": "smit thakkar (~smitthakkar96)", + "created_on": "07 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/dask-distributed-data-science-in-a-pythonic-way~axLPa/", + "title": "Dask: Distributed Data Science in a pythonic way" }, - "18": { - "Content URLs": "will update soo", - "Description": "Get to Know Tkinter , pyqt5 and pyqtgraph and how to create a data visualization and control interface for your geeky arduino project in no time. Tkinter is a is the standard Python interface to the Tk GUI toolkit pyqt5 is Python bindings for the Qt cross platform UI and application toolkit pyqtgraph is Scientific Graphics and GUI Library for Python I will show you how to send the commands to Arduino using Python GUI and how parse and create a real-time graphs from Arduino dat", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "You should know how to write mighty Hello World program in Python and Arduin", - "Section": "Embedded python", - "Speaker Info": "I'm just a Tinkerer. Been playing with Python , Arduino and Raspberry Pi from few year", - "Speaker Links": "Blog - My Tinkering with Arduino GitHub linkden simple dem", + { + "Content URLs": "https://github.com/rahulbajaj0509/Automation-with-Ansibl", + "Description": "Ansible is software that automates software provisioning, configuration management, and application deployment. Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications\u2014 automate in a language that approaches plain English, using SSH, with no agents to install on remote systems. This workshop introduces a beginner to basic fundamentals of Ansible with easy to do hands-on exercises. The workshop introduces basic use cases of Ansible followed by an introduction to Ansible Inventory, Playbooks, Modules, Variables, Conditionals, Loops and Roles. Each mentioned topic is accompanied by a set of coding exercises giving the attendees a hands-on experience in developing Ansible Playbooks. Introduction to configuration management [15 mins] What is configuration management?\nAgent vs Agent-less\nPush and Pull configurations.\nImperative vs Declarative DevOps Concepts [10 mins] Infrastructure as code.\nDeterministic Builds/Deployments.\nIdempotency.\nCommunications channels \u2013 Message Queueing vs SSH Introduction to Ansible [30 mins] Requirements\nInstallation\nConfiguration Working with Ansible [100 mins] Ansible Inventory\nPlaybooks\nModules\nVariables\nConditionals\nLoops\nRoles\nAnsible Galaxy Ansible in DevOps environment [20 mins]\nQuestions and Answers [10 mins", + "Last Updated": "07 May, 2018", + "Prerequisites": "Pre-Requisites Basic Linux Administrator Skills\nOpen mind and spirit to learn. Software Requirements We will be using two centos7 vagrant machines for the workshop. Make sure you are using a Linux distribution and have vagrant configured with any of the providers like libvirt, virtual box, etc.\nIf you are unable to install vagrant on your Linux systems, then you might want to install Fedora operating system and come for the workshop, we can do the rest together", + "Section": "Developer tools and Automation", + "Speaker Info": "Rahul is an Associate Software Engineer, Red Hat. He is a part of the official foreman organization(https://github.com/rahulbajaj0509). He contributes mostly to the Foreman project and is a \u2018Red Hat Certified Specialist in Configuration Management\u2019. He is also the organizer of Foreman Pune Meetups", + "Speaker Links": "Blog: https://rahulbajaj05.wordpress.com/\nGithub: https://github.com/rahulbajaj050", "Target Audience": "Beginner", "Type": "Workshops", - "author": "Kunchala Anil (~anilkunchalaece)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-python-gui-for-arduino-project~dw88e/", - "title": "Building Python GUI for Arduino Project" + "author": "Rahul Bajaj (~rahul56)", + "created_on": "07 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automation-with-ansible-beginner-to-advanced~azY2e/", + "title": "Automation with Ansible: beginner to advanced" }, - "19": { - "Content URLs": "TB", - "Description": "The focus is more on teaching core concepts to programmers rather than using libraries. More than one neural network will be implemented. An Easy way to learn Machine Learning An interactive way to learn ML. With ML being a leading platform in the market, the workshop introduces to one of the most important fields of Machine Learning that is Deep Neural Networks. Only basic introduction to Mathematics required. Why Python? Python for Machine Learning Machine Learning What is Machine Learning? Why learn Machine Learning? Types of Machine Learning Regression and Classification Supervised and Unsupervised Neural Networks Deep Neural Networks Feed forward Neural Networks Convolutional Neural Networks CNN Recurrent Neural Networks Layers in Neural Networks Neuron Models Perceptron Sigmoid Neuron Binary Threshold Rectifier Stochastic Binary Cost Functions (A Loss or Objective function) Gradient Descent Gradient Boosting Backpropagation Stochastic Gradient Descent Implementing the classic MNIST dataset problem A Neural Network for handwritten digit recognition Classification using individual pixels Image Classification A simple implementation using deeper networks TensorFlow Expanding the Neural Network using Google's Library for Machine Learning Might change to Caffe - nVIDIA's library for Machine Learning Deep Learning A brief introduction to Deep Learning practices Auto Encoders Other areas of Deep Learning (A qualitative study) ", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "User Prerequisites Core Python - lists, dict, string including functions and classes NumPy, SciPy - not necessary but preferred Elementary Calculus - Differentiation and Integration (Understanding qualitatively is enough) Linear Algebra System Requirements 32/64-bit Windows/Linux architecture with at least 2GB RAM Python3 compiler with NumPy, SciPy and TensorFlow library PDF reader Other Requirements but not necessarily needed Anaconda3 (or support for ipynb files, Jupyter preferred) A graphic card", - "Section": "Core python and Standard library", - "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", - "Speaker Links": "GitHub Instagram Emai", - "Target Audience": "Intermediate", + { + "Description": "React has been out there for quite some time now and its arguably one of the hottest front end frameworks out there. But MERN architecture hasn't caught up. And that's what I want to teach/discuss in my talk at pycon. How MERN could be the hottest kid on the block in the upcoming days", + "Last Updated": "08 May, 2018", + "Prerequisites": "Javascript\nBeginner level React.\nLittle to no knowledge of Node, Express and Mongo", + "Section": "Web development", + "Speaker Info": "https://himanshuc3.github.io/\nSolving problems bit by bit. After all, computer is just bits. Cracking PJs and living life to not make the most of it but make the most of me", + "Speaker Links": "https://github.com/himanshuc3\nhttps://medium.com/@himan\nhttps://drive.google.com/file/d/1wzhC56jvrriO6XOogapWE2aOMN8Afsiz/view?usp=sharin", + "Target Audience": "Beginner", "Type": "Workshops", - "author": "Aniket Chowdhury (~aniket43)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-advent-of-deep-neural-networks-neural-network-implementation-without-ml-libraries-and-extending-them-with-tensorflow~av75b/", - "title": "The Advent of Deep Neural Networks. Neural Network implementation without ML libraries and extending them with Tensorflow." + "author": "Himanshu Chhabra (~himanshu87)", + "created_on": "08 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mern-could-be-the-buzz-word~bDEkd/", + "title": "MERN could be the buzz word" }, - "20": { - "Content URLs": "Session Content: Introduction to main units of Deep learning Feature engineering techniques for audio data DeepSpeech Architecture Live demo of DeepSpeech Project Common Voice initiative (why and its need) Community Support details Applications of speech recognition Key Takeaways: Unravel the mystery behind the AI which powers speech recognition for services such as Siri, Google Assistance etc Learn about various by which one can contribute to Project DeepSpeech & Common voice project Get introduced to major units of deep learning and state of art DL architectures powering speech to text applications Tags: AI, speech recognition, speech to text, machine learning, Python, tensorflow, deep learning, Voice search Projects links: DeepSpeech : https://github.com/mozilla/DeepSpeech https://arxiv.org/abs/1412.5567 Common voice: https://voice.mozilla.org/ https://voice.mozilla.org/en/data", - "Description": "Pitch: Our voices are no longer a mystery to speech recognition (SR) software, the technology powering these services has amazed the humanity with its ability to understand us. This talk aims to cover the intrinsic details of advanced state of art SR algorithms with live demos of Project DeepSpeech. A research says that \"50% of all searches will be voice searches by 2020\". World\u2019s technology giants have placed big bets with their investments in services providing voice search, personal digital assistant, IoT devices etc. Solving the problem of speech recognition is a herculean task, given the complexity involved with data like the human voice. The talk will cover a brief history of speech recognition algorithms, the challenges associated with building these systems and then explain how one can build advanced speech recognition system using the power of deep learning and for illustration, we will deep dive into Project DeepSpeech. Project DeepSpeech is an open source Speech-To-Text engine developed by Mozilla Research based on Baidu's Deep Speech research paper and implemented using Google's TensorFlow library. Speech recognition is not all about the technology, there's a lot more concerns, challenges around how these AI models are being part of our day to day life , it's biases etc. The bigger question revolves around centralization of these AI services, projects like Common Voice addresses these problems by enabling all to be part of this revolution, a part of the talk will focus on how people need to approach these type of research keeping in mind the community and humanitarian benefits as first priority", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic Python Feel enthusiastic about ML & AI services Interest to learn about speech recognition systems", - "Section": "Data science", - "Speaker Info": "Vigneshwer is an innovative machine learning researcher with an artistic perception of technology and business, having several years of experience in developing robust machine learning solutions for video and text analytical problem statements and have played key roles in analyzing problems, creating hypothesis matrix and delivering novel algorithms and data-driven solutions for many fortune 500 companies. An open Source aficionado, Official Mozilla TechSpeaker and the author of Rust cookbook", - "Speaker Links": "Github | Website | Facebook | Twitter | LinkedIn | Talk", + { + "Content URLs": "Github and presentation will be uploaded shortly", + "Description": "Functional programming is an essential part of any programming language. It allows you to harness the language, performing tasks which can replace tens of lines with just one. This is one programming paradigm which enables the programmer to give more importance to functions than classes. Instead of the traditional approach, we shall solve problems by using functions. A ramp up with Collections and a little bit of Object Oriented concepts in python, Functional Programming can be a great curve to harness python's usability and simplicity. At the end of this session, participants will be able to use the collections library in python, list comprehensions , deal with classes , objects and write anonymous functions , lambda expressions and resolve traditional snippets to reduce , map and filters for each of the use case", + "Last Updated": "09 May, 2018", + "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college folks", + "Section": "Core python and Standard library", + "Speaker Info": "Currently working as a Software Development Engineer at Olacabs. http://sameera.me https://www.linkedin.com/in/sameera-sy During my freetime I try the below. https://stackoverflow.com/users/4303216/sameera-sy https://www.hackerrank.com/sameerasy https://leetcode.com/sameerasy https://doselect.com/@sameera.sy", + "Speaker Links": "Below are some of my sample works. https://github.com/sam95 I have also conducted a webinar on JS for JavaScript Meetup Bangalore group. https://github.com/sam95/js-for-newbies-3 https://www.youtube.com/watch?v=JXg1GT6zDGQ", "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vigneshwer Dhinakaran (~dvigneshwer)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-speech-recognition-with-project-deepspeech~erNpe/", - "title": "Demystifying speech recognition with Project DeepSpeech" + "Type": "Workshops", + "author": "sameeras", + "created_on": "09 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/functional-programming-with-python~eEQle/", + "title": "Functional Programming with Python" }, - "21": { - "Content URLs": "https://github.com/vibrantabhi19/PyConIndia2018 (A Github Link to the slides and the Jupyter Notebooks) https://docs.google.com/presentation/d/1UmT3PbazC6sO_owIeiLNj5G1EdTwrdpS84JWenO-3eE/edit?usp=sharing (Introduction Slide for CNN and PyTorch) Some more slides and notebooks as and when we come up with more ideas to make the workshop interacting and interesting", - "Description": "Just like in our everyday lives, AI and robotics are increasingly a part of our healthcare ecosystem. Currently healthcare is broken; there\u2019s shortage of doctors; poor quality of care. There is a dire need to provide assistance to the whole medical industry to improve healthcare. PyTorch, which is a very popular modular deep learning framework for fast, flexible experimentation is an invaluable resource for such problems. It supports seamless conversion of Numpy arrays into GPU tensors and vice versa. The dynamic computational graph allows to change the network behavior on the fly unlike static graphs and due to Its highly modular nature helps in fast debugging. Unlike other production grade tools, Pytorch helps with lots of Research and Experimentation with novel architectures and is very useful to test ideas a bit more quickly and prototyping. With Medical Imaging being the field most impacted by AI, our goal in this workshop is to give a good head start covering the heuristics of Medical Imaging, the concepts involved in it and how to code your way out. This workshop would be divided into two halfs. First Half: Pytorch Introduction\nDuration: 1 hour 20 minutes\nThe first half would be a gentle introduction to PyTorch framework. We will introduce the audience with the basics of PyTorch. This workshop will cover topics like: What is PyTorch? (Use cases and war stories) Tensor 101 Ndarray/Tensor library Numpy Bridge, Fast CPU to GPU conversion of tensors The automatic differentiation engine or autograd Difference between Static and Dynamic computational graphs Advantages of dynamic computational graph with examples The optimization package Scope of debugging Ecosystem Linear Code flow in Pytorch (One of the core philosophy of PyTorch) Saving and loading models* Deep Learning workflows* Tutorial on Transfer Learning.* Workflows which involve writing custom data-loaders will also be introduced in brief.* A 10 minute coffee/kit-kat break. :-) Second Half: Let\u2019s dive in. Duration: 1 hour 15 minutes. Introduction to Radiology: What is radiology? What do the images look like? How is AI used here? How will AI help improve radiology practice? Liver, Tumor and Vessel Segmentation - setting the context of why it is needed. Challenges faced in solving liver segmentation. How we solved the challenges - edge maps, data imbalance and overall architecture and data used. Hands on with live Liver Segmentation using PyTorch. Challenges faced in vessel segmentation and classification. How we solved the challenges - vesselness filters, overall architecture and data used. Hands on with live Vessel Segmentation using PyTorch. Putting it all together A 15 minutes Q & A session", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Zeal to learn new things would be enough but basic knowledge of Python would be good to go but the following are always encouraged: Basic Knowledge of algebra. Python Libraries such as Numpy. Basic knowledge of working with Neural Network (not a strict requirement as we will be covering most of it). We also encourage the participants to have a look into the following linked talks/videos/literature to get a head start into the topic. The related materials from web for ideas: https://github.com/soumith/talks/blob/master/2017-NIPS/Coding-papers-in-pytorch.pdf https://github.com/soumith/talks/blob/master/2017-GATech-Atlanta/PyTorch-frameworks_overview_deepdive.pdf https://www.youtube.com/watch?v=LEkyvEZoDZg https://www.youtube.com/watch?v=VMcRWYEKmhw https://www.youtube.com/watch?v=Rv9naeLXolY&index=3&list=PLrzfRWNHZPa0gKBEXTJ0gbDu8NsR07KEH https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/01-basics/pytorch_basics/main.p", + { + "Content URLs": "The work in progress repository of all the associated code - fromscratchtoml . The official website of fromscratchtoml . The work in progress python notebooks . The author's github profile . Sample slides will be uploaded here ", + "Description": "The aim of this workshop is to give a hands on coding experience for writing machine learning / deep learning algorithms from scratch without using external frameworks alongside visualising the model and explaining its predictions using LIME. from-scratch-to-ml The primary goals of this library is - - This framework is intended to be and educational tool to learn deep Learning . - To bridge the gap between the theoretical and coding aspects of machine learning algorithms. - To write intuitive blogs as python notebooks so as to juxtapose theory and code . Explaining the fundamentals of the algorithm from the very basics. - To minimise the use of external dependencies except the fundamental ones like numpy and matplotlib .\n - To make sure that the developed algorithms are coherent with already existing machine learning frameworks. The library is still in a nascent stage but will take shape in a couple of months. Given that the commit frequency is huge. The audience is requested to be patient. LIME (Local Interpretable Model-Agnostic Explanations) - When you are writing a machine algorithm from scratch you want to make sure that your results are coherent and your model is learning the features it is meant to learn. LIME explains why your model behaved the way it did. I will quote excerpts from their blog below - Imagine we want to explain a classifier that predicts how likely it is for the image to contain a tree frog. We take the image on the left and divide it into interpretable components (contiguous superpixels). As illustrated below, we then generate a data set of perturbed instances by turning some of the interpretable components \u201coff\u201d (in this case, making them gray). For each perturbed instance, we get the probability that a tree frog is in the image according to the model. We then learn a simple (linear) model on this data set, which is locally weighted\u2014that is, we care more about making mistakes in perturbed instances that are more similar to the original image. In the end, we present the superpixels with highest positive weights as an explanation, graying out everything else. Even from a human's perspective these explanations do make sense. SOURC", + "Last Updated": "11 May, 2018", + "Prerequisites": "Just a bit of curious dabbling around with some basic machine learning", "Section": "Data science", - "Speaker Info": "Abhishek Kumar: Deep Learning Engineer, Predible Health, Bangalore. I am presently working as Deep Learning Scientist at Predible Health, here, we have build state of the art segmentation network for liver, tumour and vessel segmentations. I have previously taken workshop at IIT-Bombay Techfest, I have spoken at Shri Mata Vaishno Devi University at their SFD celebrations and at MuPy (Manipal Institute of Technology's annual Python Conference), Kongu University and a few other colleges/Universities. I have been a constant contributor in the open source world and have been attending PyCon and other conferences every year. An athlete, a Real Madrid F.C follower and a part time stand-up comedian (good enough to make you laugh). Aditya Bagari: Final year Undergrad, Indian Institute of Technology, Madras I am a final year Undergraduate student at IIT-Madras doing my Dual-Degree in Engineering Design with specialisation in Bio Medical Sciences. I have been working on Medical Imaging and PyTorch for almost a year and I have been a constant admirer of Open Source Technologies and frameworks. Feel free to drop any suggestions or modifications that you want in this workshop. See you at PyCon", - "Speaker Links": "Abhishek Kumar: Website (A very outdated one), LinkedIn , Medium , Github . Aditya Bagari: LinkedI", + "Speaker Info": "I have graduated from IIT ISM Dhanbad in 2017. Formerly I worked for a London based startup - ALIS labs , currently I am a research fellow at CVIT Lab IIIT Hyderabad alongside being the author of fromscratchtoml . I am also RaRe's incubator program member - the same organization which looks after the reputed topic modelling library gensim . I have given prep talks and mentored dev sprint on the same in Hyderabad Python Meetup group twice", + "Speaker Links": "Author's open source contribution can be seen at his github profile where it all started. Author's current blog where he discussed a 'bit' about the impact of AI. Author's old blog archive where he talked about random developer stuff. Author's another delusional repository which he has trouble explaining to people. Author sometimes also blogs for RaRe technologies . Author is omnipresent on the web by the handle markroxor ", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Mohit Rathore (~markroxor)", + "created_on": "11 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/from-scratch-to-ml-the-machine-learning-library-you-really-understand-and-explaining-its-predictions-with-lime~dJXya/", + "title": "From scratch to ML - The machine learning library you really understand and explaining its predictions with LIME." + }, + { + "Description": "So you started learning python, and you have been able to stitch few lines of code together and it worked, but you do not know why, then this is the talk for you. We will delve into elementary yet obscure concepts that are more often than not skipped by beginners eg why is if _ name_ == _ main_ required in python scripts. et el. In a 3 hour power packed interactive and fully-hands on workshop we shall be learning python from ground up using examples from the real world. Basics of python will be covered with less emphasis on the basics of programming itself. The topics to be covered during the workshop shall include but not be limited to: Hello World Variables Loops and conditionals String Lists, Dictionaries and Tuples. functions File handling classes modules and imports lambda, map and reduce decorators and generators raising and handling exceptions sample exercises for the attendees to work on based on the concepts covered in the first half of the workshop.", + "Last Updated": "12 May, 2018", + "Prerequisites": "The person should be familiar with a *nix based operating system, and the shell should not be alien to them. Attendee should be familiar with the concepts of a hierarchical file system and at least be able to find where their editor saved the file they just created. Knowledge / experience of at least one other programming language will give them an unfair edge", + "Section": "Core python and Standard library", + "Speaker Info": "Anuvrat, along with his team at https://essentiasoftserv.com consults for python based projects which need help in maintaining, sanitizing and scaling to achieve their true potential.\nHe was one of the four who revamped the https://pydelhi.org community and volunteered for over a dozen https://pythonexpress.com workshops", + "Speaker Links": "https://anuvrat.i", "Target Audience": "Beginner", "Type": "Workshops", - "author": "Abhishek Kumar (~vibrantabhi19)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploring-pytorch-for-ai-assistance-in-medical-imaging~bqXpa/", - "title": "Exploring PyTorch for AI assistance in Medical Imaging" + "author": "Anuvrat Parashar (~bhanuvrat)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/yet-another-introduction-to-python~aKE8d/", + "title": "Yet another introduction to Python" }, - "22": { - "Content URLs": "This talk will be based on my article on Towards Data Science The hands-on examples have also been open-sourced on GitHu", - "Description": "Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. We will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D) using a hands-on approach with Python and popular open-source visualization libraries like matplotlib and seaborn. The talk shall be structured as follows: Motivation for Effective Data Visualization A quick refresher on Data Visualization Brief introduction into python open-source frameworks for visualization pandas matplotlib seaborn bokeh Univariate analysis with hands-on examples Multivariate analysis with hands-on examples Visualizing data in 2, 3, 4, 5 and 6 dimensions Visualizing a combination of numeric and categorical data Strategies for effective data visualization Conclusion", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basics of Python, data terminology (rows, columns, feature, data points, data types) helps but we will be covering briefly during the session. Hence it's not essential", - "Section": "Data science", - "Speaker Info": "Dipanjan Sarkar is a Data Scientist at Intel, on a mission to make the world more connected and productive. He primarily works on data science, analytics, business intelligence, application development, and building large-scale intelligent systems. He holds a master of technology degree in Information Technology with specializations in Data Science and Software Engineering. He is also an avid supporter of self-learning. Dipanjan has been an analytics practitioner for several years now, specializing in machine learning, natural language processing, statistical methods and deep learning. Having a passion for data science and education, he is a Data Science Mentor at Springboard, helping people up-skill on areas like Data Science and Machine Learning. He also acts as a contributor and editor for Towards Data Science, a leading online journal focusing on Artificial Intelligence and Data Science. Dipanjan has also authored several books on R, Python, Machine Learning, Social Media Analytics, Natural Language Processing & Deep Learning. More about me: LinkedIn: https://www.linkedin.com/in/dipanzan/ GitHub: https://github.com/dipanjan", - "Speaker Links": "LinkedIn: https://www.linkedin.com/in/dipanzan/ Blog Posts: https://towardsdatascience.com/@dipanzan.sarkar GitHub: https://github.com/dipanjanS Featured stories on KDnuggets: https://www.kdnuggets.com/?s=dipanjan+sarkar Recent books:- https://www.springer.com/us/book/9781484223871 https://www.springer.com/us/book/9781484232064 https://www.packtpub.com/big-data-and-business-intelligence/hands-transfer-learning-pytho", + { + "Content URLs": "", + "Description": "A short and crisp interactive session for the first time attendees of PyCon India to help them navigate through the conference and make the most of the next 4 days. 2011 was my first PyCon and in hindsight was a major turning point in my professional life. The experiences I had, the people I met and the friends I made during the conference are still shaping the choices I make and the decisions I take even today. PS: This will be a heavily opinionated talk and the attendees will be requested to weigh the advice being shared and adapt the ones that suit them the most. The audience will be implored to introspect and answer the following and more for them Which talks to attend? How to decide which talks to attend. Can I walk out of a talk in the middle? Should I attend every talk? What is the hallway track? Should I talk to strangers at the conference? How to start talking to strangers? Can I volunteer now that the conference is already happening? The volunteers are awesome people will they accept my help? How can I help? Should I help the volunteers? What is the dev-sprint? How to make the most of the dev sprint? I just started learning python, will people make fun of me if I speak? i need a job, what should I do? I need to hire, what can I do?", + "Last Updated": "12 May, 2018", + "Prerequisites": "A ticket to the conference, willingness to learn, un-learn and re-learn", + "Section": "Core python and Standard library", + "Speaker Info": "Anuvrat has been a part of PyCon India since 2011 where he found enlightenment and confidence to take charge of his education and steered his career in a direction that feels like success at least to him. These days, along with his team at https://essentiasoftserv.com he consults for companies that need assistance maintaining, scaling, and sanitizing their python based codebase", + "Speaker Links": "https://anuvrat.i", "Target Audience": "Beginner", "Type": "Talks", - "author": "Dipanjan Sarkar (~dipanjan)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-art-of-effective-visualization-of-multi-dimensional-data-a-hands-on-approach~ep6Vb/", - "title": "The art of effective visualization of multi-dimensional data - A hands-on approach" + "author": "Anuvrat Parashar (~bhanuvrat)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-make-the-most-of-pycon-india-2018~dLBva/", + "title": "How to make the most of PyCon India 2018" }, - "23": { - "Content URLs": "Will be updated soon", - "Description": "We all(probably) love facial recognition feature isn't it?. We all edit our images before posting it to social media to give a flamboyant touch and its done in too simple steps. Open the editing software, select what you want to configure(filters, Sharpness, etc.) and you're done. Quite easy, right? But what if you know how the back-end of how these softwares run? what if you know the what kind of codes make your camera detect objects? Well with OpenCV and python its simpler than you can imagine! My talk will be about OpenCV with Python. OpenCV is an acronym for Open Source Computer Vision Library . Its a library used for image processing. The code can be written in C++, Java or Python but since we all love Python, we'll use that. We will be using ' cv2 ' library for all the image processing and detection. My talk will feature: How images are stored in computer and how each pixels store image. Different types of Colour Bands and the role of Colour Bands in forming an image. Editing images with cv2 library in python. Blurring, Sharpening, Greyscaling, and other uses of image kernels. Object and Face Detection and live object Tracking using python and OpenCV.", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basic knowledge of Python and basic mathematics(Class 10th)", - "Section": "Others", - "Speaker Info": "I am undergraduate final year student, CSE branch from REVA University. I am a passionate programmer. I am an IEEE Volunteer. I was the Chair of IEEE Computer Society Chapter REVA University. Right now i am Student Branch Coordinator at IEEE Region 10(Asia/Pacific).\nCurrently I am interning at Valtech India as a Java Developer.\nI have taught python to more than 150 students in my college by taking sessions. I have taught OpenCV to more than 80 students.\nI have started loving python from 2016 when I read the book 'learn python the hard way by Zed Shaw'. My almost all the undergraduate projects are based on python", - "Speaker Links": "Blog: bit.ly/itsrohanvj\nGithub: itsrohanvj\nLinkedin: www.linkedin.com/itsrohanv", + { + "Content URLs": "https://github.com/DL4Jets https://docs.google.com/presentation/d/1dDxxsMkfg8vwMi7QDkDaVwCQnxsaXVh9-6xrgrkLvnY/edit?usp=sharin", + "Description": "Ever wondered if you could build your own deep learning framework for hundreds of users? Well, we did build one and turns out it's not as hard as it sounds. With thousands of people working towards democratising artificial intelligence (AI) , we have seen an explosion in the availability of machine learning libraries that make it simpler to build and deploy models for a wide range of tasks. From finance to art, every field has been revolutionised by the introduction of AI. At the European Organisation for Nuclear Research (CERN) we work on understanding the fundamental particles that constitute the universe by performing various experiments in particle physics. Of late, we have experienced a stratospheric rise in deep learning applications to various problems - RNNs, CNNs, and GANs - that have yielded promising results. Like, this stuff is so cool. It works! We delve into the development of one such project as it evolves from a set of scripts into a full-blown framework for supervised learning in high-energy physics. In this talk we will detail the evolution on the DeepJet Framework. It will delieate the development isssues, and how it evolved from a set of scripts hastily patched together to a structured, cross-platform framework built on top of Tensorflow and Keras. The library is a WIP so we're shipping updates on a daily basis with the goal of improving usability with focus on documenting our existing code base. Initially envisaged to support the development of the namesake jet-tagger in the CMS Experiment at CERN, it has grown to encompass multiple purposes within the collaboration. It is aimed at outlining how to go from a set of scripts to building a library that is used by hundreds of scientists in the world's largest physics research collaboration. The presentation will describe the major features the environment sports: simple out-of-memory training with a multi-threaded approach to maximally exploit the hardware acceleration, simple and streamlined I/O to help bookkeeping of the developments, and finally Docker image distribution, to simplify the deployment of the whole ecosystem on multiple datacenters. The talk will also cover future development aimed at improving user experience. ", + "Last Updated": "12 May, 2018", + "Prerequisites": "Preferred: Experience working with virtual environments or Anaconda Knowledge of basic ideas within machine learning such as training, testing, and evaluation of models Basic knowledge of particle physics helpful but not require", + "Section": "Data science", + "Speaker Info": "Swapneel is a computer scientist working at Compact Muon Solenoid (CMS) Experiment at the European Organisation for Nuclear Research where physicists and engineers are probing the fundamental structure of the universe. They use the world's largest and most complex scientific instruments to study the basic constituents of matter \u2013 the fundamental particles. His work at CERN encompasses the creation of a framework that can facilitate the use of deep neural networks and provide a suite of functions to serve multiple use-cases such as jet classification, particle identification, and so on. He is an open-source enthusiast, writing and contributing to various projects in his free time", + "Speaker Links": "Personal Website Github Medium Blog Writing - Open Source for You Magazin", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Rohan Vijay (~rohan96)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/computer-vision-with-python~bo9Xe/", - "title": "Computer Vision with Python." + "author": "Swapneel Mehta (~SwapneelM)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-deep-learning-framework-for-high-energy-physics~dN18b/", + "title": "Building a Deep Learning Framework for High-energy Physics" }, - "24": { - "Content URLs": "https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology I will update slides and code soo", - "Description": "Central dogma of life or of molecular biology is the core molecular process which keeps us alive! It's the machinery which converts DNA to mRNA to protein to active protein which eventually gets distributed in the body. DNA -> mRNA -> Protein Through this talk, I'll give a live demonstration of the processes by which this mechanism takes place and unravel its mysteries using Python! I'll explain how python is helping us simulating biological processes in the most elegant manner. How is DNA transcripted to mRNA? How is mRNA translated to protein? These are some of the questions I\u2019ll answer by simulating the actual processes using Python. By solving small challenges involved with this mechanism, I\u2019ll tell the audience, why Python is the best computer language for a bioinformatician and how great python libraries can make the life even easier especially BioPython. The challenges I am talking about are real bioinformatics problem, although basic, including translation, transcription and reverse complement. In the end, I\u2019ll brief some huge accomplishments of bioinformatics and computational biology and how we can contribute to this sector which has a promising future as well. Contents of the talk: Introduction : Introduction to gene and how we (computer scientists)\n recognize a gene Central Dogma of Life : a Live action of how a gene\n is converted to RNA and then to protein using Python. Why Python is best for biology? : Bioinformatics can be best studied using Python Impact of this sector : Accomplishments of Computational Biology and\n bioinformatics Conclusion : Possible ways in which we can contribute. Q & A session : Questions and answers session. Outcome: After the talk, the audience will have an understanding of how we function at a cellular level, how proteins are formed in our body and how can we simulate other biological processes using Python and will recognize the power of Python which can be harnessed in biology as well as other sciences. They will also have a basic introduction of BioPython", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Curiosity to learn :", + { + "Content URLs": "https://nim-lang.org http://slides.com/akapatkar/nim-for-python-programmer", + "Description": "Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org As Python programmers, we are used to a language which is expressive, intuitive and versatile. Python is widely lauded for its productivity, minimalistic syntax, standard library feature set and is an inspiration to newer languages like Go, Swift, and Julia. However, there are some areas like speed, distribution, and multicore processing where it lacks a good solution. Nim is a statically typed and high-performance garbage-collected language which builds upon Python\u2019s strengths and addresses someone its weakness in an innovative way. This talk introduces Nim to Python programmers by diving into powerful language design, syntax, data and control structures, static analysis, metaprogramming, portability/distribution and standard library features. At the end of this talk, you should have learned enough to a) get started with Nim on a project b) get familiar with Nim\u2019s growing ecosystem c) leverage/extend existing Python skills on a Nim project. Timeline breakdown: 1) Intro to Nim (10mins) 2) Language tour from Python\u2019s point of view (20 mins) 3) Things you can do with Nim + ecosystem (5 mins) 4) Q&A (5mins", + "Last Updated": "12 May, 2018", "Section": "Others", - "Speaker Info": "I have completed my B.Tech in Biotechnology this year from IIT Roorkee. I have interests in Web applications, Artificial Intelligence and Computational Biology. I have worked a couple of years in Computational Biology and Translational Bioinformatics Lab at my Institute and currently a Google Summer of Code student working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API ", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/simulating-central-dogma-of-life-using-python~enV7e/", - "title": "Simulating central dogma of life using Python" - }, - "25": { - "Content URLs": "Will be updated soon", - "Description": "Get to know Flask and how to create beautiful REST APIs in no time. Fall in love with Flask and learn the best practices for building APis in a hurry. Flask is a lightweight micro-framework for Python. Its simplicity and elasticity make it the best choice for building APIs in no time. In my talk, I will cover the basics concepts of Flask and Requests. I will show the tools that can automate the most common tasks in API development and will share the design patterns to avoid common pitfalls. Some of the specific tools and topics that I'll cover: Flask-Restplus, SQLAlchemy, request lifecycles, REST + CRUD API patterns, Flask architecture", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "No previous experience in Flask is needed", - "Section": "Web development", - "Speaker Info": "Sara is a seasoned software engineer and the Co-Founder of Gradient.gt, a data science and machine learning consulting company based in Guatemala, where she works crafting web applications and solutions to companies in need. When she is not coding, she spends her free time baking sweet treats and watching Rick and Morty", - "Speaker Links": "www.sara-codes.com Linkedin.com/in/sarairisgarcia Gradient G", - "Target Audience": "Beginner", + "Speaker Info": "I am a language enthusiast and a Python developer at Netflix. I\u2019ve been learning and using Nim for over a year now and I have benefited immensely from its learnings. There is a strong correlation between Nim and Python and I would like to explain that to the audience and show them a way to think problems using Nim\u2019s construct which I am sure will help them improve their Python skills. I am currently using Nim to write an interpreter for \u2018lox language\u2019. More details here https://github.com/cabhishek/nimlo", + "Speaker Links": "International Conference Talks: PyCon Ukraine 2018 https://2018.uapycon.org/#schedule PyCaribbean 2018 http://pycaribbean.com/schedule.html Python San Sebastian 2017 http://pyss17.pyss.org/", + "Target Audience": "Advanced", "Type": "Talks", - "author": "montjoile", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-apis-in-no-time-using-flask~bmVGd/", - "title": "Designing APIs in no time using Flask" + "author": "Abhishek Kapatker (~abhishek69)", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/nim-for-python-programmers~aO9Ed/", + "title": "Nim for Python Programmers" }, - "26": { - "Description": "A framework which will give a drag and drop web development option using Django as the backend", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Python and basics of Djang", - "Section": "Web development", - "Speaker Info": "Sanket Sarkar [ Microsoft Technology Associate {Introduction to Python Programming}]\nA final Year Student of B.Tech", + { + "Content URLs": "https://github.com/bhagvank https://ingeniopythonis.wordpress.co", + "Description": "Video content management, AI, Blockchain and Virtual/Augmented reality technologies are changing the learning management platforms. Customer focused learning systems are emerging in enterprises. Enterprises are structuring their curriculum products to help solve the high value use cases of their customers. Members of the LMS system (python/ Django stack) can tailor their educational experience by choosing courses based on their learning styles. The courses are becoming more effective and helping members retain information. Platforms are differentiating by providing better, faster ways to find relevant content, whenever and wherever learners need it. Modern learning management platform is an end-to-end eLearning solution which has capabilities to create, distribute, edit and manage entire courses from start to finish independent of the content. Educational success and fulfilment are achieved through personalization and optimization of the learner\u2019s path through courses and gaining of competencies. This new class of learning technology vendors is making it possible to augment their systems with cloud-based applications which can be easily integrated with an enterprise-scale technology ecosystem. Enterprises are now tracking and analyzing learning experiences with incredible precision which can be used to improve ongoing program and business outcomes. Tracking and reporting comes in learner-oriented dashboards and reports built for the staff", + "Last Updated": "12 May, 2018", + "Prerequisites": "python, djang", + "Section": "Data science", + "Speaker Info": "Co-Founder of Architect Corner, Bhagvan has around 18 years experience in the industry, ranging from large scale enterprise development to helping incubate software product startups. He has completed a Masters in Industrial Systems Engineering at Georgia Institute of Technology, and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras", + "Speaker Links": "https://www.youtube.com/channel/UChu9J4M85CC7C8hMYp5cgRg/video", "Target Audience": "Advanced", "Type": "Talks", - "author": "Sanket Sarkar (~sanket78)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/drag-and-drop-framework-for-django~elVMb/", - "title": "Drag and Drop Framework for DJANGO" + "author": "bhagvank", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-management-next-generation-platform~dPJ6a/", + "title": "Learning Management : Next Generation Platform" }, - "27": { - "Content URLs": "Content will be updated soon", - "Description": "You all would have often faced the issue of not being able to recognize handwriting, either it is a Doctor's prescription or sometimes, even your friend's assignment. This problem might have caused some harm, maybe due to the delay in submitting the assignment or seeking chemists' that can recognize that particular handwriting.\nTherefore, in this talk, we will be focusing on how Python and Data Science can be used to recognize handwritten digits and character which will ease out the pain of recognizing haphazard writings. Topics to be covered: What is Handwritten Digit and Character Recognition? Why we need it and uses of it? How Python can help in achieving this? Future Scope", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " Basics of Python Basics of Data Science", + { + "Content URLs": "For workshop home here and here such as to get sample data, Jupyter notebooks, slides etc For workshop slides pls see her", + "Description": "Geospatial representation are so prevalent in day to day life, such as even in simple travel related conversation to maps, aerial/satellite images etc. In digital era, geospatial data is extensively produced and consumed in ever growing proportion. Python with its free and open source libraries are giving wide variety yet simple and effective set of tools to visualise and analyse geospatial data. The current workshop is directed for beginners of Python programming language, who have basic understanding on computing and data formats. The primary objective of the workshop is to introduce and give hands on training on selected list of FOSS libraries for geospatial analysis. The workshop as a do it yourself fashion tries to solve two real world problems in Geographical Information System (GIS) and its geospatial data sources. The workshop comprised of three components: Component 1 Python environment and work flow setup, an assisted task of setting up the Docker and Jupyter notebook setup. Setting up the Geographical Information System (GIS) environment with extended discussion. Setting up of GIS tools such as FOSS QGIS and Google earth. This component is comprised of four exercises. 1. Introduction to vector data, 2. Introduction to raster data, 3. binary and text file formats of geospatial data, 4. Introduction to tools of GIS, 5. Introduction to literal programming- Jupyter notebook Component 2 Find characteristics of road network(type of road network, length of the type) within a 1X1 km grid. The data source is Open Street Map (OSM) road network data on a city level (60X60km size). This operation is operationally simple such as measure a line feature but computationally intensive as the operation comprised of geometry within operation on dense road network seen in urban setup. Libraries such as Shapely, Fiona, Geopandas and rtree index will be used for the fast processing of this operation. This component comprised of three exercises 1. Find distance between two points 2. Find distance between two points constrained by another vector 3. Find distance between large number of points in for loop Component 3 Find cloud cover percentage over area of interest. The data source is Landsat satellite imagery. Searching cloud free Landsat images over an Area of Interest for a temporal extent of a year or more is manual and time consuming. Applying cloud cover detection algorithm could make this operation automatic. Libraries such as rasterio, Geopandas, Fiona, and libraries related to landsat algorithms will be used for this task. This component comprised of two exercises 1. Convert the imagery in geotiff into numpy arrays 2. Apply the algorithms to find the cloud cover Workshop Plan Introduction and setup- 30 minutes Component 1- 30 minutes Component 2- 45 minutes Component 3- 45 minutes", + "Last Updated": "12 May, 2018", + "Prerequisites": " Laptop 32bit/64 bit Workshop material is tested on 64 bit computer, it is said to be working in 32 bit, lets experiment! A copy of Docker container image from here , file from the link foss-pt-gsa_v3.tar.gz is 2.5 GB in size, will be using this container for DIY Local copy of Docker toolbox from here for windows 64 bit, for 32 bit Windows, follow this link , if any issue, don't worry, we have a session for setting up the docker! Local copy boot2docker.iso from here , we will be following old method of docker toolbox instead of docker native software for Windows.", "Section": "Data science", - "Speaker Info": "I'm Prashant Pandey. I've deep interest in Data Science, especially in Python. I've been working in the domain of Data Science since one year now, and have completed several projects. Presently, I'm working on Handwritten Digit and Character Recognition", - "Speaker Links": "https://github.com/Prashantpandey2398", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Prashantpandey2398", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handwritten-digit-and-character-recognition-using-python~bkV6a/", - "title": "Handwritten Digit and Character Recognition using Python" + "Speaker Info": "I am a research associate at UrbanEmissions.info . My doctoral study was related to interoperable management of data from air pollution monitors and atmospheric models. I used free and open source libraries of Python for the study, especially on geospatial data compilation, analysis and visualization. Freedom and customization of free and open source languages such as of R and Python were immense. After Conda python package manager came into existence, the world of Python was so easy and I started to use Python for most of computing", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "nishadhka", + "created_on": "12 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/free-and-open-source-libraries-of-python-for-geo-spatial-analysis-and-visualisationmaps-and-satellite-imageries~aQL5e/", + "title": "Free and Open Source libraries of Python for Geo spatial Analysis and Visualisation(Maps and Satellite imageries)" }, - "28": { - "Content URLs": "Will be updated soon", - "Description": "Your machine learning models might be intelligent enough to make predictions but may lack the wisdom to prevent bias. They may be as vulnerable as a child getting influenced by inappropriate sources encouraging racism, sexism or any unintended prejudice. Models learn exactly what they are taught. The more biased your data is, the more biased is your model. For instance, a text model by Google says how \u201cEngineer is to a Man\u201d is the same as \u201cHousewife to a Woman\u201d. This shows how incidental data can lead to unintended bias. Machines are given the power to judge so there is a need for us to ensure we prevent biased/unfair judgements. In this talk, we are going to discuss What is Machine Learning bias? How is it caused? Different ways to identify bias? Techniques to prevent bias One Famous example of bias:", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Knowledge in python3 and pandas Knowledge of building machine learning models Little idea on deep learnin", - "Section": "Others", - "Speaker Info": "I am a software developer, speaker, opensource contributor and a wannabe developer evangelist. I love everything python and NLP(Natural Language Processing) research. I have been volunteering with various local startup and tech communities to promote entrepreneurship and technology. I work at mroads and help them develop better a.i", - "Speaker Links": "Links: Linkedin: https://www.linkedin.com/in/poornagurram/ Github: https://github.com/poornagurram StackOverflow: https://stackoverflow.com/users/5443381/poorna-prudhv", + { + "Description": "Millions of visitors visit business websites every day and each one of them takes different set of steps in order to seek the right information/product. Yet most of them leave disappointed or dejected for some reason and very few get to the right page within the website. In this kind of situation, it becomes difficult to find out if the visitor actually got the information that he was looking for? Also, the individual journeys of these visitors can\u2019t be compared to each other since every visitor has done different set of activities. So, how can we know more about these journeys and compare these visitors to each other?\nSequence Embedding is a powerful way that offers us the flexibility to not only compare any two distinct visitors entire journey in terms of similarity but also to predict the probability of visitor\u2019s conversion. Sequence embeddings essentially helps us to move away from using traditional features to make predictions and considers not only the order of the activities of a user but also the average time spent on each of the unique pages to translate into more robust features and used in Supervised Machine Learning across multiple use cases (next possible action prediction, converted vs non-converted, product classification)\u00a0.Using traditional Machine learning models on the advanced features like sequence embeddings, we can achieve tremendous results in terms of prediction accuracy but the real benefit lies in visualizing all these user journeys and observing how distinct are these paths from the ideal ones. This session will unfold the process creating sequence embeddings for each user\u2019s journey in python and use them to build machine learning classification model to predict visitor conversion along with comparing all the user journeys in terms of similarity score", + "Last Updated": "14 May, 2018", + "Prerequisites": "Basic understanding of Machine Learning ,\nPython Basic", + "Section": "Data science", + "Speaker Info": "Co-Founder of DataScienceBridge and currently Sr. Data Scientist at SapientRazorfish core Data Science Team has around 8 years\u2019 experience in the industry, ranging from large scale IT enterprise business development to building complex Machine Learning models by applying state of the art techniques. He has completed his Master\u2019s in Business at Symbiosis International University and certified professional in Machine Learning from IIM-Calcutta.\nHis core expertise involves Machine Learning, Deep Learning, Recommendation Systems using python, spark and Tensorflow for various projects. He is president of Data Science meet up group at SapientRazorfish and conducts multiple webinars on Machine Learning. Along with that he is also a speaker and recently presented a talk at \u201cGreat Indian Developer Summit \u201c(GIDS 2018).\nIn his spare time, he likes to read, code and help aspiring Data Scientists", + "Speaker Links": "https://www.youtube.com/watch?v=Nbpz79v2y5", "Target Audience": "Intermediate", "Type": "Talks", - "author": "G POORNA PRUDHVI (~poornagurram)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-fair-machine-learning-systems~egVkd/", - "title": "Building fair machine learning systems" + "author": "Pramod Singh (~pramodchahar)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sequence-embeddings-in-python-classification-user-journey-comparison~dRBwd/", + "title": "Sequence Embeddings in Python: Classification & User journey Comparison" }, - "29": { - "Content URLs": "Will come soo", - "Description": "Blockchain Technology is the talk of the town. Almost all articles published have some relation to Blockchain concepts.\nWhile Public Networks usually pertain to Cryptocurrency, Private networks pertain to business-level implementations. In order to develop with this technology as our base, it is important to understand the key features, as well as make implementations using the existing skillset, which happens to be the Python Programming Language. The talk will feature Complete in-depth explanation of Blockchain technology, and the working of Bitcoin as an example. Developing your personal Cryptocurrency with Python Introduction to Hyperledger Sawtooth, and understanding how and why to use Python with it. Best practices to consider in mind while developing for a blockchain. By the end of the talk, you will be able to Explain the concepts of Cryptocurrency and Blockchain technically. Understand Python's role in one of the most popular frameworks created by Intel, and implement your own ideas with the same.", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "General Pytho", - "Section": "Others", - "Speaker Info": "Hi, I'm Priyansh! Here's a quick bio. CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms. Technical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", + { + "Description": "A lot of budding programmers use print() function or logging module to display the state of the program. However, it soon becomes untenable to reason about the program in a barrage of print statements. At that time, a debugger is a must. Debuggers are a better and structured way to inspect a program. A practical and basic understanding of debuggers will help in locating bugs easily and save developer's time and unnecessary frustration. In this talk, we are going to learn the terminology associated with debugging and explore the most commonly used commands of pdb", + "Last Updated": "14 May, 2018", + "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college students or people who just started programming in Python", + "Section": "Core python and Standard library", + "Speaker Info": "I'm currently a Senior Web Developer and Curriculum Designer at Pesto Tech. I've programmed in Python and Flask since the last 3 years. Open source enthusiast, and frequent blogger", + "Speaker Links": "Medium - https://medium.com/@arfatsalman Twitter - https://twitter.com/salman_arfat GitHub - https://github.com/ArfatSalman LinkedIn - https://www.linkedin.com/in/arfatsalman", "Target Audience": "Beginner", "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-with-python~e0yLa/", - "title": "Blockchain with Python!" + "author": "Arfat Salman (~ArfatSalman)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-basics-and-debugging-python-scripts-with-pdb~eVZoe/", + "title": "Debugging basics and debugging python scripts with pdb" }, - "30": { - "Content URLs": "Will be updated soo", - "Description": "Automation is something we all desire, may it be the twitter feed of a celebrity, or perhaps the latest price of bitcoin. For students, it can range from tracking assignment deadlines or message updates. For developers, it can be the tracking of an important issue or auto merging of pull requests. For management, deadlines for a work assignment or a due presentation. With Python, everything listed above is possible. The talk will feature how to start automating the small things that can prove highly productive. We will use simple libraries first, and this will be followed by using fully headless browsers like selenium and understanding the concepts of web crawling. Integration of API services like Google Calendar and Google keep, to sync all the data collected will be demonstrated. Finally, we will deep dive into an interesting open-source project I made, and how I have automated most of my college work", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic understanding of REST APIs and Frameworks, and Beginner-Intermediate Level of Python Programmin", + { + "Content URLs": "https://github.com/devxp", + "Description": "My talk is related to my work on ZProc , a library for doing multiprocessing in python Its provides a high-level wrapper over zeroMQ, the distributed messaging library. I will provide a basic introduction to the ways we can natively implement concurrency/parallelism in our applications and how ZProc is a better way to do multi-tasking", + "Last Updated": "14 May, 2018", + "Prerequisites": " A good knowledge of basic python. Some knowledge about the python Process/Thread interface is appreciated If you ever had your hands on the zguide , I have a hunch you'll like this. ", "Section": "Developer tools and Automation", - "Speaker Info": "CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms.\nTechnical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", + "Speaker Info": "I'm 19 year old python programmer, picked up python when I was around 15. My adventures with multi-tasking applications started when I was 17, trying to build a concurrent youtube downloader. I am since, trying to find ways to make writing concurrent, multi-core applications simpler in python", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-your-life-with-python~b873a/", - "title": "Automating your life with Python" + "author": "Dev Aggarwal (~devxpy)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/zproc-process-on-steroids~bWBoa/", + "title": "ZProc - Process on steroids" }, - "31": { - "Content URLs": "Will be updated soon", - "Description": "Dash is a Python framework for building analytical web applications, built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs to your analytical Python code. The workshop will include building interactive dashboard with Dash framework. How to visualise the data purely in python will be the key take away", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Python 3 Pip3", - "Section": "Web development", - "Speaker Info": "I am software engineer working at Juxt Smartmandate, who believes in creating products using open source technology", - "Speaker Links": "https://github.com/kapoorabhish https://www.linkedin.com/in/abhishek-kapoor-4b7b9295", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "kapoorabhish", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-interactive-dashboard-using-plotly-dash~e771e/", - "title": "Building interactive dashboard using Plotly Dash." - }, - "32": { - "Content URLs": "A sample code can be found here :\nhttps://github.com/KaustabhGanguly/Recurrent-Neural-Networks-to-predict-Google-Stock-Pric", - "Description": "I will show you how to predict google stock price with the help of Deep Learning and Data Science .\nThe predictions are not realistic as stock prices are very stochastic in nature and it's not possible till now to accurately predict it .\nAs I'll only have 30 mins to talk , I can't train the data and show you as it'll take several hours for the model to train on google collab . So , I will show you : Basics of Recurrent Neural Networks and LSTM Basics of pytorch Coding line by line with describing every words Then starting to train the model and prematurely closing it and move forward to show you the results that I'll bring with me after training .", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "You should have basic pyTorch understanding but I'll guide you anyways through the basics .\nBasic understanding of LSTM or RNN is preferred but not required ", + { + "Content URLs": "https://atad.xyz\n[ Will share the GitHub repo during the talk with sample web crawlers ", + "Description": "Introducing to Web Scraping. A complete walkthrough the below items: Challenges in scraping websites and parsing the data, Introducing Scrapy, a widely used framework to extract data Dos & Don'ts Usage of Proxies & IP Rotation Crawling hundreds of websites, running and scaling them to huge volumes", + "Last Updated": "14 May, 2018", + "Prerequisites": "Laptop with Ubuntu or a similar OS. \nPython and MySql latest versions Basic understanding of Python and MySql\nGood to have knowledge in writing Xpaths and usage of proxie", "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India . I'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 . I'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github : github.com/kaustabhganguly Connect with me on linkedin : linkedin.com/in/kaustab", + "Speaker Info": "I am Raja Emmela, \nI Run Headrun Technologies, Bangalore - helping clients in Data Scraping and Web Applications We are in this space for the last seven years, extracting data and parsing them. My experience helps do share the challenges we faced with domestic and NA & APAC clients while scraping websites and the don'ts in particular", + "Speaker Links": " LinkedIn Twitter Blog", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-stock-price-time-series-prediction-with-rnnlstm-using-pytorch-from-scratch~b67Rd/", - "title": "Google Stock Price Time Series Prediction with RNN(LSTM) using pytorch from Scratch" + "author": "rajaemmela", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-intro-to-web-scraping-dos-donts-and-the-challenges-in-scaling-it-to-huge-volumes~eXVVb/", + "title": "An intro to Web Scraping, dos & don'ts and the challenges in Scaling it to huge volumes" }, - "33": { - "Content URLs": "The code is in this repo :\nhttps://github.com/KaustabhGanguly/Smile-Detector :", - "Description": "In this era of deep learning and machine learning , the beginners may get lost sometimes , as there is a steep learning curve involved with the process .\nWhen I was starting out on machine learning , I always wanted to get my hands dirty in the advanced stuffs but It was hard for me and there was no guidance .\nSo , in this talk and coding session I will guide you through how you can build your own facial recognition system and implement a smile detection very quickly and easily with the power of openCV and python . It will take 10 mins and any beginner with basic knowledge of python can grasp the concepts easily .\nI will not use convNet or anything ,but a model called HaarCascades . It's an old mathematical model which was/is mainly used where deep learning is not an option . I will guide you through the basics and tell you some quick things and facts and we will enjoy a lot . See you on pyCon 2018 ! kindly upvote if you want some quality 10 mins learning something new ", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic Python knowledg", + { + "Content URLs": "Sensor Fusion Introduction\nhttps://youtu.be/C7JQ7Rpwn2k Sklearn Quick Tutorial\nhttp://scikit-learn.org/stable/tutorial/basic/tutorial.htm", + "Description": "Abstract The primary purpose of this talk to describe how we are using python and Sklearn to model and analyse time series sensor data. In particular, I will walk through how we use Python to process data from an IoT enabled sensor attached to a cricket bat, build machine learning models on the data, and use open source tools to deploy our models in the sensor device as a smart IoT application. Description With the steep increase in the number of smart-things connected to the internet, the amount of data that is being generated by such devices is increasing exponentially. However, much of that data is not useful and therefore filtering unuseful data is an important task. How do we filter the important part and remove the noise from sensor data streams to generate actionable insights? To demonstrate the problem we are placing a sensor device on a cricket bat. The IoT device is a miniaturised, wireless MEMS inertial measurement unit (IMU). The IMU incorporates three-axis sensing of bat acceleration and angular velocity with a low-power Bluetooth to transmit this data to a mobile. First, we gather event-based data rather than storing the entire stream. This again poses the question: how do we define an event? What makes an event unique from the surrounding \u2018non-event\u2019 context? These are some of the questions that need to be answered in order to define an event. Watching a cricket batter stand and prepare to swing, the human brain continuously filters its visual perception and is able to detect and differentiate a swing from the pre- and post-swing activity. We need to be able to automate that same process. Some data instances can be tagged while other can\u2019t be. This helps in training and evaluating machine learning models later. Secondly, After we have extracted time series data based on the instances, we can start analysing these event-based sets of data to understand the language of sensor data. For this, we are using Jupyter Lab to interactively work with data. How does an accelerometer data depict the real world physical motion? This step helps us find the relation between the real world actions and the sensor data set. Well, the extraction process will be prone to noises. The data comes in CSV files, python seems the right choice for us to read and analyse the data. Pandas and offer data frames that come handy to rapidly form and validate hypothesis interactively in Jupyter notebooks. Any analysis is incomplete without visualisation, that's where Matplotlib helps us understand the data better. We quickly test the machine learning models by using Sklearn, which has most of the standard algorithms already implemented. This keynote will describe some of the analysis (along with python code) to show how we have taken several steps right from forming the hypothesis to implementing a solution in the device level layer. All of this demonstrates how Python and its rich set of libraries are helpful in forming solutions to some of the product related features. Thirdly, we need to automate the task of classifying a particular instance from the stream. For this to happen, we can either feed a machine learning model or create a rule-based algorithm which can classify the events into buckets. Now every step has its own set of challenges, firstly the application we are working on involves using motion sensors attached to the back of a cricket bat. There are network constraints in the field. If a sportsperson wants to know real-time analytics from the device, the segregation needs to happen offline. We have to deploy the models on the miniature sensor devices because sometimes the players don\u2019t even carry their mobile phones to the playing area. Therefore our objective is to enable the devices to remain independent in running machine learning algorithms by themselves", + "Last Updated": "14 May, 2018", + "Prerequisites": "Participants should have an understanding of python basics", "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India .\nI'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 .\nI'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github :\ngithub.com/kaustabhganguly\nConnect with me on linkedin :\nlinkedin.com/in/kaustab", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quick-and-easy-implementation-of-smile-detector-on-your-webcam-using-python-and-opencv-from-scratch-without-any-neural-network-and-for-beginners~e5E8e/", - "title": "Quick and easy implementation of Smile Detector on your Webcam using python and openCV from Scratch without any Neural Network and for beginners ." - }, - "34": { - "Content URLs": " Apache Beam : https://beam.apache.org/ Apache Beam Python SDK : https://beam.apache.org/documentation/sdks/pydoc/2.4.0", - "Description": "Data together with 3Vs characteristic, volume, variety and velocity is labelled as Big Data. Big Data and parallel processing have been hot topics since Google\u2019s paper on MapReduce and till today the era of different runners like Apache Spark, Google Cloud Dataflow etc. Apache Beam is a unified big data processing paradigm which enables the user to run batch and streaming data processing jobs on multiple execution engines like Apache Spark, Apache Flink, Google Cloud Dataflow etc. *Objective of the talk* : Overview of Apache Beam Python SDK Core SDK constructs like Pipeline , PTransform , PCollection etc. Creating custom DoFns and composite Transforms Creating a Pipeline with customizable options Running a pipeline on different runners like DirectRunner , DataflowRunner etc Unit testing a Pipeline with asserts Demo: StreamingWordCount example using Google Cloud Dataflow Q&A", - "Last Updated": "22 Jun, 2018", - "Prerequisites": " A little knowledge about Python 2.7 Enthusiasm for Parallel Data Processing Motivation to play with lots of Data", - "Section": "Others", - "Speaker Info": "I am Mukul Arora, working as a Software Engineer in Schlumberger India Technology Centre. I graduated from Delhi Technology University in May 2017. I am a Data Science and Big Data practitioner and have been highly involved in solving Computer Vision and Medical Imaging problems using Deep Learning Techniques. Currently, I am exploring efficient ways to solve Big Data problems on Cloud.\nI am an avid cricket fan and love to write poems", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/mukularoradce/ Github : https://github.com/codemukul95 YourQuote : https://www.yourquote.in/mukul-arora-ffds/quotes", + "Speaker Info": "Sanjiv Soni is a data scientist at Str8bat, Bangalore. He currently an international fellow at University of San Francisco for Deep Learning Programme. Sanjiv has experience with Software and product ecosystem. He has interests in building software devised solutions to problems solved by humans", + "Speaker Links": "https://twitter.com/sanjivsoni7 https://www.linkedin.com/in/sanjiv-soni", "Target Audience": "Intermediate", "Type": "Talks", - "author": "mukul arora (~mukul11)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unified-and-portable-parallel-data-processing-using-apache-beam~b4Dxb/", - "title": "Unified and Portable Parallel Data Processing using Apache Beam" + "author": "sanjiv soni (~sanjiv)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/swing-and-a-miss-deploying-machine-learning-models-for-iot-enabled-devices-using-python~bYXYa/", + "title": "Swing and a Miss: Deploying machine learning models for IoT enabled devices using Python" }, - "35": { - "Content URLs": "A similar version of this talk was recently delivered at Pycon APAC2018 (Singapore). Slide deck: https://goo.gl/xRRdKt An attendee's review of my talk: https://tryolabs.com/blog/pycon-apac-2018-singapore-experience", - "Description": "Offensive / abusive content is a major issue for social-media and digital interaction platforms. In some jurisdictions (Eg: Europe), platform providers are required by law to remove such content within 24 hours of posting or risk hefty fines (upto \u20ac50M in Germany). In order to meet the governance mandate, we need to have systems in place that can automatically detect abusive content at scale. This talk is based on my practical experience of building an automated solution to solve this problem. This talk begins with discussing some of the approaches currently being employed for offensive content detection at scale: word filtering, rule-based systems and actual human annotation. The former two are restricted by the following: Offensive content is context specific. A given word (f ck) can be used in both positive (that\u2019s f cking awesome) and negative (that\u2019s f*cking terrible) contexts. Robustness to spelling variations (The word \u2018shit\u2019 can be spelt as \u2018sh*t\u2019, \u2018sh!t\u2019, etc) Failure to detect content that is offensive in idea but uses non-offensive words. (Eg: your mom is a fat cow, X people are inferior, etc) Manual human annotation is notoriously hard (ask Google!) and expensive to scale. The talk presents a Deep neural network based approach to overcome the previously mentioned limitations. It introduces and discusses the building blocks of model architecture (deep convolutional networks, word embeddings, etc). The second half of the talk focuses on implementing the above model to solve the problem at scale as a RESTful micro-service using python, Django, Tensorflow and Docker. This architecture can also be used to implement other text classification systems as well (eg: user intent detection systems, topic-of-discussion classifiers, etc.), making the talk relevant for a wider user base. Attendees will: Gain insights into building deep learning based text-classification systems that can scale Learn the nitty gritties of the offensive content detection and text classification Learn about the basic concepts of Deep Learning and NLP (convolutional neural nets, multi-layer perceptron, word embeddings, etc.) Understand the scientific and software challenges involved in text classification and learn to overcome them Be able to apply the learnings from here to other text classification problems as well", - "Last Updated": "22 Jun, 2018", - "Prerequisites": "Just bring an open mind ;", - "Section": "Data science", - "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. He is currently employed as a Machine Learning Engineer. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", - "Speaker Links": "https://www.linkedin.com/in/alizishaan-khatri-32a2063", + { + "Content URLs": "I will soon share presentation, resources, and code soon on GitHub", + "Description": "Abstract Think of wireless internet, but has the wire somewhere. Serverless architecture still has the server behind :P. What serverless actually means that developer should focus on the code rather than thinking about the servers. As a technique, it removes most of the manel parts of an application, so you can actually spend your day coding. This means that you, developers, can quickly create apps that handle production-ready traffic. You do not have to actively manage scaling for your applications. You do not have to provision the server, or to pay for resources that are unused. The serverless movement started with the release of AWS Lambda, a Function-as-a-Service (FaaS) compute service. But serverless is much more than just FaaS Chatbots have been around for quite a long time. But why this sudden surge and interest in chatbots now? Well, there are various reasons. Unlike the earlier days, many AI and NLP capabilities are now available as consumable services. Also, serverless technologies make chatbots easier to build and scale. The question is, how is the backend served? Would you set up a dedicated server (or a cluster of servers)? That\u2019s costly, painful, and time-consuming! or You will deploy it to Heroku, which will eventually sleep (only happens in the free tier) if no one uses your chatbot. Imagine suddenly, traffic increased your chatbot is used by thousands of people at a time. When Heroku free tier is over, the application crashed or you exceeded memory limit. What would you do now? That\u2019s where serverless technology can help. Benefits of serverless No Administration - We can deploy our code without provisioning anything beforehand, or manage anything afterward. There is no concept of a fleet, an instance, or even an operating system. Scalability - One doesn't have to care about auto-scaling, No need to show alerts or write scripts to scale up and down. With serverless, we can handle quick bursts of traffic. Cost - Function-as-a-service (FaaS) compute and managed services charged based on actual usage rather than pre-provisioned capacity. This means one pay the amount we use, so if we use service for 10 sec then we pay for 10 sec. Faster Development - Now loop between having an idea and deploying to production is shortened because no one need to manage anything after deployment, smaller teams can ship more features. It's easier than ever to make your idea live. Easy Integration With Other Services Going serverless allows a seamless integration to various other cloud services from the same provider. For example, if you are using the AWS platform for chatbots, then you can use DynamoDB for the database, write programming logic as Lambda functions, and expose them through the API Gateway. Session key Takeaways The main question is how to write code which is serverless compliant. This is where this session will help you. This talk will help people to move a step ahead of the traditional way of writing code as some of you had already developed chatbot, I will share how can you can write the simple chatbot in python and can take leverage of serverless to deploy and publish. I will cover Serverless Framework principals AWS Lambda, Amazon Lex and API Gateway How to write a chatbot in python and create a Lambda function How to troubleshoot in a serverless world", + "Last Updated": "14 May, 2018", + "Prerequisites": "Basic knowledge of python and development in general", + "Section": "Others", + "Speaker Info": "Vaibhav Singh is an undergrad final year student of BML Munjal University, Gurugram. He had worked with AWS services as a solution architect intern in Amazon and he is also open source enthusiast and contributed to many open source organization like Fossasia, coala, etc. He is now Google Summer Of Code intern with FOSSASIA. Previously, He was the finalist winner in Codeheat competition. I write mostly in python ;). I had written various small scripts to make my life easier :", + "Speaker Links": "Website GitHub Twitter Facebook Linkedin Mai", "Target Audience": "Beginner", "Type": "Talks", - "author": "Alizishaan Khatri (~alizishaan)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/detecting-offensive-messages-using-deep-learning-a-micro-service-based-approach~e30Ra/", - "title": "Detecting offensive messages using Deep Learning: A micro-service based approach" + "author": "Vaibhav Singh (~vaibhavsingh97)", + "created_on": "14 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-serverless-framework-build-a-chatbot~eZXgb/", + "title": "The Serverless Framework - Build a Chatbot" }, - "36": { - "Content URLs": "Git Hub Repository : click here Demo: click her", - "Description": "The workshop will be escalating from a very beginner level and so I only require you to know the basics of python and if possible a glance of the OpenCV library. The workshop will be proceeding accordingly : Basics of Image processing. Image classification using Deep Learning ( CNN ). Deploying your own Emotion recognizer. ", - "Last Updated": "21 Jun, 2018", - "Prerequisites": " Basics of Python Please download and install the following libraries in beforehand : Pytorch OpenCV Fastai numpy matplotlib dlib imutilis We will be using all of the mentioned libraries to make the goings of the workshop easy to understand and implement. Additional Files : Please download from her", - "Section": "Data science", - "Speaker Info": "I am shaaran and my main aim is to take technology to everyone and spread my knowledge as far as I can, in a journey to fulfill my dreams I have went to many institutions and have conducted workshops and talks in Robotics and AI, I am currently a second-year student at VIT University and also a part of many organizations like Google Developers Group, RoboVITics and more , I have interned at Toshiba recently and have made a new AHU control system using IOT and AI", - "Speaker Links": "Github: click here Linkedin: click her", + { + "Content URLs": " Coming soon...", + "Description": "Take it from someone who has introduced an exorbitantly high number of bugs in empty files for most of his life: debugging is hard indeed. But since the dawn of time, developers have been debugging code: there's no escaping that. Software testing, as the elders would tell you, is one of the greatest weapons in your arsenal against those bugs. It's easy to write tests. It helps you write more robust software. And it really helps you sleep at night: and your on-call ops team would love you! But testing is also deeply mystified, unfortunately. Beginners, and sometimes even seasoned developers, generally have a difficult time just to get started: so they eventually miss out on this easy way to attain peace of mind. This talks aims at removing all the mystery around software testing in Python, and give the attendees a head-start into the easiest way of writing tests for their code. As part of being a Python developer for the past 8 years and leading a team of developers building enterprise-grade software for the past 4 years, I've learnt immensely about the important role of software testing in building scalable, durable software; and also a better, pragmatic way of thinking about testing in Python. This talk aims at providing a distilled version of my learning to the audience: both beginners to Python, and seasoned Pythonistas. The talk would broadly cover these topics: A formal way of thinking about software testing / Why you should even bother about writing tests? Writing the simplest of tests in Python / Brief exploration of unittest and pytest Introduction to mocking in Python / In-depth exploration of mock and how to effectively use it for mocking any type of scenario in your code Writing tests for complex applications / working code examples from real life \u2014 This section would contain walkthrough of tests written in a few real-life applications and Python libraries, and a discussion on how to add test coverage for things that might not seem very straightforward to mock in a unit test. A few (opinionated) recommendations about testing Apart from providing to the audience an easy-to-grasp framework of thinking about software testing, this talk aims to teach by examples from real world. Complex and not so straightforward concepts would be explained with code samples and tests from production, so it's easy for the audience to truly grasp them. The talk also features anecdotes from my own experience in building software to give the audience better context", + "Last Updated": "15 May, 2018", + "Prerequisites": "This talk is intended for newcomers to Python (who might never have written a test yet), as well as experienced developers (who might not be writing tests effectively). There are no technical pre-requisites for this talk. The key takeaways would be patterns you can directly start using in writing tests for your own code", + "Section": "Developer tools and Automation", + "Speaker Info": "Sanket ( @sanketsaurav ) is co-founder and Chief of Geeks at DoSelect . He\u2019s 50% developer and 50% designer. He\u2019s been dabbling with computers since the age of 10, and had started his first venture at 18. He loves the Web and likes building cool stuff that matter. His languages of choice are Python, Go and JavaScript, and he\u2019s been building production apps using these for the past two years. He\u2019s also spoken at more than 50 events and hackathons across the country on open source technologies including Python, HTML5 and web applications in general. Sanket also contributes extensively to open-source, with contributions to projects like Django, Celery and Docker, and original Python modules like S3Tree and mimelib ", + "Speaker Links": "Social presence: GitHub Website DoSelect Past talks: Talk at PyCon India 2017 Talk at PyCon Pune 2017 Talk at PyCon India 2013 Django on Steroids -- Slides Lessons from Scale: Django", "Target Audience": "Beginner", - "Type": "Workshops", - "author": "shaaran Lakshminarayanan (~devshaaran)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-your-own-emotion-recognizer-from-scratch~b2rzb/", - "title": "Building your own Emotion recognizer from Scratch !" + "Type": "Talks", + "author": "Sanket Saurav (~sanket)", + "created_on": "15 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-is-hard-testing-is-easy~e17qb/", + "title": "Debugging is hard, testing is easy!" }, - "37": { - "Content URLs": "https://github.com/someshchaturvedi/customizable-django-profiler Will be updating slides soon", - "Description": "Django, as we all know, is an excellent framework for building high stable, scalable, extensible web apps. Django framework operates around middlewares. Do we really understand how a middleware works? What happens when the request comes in and response goes out? Which middleware is used for what purposes? Why is the order of middleware stack important? How can we implement a custom middleware? Benefits and complications of implementing custom middlewares My talk will cover all the above questions along with a live demo of a profiling middleware ( customizable-django-profiler ) which is used to track down the function calls associated with an API call taking more time for execution. Contents of the talk: Introduction : Introduction to middleware. Middleware architecture : I will talk about the middleware architectural design. It\u2019s basics and various use cases Implementation of middleware in Django : Explain how the request-response cycle works along with targeting above mentioned questions on the go. Live demo : I will demo the development of a simple custom middleware which can be used for profiling requests. Conclusion : Possible use cases for Django middlewares. Q & A session : Questions and answers session. In the end, the audience will have an understanding of Django middleware stack, middleware architecture, request-response cycle in Django and will be able to develop their own middleware for Django from scratch", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics of Python and Djang", - "Section": "Web development", - "Speaker Info": "I am recently graduated from IIT Roorkee. I have been working on web applications (especially Django for more than 3 years now). Selected for Google Summer of Code this year and working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API . My areas of interest are Web Applications, Artificial Intelligence and Computational Biology", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", + { + "Content URLs": "https://games.renpy.org/category/rpg https://www.renpy.org", + "Description": "Ren'Py is one of the most versatile and easy-to-use frameworks, written in Python, for the development of Visual Novels and smaller Role-playing games. The talk will explore the details about creating your own development environment for development of visual novels, writing a script and developing GUI, porting your game to Android and iOS and how you can get help for issues in development process. The talk will also explore some of the games which have been developed in Ren'Py like Katawa Shoujo, Doki Doki Literature Club, Imre's Curse: The Prologue etc. The talk will be an interactive one and have a very light and humorous note", + "Last Updated": "15 May, 2018", + "Prerequisites": "No prerequisites required. An open mind and familiarity with Python is all what is needed to attend the talk", + "Section": "Others", + "Speaker Info": "I am currently involved with Lernr Project, a startup based in Ahmedabad and have been working with Python for 3+ years, certified as a\nSoftware Carpentry Instructor and one of the organizers of Django Girls Bangalore. Contributor to Biopython, Galaxy Project, bioconda and conda-forge communities. My interests are in the field of Bioinformatics, High-Performance Computing and am working under Prof. V.K. Jayaraman in the field of Proteomics", "Target Audience": "Beginner", "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-django-middleware-stack-with-a-live-demo~e1qme/", - "title": "Understanding Django middleware stack with a live demo" + "author": "Sourav Singh (~sourav)", + "created_on": "15 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/make-your-own-visual-novel-in-renpy~b2JAb/", + "title": "Make your own Visual Novel in Ren'Py" }, - "38": { - "Description": "Data proliferation is putting pressures on business leaders to become data-driven. Although, leaders have to rely on data analysts to run those queries and get insights out from data warehouses. Its a common principle-agent problem wherein data analysts only ask questions from data which they are directed to ask, but its never a one-way street. One has to flirt with data for a long time to get to know it and leaders get stuck in the loop of data analyst direction as leaders are not equipped with or don't have time to write SQL queries. This calls for a natural language query wherein a business leader can ask a question in simple plain English and data is spitting out either in a table or graph. This session is guided towards how Innovaccer has solved this problem and provides an architecture, knowledge base building, and natural language processing guidance to build one on your own. The session will also emphasize on the fact that accuracy of such a software will be very poor if it is industry agnostic as SalesForce and ThoughtSpot have tried in the past. Thus, one has to tame it to their own business context or vertical", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics knowledge on natural language processing, not even how to code it, but what are its basic components. https://www.nltk.org", + { + "Description": " Understanding Neural Networking using NumPy Implementing CNN using Keras & understanding foundations Using Pretrained models. Transfer training for doing dog breed identification", + "Last Updated": "15 May, 2018", + "Prerequisites": " Python Basics NumPy Machine Learning Basics", "Section": "Data science", - "Speaker Info": "Kanav Hasija is Co-Founder and Chief Product Officer at Innovaccer. He has developed a healthcare data platform with his team which helps connect to various healthcare IT systems to get a longitudinal view of the patient record and turn it into analytical insights on risk, cost, and utilization behaviour of patient to act on them and treat them before they get sick to reduce the cost of healthcare. The platform today has more than 10 million lives on the platform and an estimated $1 Billion has been saved till date in US healthcare costs while keeping people healthy with a quality of care bump of 15%. He is a coder and mathematics enthusiast since the age of 10, completed his bachelor in engineering from IIT Kharagpur and pursued higher studies in Intellectual Property Law from UNH Law in the US. He is recipient of various awards like Samsung-Stanford Patent Prize, Honorable Mention for Excellence in Technology, Best Graduate Student Award, and is also an author in a few publications like IEEE. Harshil Rastogi is a software development engineer at Innovaccer. He has worked on various enterprise-grade software components in the fields of data management, data transformation, and natural language processing", - "Speaker Links": "https://www.linkedin.com/in/kanavhasija/ https://www.linkedin.com/in/harshil-rastogi-3a754b65", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kanav Hasija (~kanav)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bringing-analytics-in-hands-of-leaders-natural-language-query-in-python~bYx2a/", - "title": "Bringing analytics in hands of leaders: Natural Language Query in Python" - }, - "39": { - "Content URLs": "Speaker will focus on when and how to use design patterns, rather than what are the design patterns available. Github repository for the talk", - "Description": "Having less time to design software and solving the design problems correctly, to create robust , modular and highly maintainable code is current challenge.\nMight be, you are aware of some of the design patterns but it will never solve your problems until you have deep understanding on the problem and right place to use design pattern. If you think, you need to design a very unique architecture, then may be you are missing powerful available design pattern that can provide you generic solution template. Let's learn ( and become expert), to speed up development process; guessing issues that can come up later development stages and selecting the right design pattern in the right stage of the software development in Python", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Coders and programmers who want to learn about software design and architecture", - "Section": "Others", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/i-would-have-known-this-software-design-techniques-before~eXwgd/", - "title": "I would have known, this software design techniques before.." + "Speaker Info": " 10 + Industry Experience. Machine Learning & Deep Learning Trainer/Consultant for more than 20 companies https://www.linkedin.com/in/awantik/ Co-Founder EdYoda & Zekelabs", + "Speaker Links": "https://www.linkedin.com/in/awantik", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Awantik Das (~awantik)", + "created_on": "15 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-using-python-from-scratch-image-classification~b4KJa/", + "title": "Deep Learning using Python from Scratch - Image Classification" }, - "40": { - "Description": "for students,\nunderstanding data analysis with pandas, using ipython shell or terminal and jupyter notebooks", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "understanding of python scripts", + { + "Content URLs": "https://github.com/sdonapar/data_analysis_pytho", + "Description": "Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data. Data Visualisation helps to get hidden insights quickly . Data Visualisation is key for summarising and communicating your insights. This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis and visualisation Following will be covered as part of this session How does data analysis fit in the life cycle of data science project Dealing with numpy arrays - quick overview Reading data using various formats and sources Data scrubbing/cleansing - dealing with missing values, data transformation Introduction to data visualisation and quick overview of libraries available Using visualisation to understand and communicate results Analysing one of the open source data set By the end of the session Audience will have very good understanding of how to apply numpy, pandas to analyse, visualise understand and communicate the results Scrub/Cleanse the data and prepare data set required for machine learning", + "Last Updated": "16 May, 2018", + "Prerequisites": "Hands on exposure with basic python programming language Software requirements: Please install Anaconda ( https://www.anaconda.com/download/) with Python 3.6 Download the git hub repo - https://github.com/sdonapar/data_analysis_pythonwe would be using jupyter notebooks for this worksho", "Section": "Data science", - "Speaker Info": "I'm a 3rd year B.tech(information science) student from Bangalore, Karnataka", - "Speaker Links": "https://github.com/pandyamaru", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marut Pandya (~pandyamarut)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-with-pandas~bWvxa/", - "title": "Data analysis with Pandas" + "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company. I have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delh", + "Speaker Links": "github link - https://github.com/sdonapar linkedin profile - https://www.linkedin.com/in/sasidonaparthi twitter handle - @sdonapa", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Sasidhar Donaparthi (~sasidhar)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-visualisation-using-python~e50Xd/", + "title": "Data Analysis & Visualisation using Python" }, - "41": { - "Content URLs": "Will be updated soon", - "Description": "Talk Summary :- Recently, there is a boom in concept of face recognition system with the introduction of Face ID by Apple in their iPhone X mobile phones. This was also incorporated by OnePlus for their mobile phones too. The most notable use of this technology is at Baidu, an internet company, are using face recognition instead of ID cards to allow their employees to enter their offices. Another place where this technology is prominently seen is in auto photo and video tagging feature of Facebook. In this talk we will build a Facial Recognition program using python library \u201cface_recognition\u201d and then we will dive deep in the behind the scenes action of this library and will try to build a One Shot Learning face recognition model using PyTorch. We will be implementing a Siamese neural network on AT&T Laboratories Cambridge dataset. We will also cover the basics of this neural network, triple loss function and and will discuss the reason for choosing this architecture. I will explain how the network models a relation between two images and relates them. Outcome of this Talk :- Attendees will be able to possess the power to implement state of the art Facial Recognition program in a few minutes. They will also get to know how facial recognition works when we have very small dataset. They will be able to make a state of the art One Shot Learning face recognition based on Siamese Network (the working force of face_recognition and implementation of Google\u2019s FaceNet). Agenda :- Introduction to Face Recognition [2 mins] Introduction of python library \u201cface_recognition\u201d [1 min] Building a face recognition program using \u201cface_recognition\u201d library\n (possible live demo of the output) [6 min] How \u201cface_recognition\u201d encodes faces [2 min] Introduction of Triplet Loss and Siamese Network and reason to choose one shot learning (which is used to\n encode faces) [5 min] Implementation of Siamese Network using PyTorch on AT&T Laboratories\n Cambridge dataset and its results [10 min] Q&A Session [3 min]", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basic Knowledge of Machine Learning and Neural Networks Love for Pytho", + { + "Description": "You only look once (YOLO) is a state-of-the-art, real-time object detection algorithm. The model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image. It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. This makes it extremely very fast. This talk teaches you to develop your own real-time object detection python application to detect and classify objects in images as well as videos in real-time, which you can use in your next self driving car", + "Last Updated": "16 May, 2018", + "Prerequisites": " Knowledge of basic Python and its syntax Idea/Overview of deep learning as a technology", "Section": "Data science", - "Speaker Info": "Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", - "Speaker Links": "Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", + "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune. I'm currently working in HSBC Technology India, as a software developer. I am also a decent artist, and love to play the piano in my free time", + "Speaker Links": " LinkedIn Twitter Recent talk on WebVR", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Saurabh Ghanekar (~saurabh29)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-state-of-the-art-facial-recognition~eVrXe/", - "title": "Understanding State of the Art Facial Recognition" + "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-object-detection-coz-yolo~b6VNb/", + "title": "Real-time object detection coz YOLO!" }, - "42": { - "Content URLs": "Github repository links will be updated soon", - "Description": "In this talk, I am going to talk about advanced concepts of Python related to Caching. A cache can be easily understood as a saved answer to a question. Caching can speed up an application if a computationally complex question is asked frequently. Instead of the computing the answer over and over, we can use the previously cached answer. Caching is an important component while scaling applications which are to be used by many users. It solves various problems related to cost and latency. Usually it takes more time to retrieve data from DB rather than cache. Using a cache to avoid recomputing data or accessing a slow database provides us with a great performance boost. I will describe in depth the different methods of Caching, their pros and cons. This talk will help developers focus on their code before scaling their applications. It will provide immense performance improvements with this simple concept. Outcomes: The novice audience will be able to understand basic Caching Mechanisms. They will be able to utiilize their knowledge which will serve pivotal while scaling applications Contents to be covered in talk: Local Caching: What is it, how to do it, example, built-in Python libraries: (using cachetools ), advantages, dis-advantages Memoization: What is it, pseudo-code algorithm, implementation using example, built-in Python libraries: (using lru_cache ), advantages, dis-advantages Distributed Caching: What is it, techniques: (using memcached , using pymemcache ) Agenda: Initial 10 minutes: Introduction to Caching and its various techniques. 10 - 20 minutes: Examples and code walk through for various techniques. 20 - 25 minutes: Comparative analysis of how caching is better than non-scaled applications. 25 - 30 minutes: Q&A session", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + { + "Description": "The human voice is becoming an increasingly important way of interacting with devices, but current state of the art solutions are proprietary and strive for user lock-in. Mozilla\u2019s DeepSpeech and Common Voice projects are there to change this. In contrast to classic STT approaches, DeepSpeech features a modern end-to-end deep learning solution. Based on Baidu's Deep Speech research paper, it trains a model by machine learning techniques. This model directly translates raw audio data into text - without any domain specific code in between. To train systems like DeepSpeech, an extremely large amount of voice data is required. Most of the data used by large companies isn\u2019t available to the majority of people. That's why Mozilla launched Common Voice, a project to help make voice recognition open to everyone", + "Last Updated": "16 May, 2018", + "Section": "Data science", + "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune, and a Mozilla TechSpeaker. I am also a decent artist, and love to play the piano in my free time", + "Speaker Links": "Mozilla Research machine learning home page: https://research.mozilla.org/machine-learning/ Speaker's LinedIn: https://www.linkedin.com/in/shaguftagurmukhdas/ Speaker's twitter: https://twitter.com/shaguftamethwa", "Target Audience": "Beginner", "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-caching-in-python~aQm9a/", - "title": "Understanding Caching in Python" + "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mozillas-deepspeech-and-common-voice-projects~e7JBd/", + "title": "Mozilla's DeepSpeech and Common Voice projects" }, - "43": { - "Content URLs": "Will be updated soon", - "Description": "Talk Summary: Bitcoin has become so mainstream these days. It unveiled the importance of decentralization. But how does Bitcoin work? It\u2019s because of its core technology called Blockchain. After the Internet, Blockchain technology is regarded as the next big revolution. This talk gives a hands-on demonstration of how Blockchain technology works by building a toy version from scratch. Outcomes: After this talk the audience should be able to understand the basic working principles of bitcoin. They will be able to leverage their knowledge as a starting point of open-source contributions to projects like Ethereum. This demonstration will consider three important features of Blockchain Technology. All these features are essential to blockchain technology and we will be building a minimal version in Python. Agenda: 0 - 5 mins:\n Blockchains are secure because they use SHA256 or SHA512 algorithm for cryptography. I will describe the logic behind these hashing algorithms and give some computational facts about them. 5 - 10 mins: \n I will use the Python library called \u2018hashlib\u2019 to implement the SHA256 algorithm in Python. This makes us to convert data into SHA256 hashes. 10 - 15 mins:\n The SHA256 algorithm is used to convert all the transactions and their details into a single hash. Once the everything is converted into a hash, this hash must be stored for future usage. After a new transaction is approved, this new transaction and its details are again converted into a new hash along with the previous hash. I will demonstrate the process of storing the hash and using it again for a new transaction. 15 - 20 mins:\n Here I will explain a basic working principle of blockchains and how linking the previous transactions with the new one helps in the their security. The hashes stored are called blocks and the process of liking the previous hash the new hash makes a chain like connection thus forming a Hyperledger. 20 - 25 mins:\n Later in the process of mining will be explained using the variable quantity called Nonce. This explains why bitcoin miners need high computation power to do Proof-of-Work. \nI will also cover a variety of essential terms and concepts through the course of the talk which haven\u2019t been detailed in the agenda. Also, I will use python module called 'TkInter' to build a basic GUI for our blockchain. Last 5 mins:\n Questions and further reading + code sharin", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Love for Python and acquaintance with its libraries", - "Section": "Core python and Standard library", - "Speaker Info": "I am Koushik, a Computer Science sophomore whose research interests lie in decentralization and cryptocurrencies, occasionally working on deep learning projects. As a member of the Next Tech Lab, a QS-Wharton award-winning student-run lab, I work in the Satoshi research group for blockchain technology. I also regularly participate and give talks in paper-reading groups and meetups like PyData", - "Speaker Links": "Visit my profile on LinkedI", + { + "Content URLs": "OpenFaas Docs: https://docs.openfaas.com/ OpenFaas Website: https://www.openfaas.com", + "Description": "OpenFaaS makes Serverless Functions simple with any programming language through the use of Docker containers. The project can be hosted on any cloud, or on your own hardware - even your laptop. Learn how to build Serverless functions with OpenFaaS and Python in this self-paced workshop lead by the community behind the project. Start by deploying OpenFaaS to your laptops with Docker for Mac or Windows and then learn how to build, deploy and invoke serverless functions in Python. Topics will include: Managing dependencies with pip, dealing with API tokens through secure secrets, monitoring functions with Prometheus, invoking functions asynchronously and chaining functions together to create applications. We'll finish by building a custom action for Google Home/Google Assistant for managing slack notifications using Google's DialogFlow and Slack API. The workshop will have the following labs: Prepare for OpenFaas Test things out Introduction to functions Go Deeper with functions HTML for your functions Asynchronous functions Advanced feature - Timeouts Advanced feature - Auto Scaling Advanced feature - Secrets Create a Slack bot using DialogFlow, Slack API and OpenFaaS", + "Last Updated": "16 May, 2018", + "Prerequisites": " Basic knowledge of Docker Functions will be written in Python, so prior programming or scripting experience is preferred. Requirements: We can use - https://labs.play-with-docker.com/ or any VM / box with the latest docker installed", + "Section": "Web development", + "Speaker Info": "Vivek Singh: Currently working as Software Engineer - II at Akamai Technologies. Been an active contributor to OpenFaaS project. Co-organizer and Speaker at OpenFaaS Bangalore meetup group . Loves to code in Python and Golang. Contributes to Open Source projects in free time. Vivek Sridhar: Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", + "Speaker Links": "Vivek Singh: Contributions: https://github.com/viveksyngh LinkedIn Profile: https://www.linkedin.com/in/viveksyngh/ Twitter: https://twitter.com/viveksyngh Website: https://www.viveksyngh.info Blog: https://www.viveksyngh.info/blog/ Vivek Sridhar: https://www.linkedin.com/in/vivsridh https://twitter.com/vivek_sridhar https://github.com/vivsridh4 https://hasgeek.tv/rootconf/2018-day-2/1509-distributed-tracing-with-jaeger-at-scale https://hasgeek.tv/rootconf/cloud-sever-management-delhi/1435-auto-remediation-at-scale-using-watchers-vivek-sridha", "Target Audience": "Beginner", - "Type": "Talks", - "author": "KOUSHIK BHARGAV M M Srinivas (~koushik_bhargav_m)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchains-from-scratch~dPl4d/", - "title": "Understanding blockchains from scratch!" + "Type": "Workshops", + "author": "Vivek Kumar Singh (~viveksyngh)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-serverless-with-openfaas-and-python~e9Xzd/", + "title": "Hands-On Serverless with OpenFaaS and Python" }, - "44": { - "Description": "With examples build the concept of creating a language model using text data", - "Last Updated": "19 Jun, 2018", - "Section": "Data science", + { + "Description": "DevOps is gaining momentum and we at Microsoft want our users to have great CI/CD story for any language targeting any platform. In this session, we will be talking about how easy is to get started on Cloud and DevOps for Python developer in this new generation of Microsoft We're going to start from scratch and before we're done we will use Visual Studio Team Services (VSTS) to setup Continuous Delivery for Python Applications on Cloud and demonstrate the DevOps strategy in action. The solution grows up to the most demanding needs of a modern software developers powered by VSTS. Whether you are starting new, bringing your own tool chain or inter-operating with existing tools and assets, you can accelerate your delivery of value with Azure and VSTS", + "Last Updated": "16 May, 2018", + "Prerequisites": "N", + "Section": "Developer tools and Automation", + "Speaker Info": "Alok Agrawal is Product Manager for Microsoft Visual Studio Team Services where he and his team are building next generation cloud based developer tools. He has been with Microsoft for over 7 years. Previously he has worked with Windows Application Compatibility and Azure Application team. Alok has Bachelor's degree in Computer Science and completed his business management from IIM Calcutta", + "Speaker Links": "http://www.imalokagrawal.com https://twitter.com/imalokagrawal https://github.com/imalokagrawa", "Target Audience": "Intermediate", "Type": "Talks", - "author": "divya chowdhary (~divya69)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~aOkra/", - "title": "Language Model (Text Analysis) using Python from scratch" + "author": "Alok Agrawal (~imalokagrawal)", + "created_on": "16 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-plumber-building-deployment-pipeline-in-minutes~e03Nd/", + "title": "Becoming a Plumber: Building deployment pipeline in minutes" }, - "45": { - "Description": "Abstract: Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. The Big Question: \"Is everything Perfect in AWS Lambda?\" .... Well it depends on how you use it and this is what I will cover in my Talk. Note: This Talk will have some code references using PYTHON Outline: What will you learn from this session/talk: What are Lambda Functions . What are the different features of Lambda Functions. The famous Lambda Timeout . The Deployment and Resource Limits . The Cold Start issue and its workarounds. The Cost Factor Why do you need to know this: Helps develop decision making in the project design architecture The Case Study: Case Study in which you should/should not use Lambda Functions. Real Life project experience: The hidden learning with an on job project on the limitations to Lambda Function. Q&A ", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Python: Basics of Serverless Computing Basic of Python Programming Basics of Python Libraries Usages (Imports)", - "Section": "Others", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Ritu Mehra (~ritu86)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-lambda-with-python-dos-and-donts~dNjvd/", - "title": "AWS Lambda with Python : Do's and Dont's" - }, - "46": { - "Content URLs": "https://docs.openstack.org/infra/jenkins-job-builder", - "Description": "Jenkins job builder is an openstack project used for automation and reusing of templates in yaml and json to make jobs and subscribe them to Jenkins. People who like to save time on tedious details can use this open source software and live there life a little better", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Jenkins( a little bit )\nPython\nPip\nRelated libraries like PyYAML, Jinja etc", - "Section": "Developer tools and Automation", + { + "Content URLs": " http://haridas.in https://github.com/haridas", + "Description": "Data-science mainly involves understanding your data and identify suitable models based on the data. Mastering the standard tools like pandas and seaborn will be key to gain insights about ML problems. This tutorial coverers, Basics of pandas and seaborn Different plotting patterns using seaborn for your data. Plotting Single and bivariate distributions, categorical plots with distribution. Understand two variable behaviour using regression plots. One usecase:- How I decided to buy a petrol car instead of diesel car by analysing my fuel spending.", + "Last Updated": "17 May, 2018", + "Prerequisites": "Lapatop with following packages installed. pip install seaborn pand", + "Section": "Data science", + "Speaker Info": "Haridas is a Principal Engineer in Pramati Technologies, part of Labs team. He has 8+ years of experience in multiple domains like, Web development, SOA, ML, Devops. He has been working extensively in different ML use-cases and applying them in real scenarios", + "Speaker Links": " http://haridas.in Twitter @haridas_n", "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jenkins-job-builder-automating-jobs~aMgGd/", - "title": "Jenkins job builder - automating jobs" + "Type": "Workshops", + "author": "haridas n (~haridas)", + "created_on": "17 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/find-patterns-in-your-data-using-seaborn-and-pandas~ejJ4e/", + "title": "Find patterns in your data using Seaborn and Pandas" }, - "47": { - "Content URLs": "Coming soon", - "Description": "Do you know, your favorite superheroes in Avengers , cute characters of Kung Fu Panda and the epic wars of Baahubali were brought to screen with the help of python ? If you are into gaming , you need to thank python for the characters you have played and the world you have explored. Even the next generation technologies like AR and VR use python to deliver their magic to you in new formats. It won't be a overstatement if we say python is the backbone of the animation Industry In this talk we go behind the scenes and see how our favorite programming language is used in the animation industry, why it plays a huge role and the kind of applications built with it", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "A bit of curiosity and interest in learning about usage of python in various industries, usually less represented in the python community", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", + { + "Content URLs": "Shall be updated soon", + "Description": "You have got this super awesome REST API served through Django/DRF based project and suddenly these requirements come in: We need to have a local support for Chinese language! In case, you've not written your application with localization and internationalization in mind, then \"Boy! You're in danger! You should better start praying to almighty to give you strength and endurance to support yet another language in your app\". In this talk, we'll see how do we support localization and serve our app in different languages, based on what language the client wants to communicate in. As a backend, we should be language agnostic and allow all clients to communicate with us in one of the languages we support. We'll see how to support translation for static data (using makemessages / compilemessages) and dynamic data, using various third-party services such as django-translations and transifex. Here, static data is translations for all the fields, error messages etc. that the app already has and dynamic data is the custom data input by the user in the app. This would enable you to have your admin panel, as well as RESTful APIs, served in different languages", + "Last Updated": "18 May, 2018", + "Prerequisites": "Basic knowledge of Python and Django", + "Section": "Web development", + "Speaker Info": "Why do you want this person to speak? Sanyam is a self-taught programmer with a \"can-do\" attitude who developed his interest in Computer Science and Software Development over the years. He mostly goes by CuriousLearner all over the web and you might run into him at various Python Conferences and local meetups. In his free time he contributes to FOSS. Some of his noticeable contributions are in Gecko Engine from Mozilla and CPython. You can read about his latest hacking CPython and other projects at http://www.SanyamKhurana.com/blog & http://medium.com/@CuriousLearner Highlights : Goes by CuriousLearner all over the web. Bug Triager and contributor to CPython (bugs.python.org) GSoC 2018 Mentor for Debian RGSoC 2016 Mentor Mozilla Reps Mentor and contributor to Mozilla's GeckoEngine, Add-ons ecosystem, and other few projects. Core-organizer for PyCon India 2016 & PyCon India 2017 Volunteer for PyCon India 2015.", + "Speaker Links": "Blog: http://www.SanyamKhurana.com/blog Website: http://www.SanyamKhurana.com Github: https://github.com/CuriousLearne", "Target Audience": "Beginner", "Type": "Talks", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/amazing-world-of-animation-powered-by-python~dLDrd/", - "title": "Amazing world of animation - powered by python" - }, - "48": { - "Content URLs": "Coming Soo", - "Description": "It's really hard to escape the 3D buzzword. You find it used in all sorts of places, right from the movies you watch, Games you play, 3D printing , webgl graphics in the browser and VR , AR applications. In this workshop we are going to cover the basics of 3D and do a hands on session on creating 3D Art using a professional open source application called Blender . Of course, python is a major part of blender and we will put your python skills to some good use. What is this workshop NOT about : This is not one of your boring programming workshops. We are not going to try improve your python knowledge ten folds in a matter of 2 hours. What is this workshop about : Come to this workshop if you want to be a kid again and have fun creating art in 3D using Blender and Python !!! Who am I : Hello, Sreenivas here! I am a 3D artist turned programmer. I work in the animation and VFX Industry and battle production issues with the power of python. I love art, technology and excited about combining both. I support open source by evangelizing Blender and Krita . Who are you : You are a person with an open mind, bitten by the curiosity bug and intrigued by how 3D Art is made. You have at least basic knowledge of python and ready to use your super powers to create 3D Art. Takeaway : By the end of the session\u2026 You will know a broad overview of 3D Art . Have a working knowledge of the professional open source 3D application, Blender . Get a deeper understanding of the workflow for creating 3D art. Use your python skills in the process of creating 3D Art.", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Laptop with a decent GPU (any modern laptop) A mouse with a middle click button (scroll which is clickable) Download and install Blender from https://www.blender.org/download/", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3d-art-using-blender-and-python~aKBxe/", - "title": "Creating 3D Art using Blender and Python" + "author": "Sanyam Khurana (~CuriousLearner)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-multilingual-superhero-in-django~bkMve/", + "title": "Becoming a Multilingual SuperHero in Django" }, - "49": { - "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. \nThe website for the workshop at PyCon India 2015 is here . \nYou can find the introduction slides here , the sphinx tutorial here and the exercises in form of IPython notebooks. Note: that the notebooks are hosted statically, you can download from here and run locally to have an interactive session", - "Description": "SymPy is a Python library for symbolic mathematics. It aims to be an alternative to systems such as Mathematica or Maple while keeping the code as simple as possible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.\nThe talk will highlight the following: SymPy, what it is and how it is different from others. What is symbolic computation and how SymPy achieves it. Power of SymPy: Symbolic manipulations Equation solving Calculus Linear Algebra ", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Basic mathematics, just enough to appreciate the manipulation done by the computer algebra system and Python. No prior knowledge of SymPy or other Python libraries is required", - "Section": "Data science", - "Speaker Info": "SymPy India developers will be conducting the talk: Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers module", - "Speaker Links": " Resource repository: https://github.com/sidhantnagpal/pycon-sympy SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://www.youtube.com/watch?v=5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://www.youtube.com/watch?v=nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://www.youtube.com/watch?v=AqnpuGbM6-Q SymPy Tutorial, SciPy 2014: https://www.youtube.com/watch?v=Lgp442bibDM SymPy Tutorial, SciPy 2013: https://www.youtube.com/watch?v=dAgShwIx72c", + { + "Description": "Sometimes it can be a laborious task for developers to build android apps using Java. Though Java supports Android apps in a powerful way but it also increases the code complexity for a high end app. Now, if you are a python enthusiast and also want to develop Android apps then Kivy comes to your rescue. Kivy is an open source python library for rapid development of cross platform apps. Using the Kv design language and the Kivy framework for Python, you can build amazing interactive multi-touch apps in just a matter of minutes. Kivy framework solves the complexity problem any android developer face while writing complex codes. It also serves the advantage of being cross platform which saves a great amount of time for any app developer. If you love Python, you will also love Kivy", + "Last Updated": "18 May, 2018", + "Prerequisites": "Python Basic Knowledge of Androi", + "Section": "Web development", + "Speaker Info": "The speaker goes by the name amanraj209 all over the web. I've been interested in learning new technologies since high school and I've been developing apps using Python, Javascript, Java, Go since the last 3 years. I've also done some small projects in Machine Learning. Being a developer gives me a great sense of feel to build apps for the users and contribute to the community. It has always been my passion to dive into the technology and contribute to the community something useful", + "Speaker Links": "Github: https://github.com/amanraj209 LinkedIn: https://www.linkedin.com/in/amanraj209 Facebook: https://www.facebook.com/amanraj20", "Target Audience": "Beginner", "Type": "Talks", - "author": "Yathartha Joshi (~Yathartha22)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-sympy~dGxJe/", - "title": "Symbolic Computation with SymPy" + "author": "Aman Raj (~amanraj209)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/developing-android-apps-using-kivy~el61b/", + "title": "Developing Android apps using Kivy" }, - "50": { - "Content URLs": "Will share the Slides post my Talk through a proper channel", - "Description": "Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. Note: In this workshop all the implementation will be done using PYTHON Session Takeaways: How to use different features of AWS to create your Serverless Application. What is Serverless Computing and how \"Functions as a Service\" is a revolutionary way to develop applications. Understand AWS Lambda Functions, the FaaS offering on Amazon Web Services. Understanding of the AWS services - Lambda, S3, EC2, CloudWatch, API Gateway, RDS, IAM How to access the AWS services using Python libraries in the Lambda Function. Hands On Cloud Native Web Applications Development using AWS Lambda and other offering. Practical examples of how you can combine multiple services and events in AWS and develop applications rapidly using AWS Lambda Functions", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Python: Basic of Python Programming Basics of Python Libraries Usages (Imports) AWS Free Tier account - https://portal.aws.amazon.com/billing/signup?redirect_url=https%3A%2F%2Faws.amazon.com%2Fregistration-confirmation#/start", - "Section": "Web development", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", + { + "Content URLs": "Coming up soon (related to this workshop", + "Description": "Convolution Networks - Framework = Vision in vanilla python. This workshop aims at providing the attendees an experience of implementing convolution neural from scratch without any big framework working in the backend supplementing the need for computation. This would give the attendees an overall understanding of what are Convolution Neural Networks and why do they work so exceedingly well! One does not simply code in vanilla python. What can you expect from this workshop! You'll understand what are convolution neural networks Why they work so well on image data? All the different implementation of Convolution network and how they improve the vanilla network What are the best ways to implement convolution network on a given data What this workshop is not! Just another workshop telling you to use frameworks Maths will not be looked over. (It's important) This workshop is not any other university lecture where you'll not understand anything. I find this image to be so apt given all the abstraction provided by frameworks", + "Last Updated": "18 May, 2018", + "Prerequisites": " Command over Python Familiarity with Numpy and basic math packages Intermediate Mathematics Familiarity with algorithms common in machine learning", + "Section": "Data science", + "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a deep learning enthusiast who loves mathematics and astronomy. I've been exploring machine learning/deep learning for about 2 years now and fiddling with the basic mathematics and scratch implementations always excite me. I'm currently mentor of deep learning in a Delhi based startup Greatech Soft Solutions and interning at Startup labs and a Google Summer of Code '18 student under the organization OpenAstronomy", + "Speaker Links": " http://prsr.me https://www.linkedin.com/in/prakharcode https://github.com/prakharcode", "Target Audience": "Intermediate", "Type": "Workshops", - "author": "Ritu Mehra (~ritu86)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/serverless-application-development-using-aws-and-python~eEvga/", - "title": "Serverless Application Development using AWS and Python" + "author": "prakhar srivastava (~prakhar91)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/convolution-neural-networks-without-any-frameworks~bmX3a/", + "title": "Convolution Neural Networks without any frameworks" }, - "51": { - "Content URLs": "https://docs.google.com/presentation/d/1_hyRLHdITpIMzhAbpxuaTQkm6qop4ZWQt6ERGW4MFag/edit?usp=drivesdk&ouid=10471550379351873801", - "Description": "This is a simple talk about web scraping using python.In this lecture we going to have a clear picture of webscraping. \nBy the end of the lecture audience are going to have a clear picture of \nWhat is web scraping? \nWhat is the use of it? \nWhat are the useful libraries in python for web scraping? \nPros and cons of the libraries\nAnd mainly how to parse the Websites with practical examples", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "A little amount of python knowledge is useful but not mandatory. I'm going to explain right from the very beginnin", + { + "Content URLs": " https://docs.julialang.org/en/release-0.4/ https://julialang.org/ Ppt (soon)", + "Description": "Julia Programming Language The Julia programming language is proving to be a new paradigm shift in the data science community due to it's easy to pick up syntax like python but and execution speed equivalent to C , this is possible due to flexible types and JIT compiler. The speed and user-friendliness are only some of its good parts. This talk delves deeper into understanding, how can Julia be the next language on your learning list. Outcomes of the talk What is Julia? How can I get it into my daily workflow What Julia offers that Python does not Understanding benefits of shifting to Julia How can a python-ista shift to Julia", + "Last Updated": "18 May, 2018", + "Prerequisites": " Laptop with Julia up and running", "Section": "Others", - "Speaker Info": "I am a student of Vishnu Institute of technology, Bhimavaram. I am studying 2nd IT. I was fallen in love with coding when I listened to the 1st lecture of my academic about C programming. That day changed my life. I have been working on python from January 2018.\nI am a quick learner, self disciplined, self motivated guy. \nMy hobbies are coding and learning new thing", - "Speaker Links": "https://www.sololearn.com/Profile/495149", + "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a recently born Julia-n, I do a lot of code in Julia and move back and forth from Julia to Python to C. I'm a deep learning practitioner and loves Astronomy. I recently got selected into Google Summer of Code under OpenAstronomy org and my project's fundamental language is Julia. I'm a computer science by day and dancer by night. Currently, I'm fiddling with Julia and it's awesomeness and I'll offer you nothing less than awesome", + "Speaker Links": " http://prsr.me https://linkedin.com/in/prakharcode https://github.com/prakharcode", "Target Audience": "Beginner", "Type": "Talks", - "author": "Deepak Puppala (~deepak12)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping~bDrKe/", - "title": "WebScraping" + "author": "prakhar srivastava (~prakhar91)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/julia-an-upgrade-to-python-programming-language~enJpe/", + "title": "Julia. An upgrade to Python Programming Language" }, - "52": { - "Content URLs": " Hydra Draft Hydra Ecosystem Wiki Hydrus Hydra Flock Demo Hydra CG homepage I'll be sharing my slides after the talk", - "Description": "Building Web APIs seems still more an art than a science. How can we build APIs such that generic clients can easily use them? And how do we build those clients? Current APIs heavily rely on out-of-band information such as human-readable documentation and API-specific SDKs. However, this only allows for very simple and brittle clients that are hardcoded against specific APIs. Hydra, in contrast, is a set of technologies that allow us to design APIs in a different manner, in a way that enables smarter clients. The main aim of this talk is to provide an overview of Semantic Web, Hydra Draft, and Hydrus. Hydra - Hydra is a framework to enable REST API to be described semantically using RDF. It is based on JSON-LD and proposed as W3C draft . Hydrus - Hydrus is a Flask server meant to build and deploy Hydra-based Web APIs in a straightforward and effective way. Hydrus utilises the power of Linked Data to create a powerful REST APIs to serve data. Hydrus uses the Hydra draft standard for creation and documentation of it's APIs. The flow of the talk will be as follows: My Introduction Brief Overview of Semantic Web and JSON-LD What is Hydra Draft? Detailed introduction to Hydrus How can we use Hydrus to create REST APIs easily? Future Scope An interactive Semantic Web demo. Q/A session", - "Last Updated": "18 Jun, 2018", - "Prerequisites": " Python Basic knowledge of APIs and Web", - "Section": "Web development", - "Speaker Info": "My name is Akshay Dahiya. I'm a Mentor and Organization Admin for Python Hydra in Google Summer of Code 2018 and I love working on Semantic Web and AI related projects. \nRecently, I have been learning through Udacity, adding more structure to my education on Web Technologies, Machine Learning, Deep Learning and Software development in general. I also mentor students across various Udacity Nanodegree programs (FullStack Nanodegree, React Nanodegree and Deep Learning Nanodegree) in my free time", - "Speaker Links": " http://www.xadahiya.me/ https://github.com/xadahiya/ https://www.linkedin.com/in/xadahiya/ http://www.typingeek.com/", + { + "Content URLs": "Slides: https://speakerdeck.com/satwikkansal/do-you-really-think-you-know-strings-in-python Also relevant: https://github.com/pydelhi/talks/issues/77 Most of the snippets and concepts to be discussed are taken from various resources I came across during my 6 months long research about Python. I have collected such snippets in a project called \"What the f*ck Python!\". Here's the source: https://github.com/satwikkansal/wtfpytho", + "Description": "Do you know that, 'a'[0][0][0][0][0] is a semantically valid statement in Python. print(r\"\\ some string\") is a valid statement, but print(r\"\\ some string \\\") raises a SyntaxError . print('wtfpython''') is valid but print(\"wtfpython\"\"\") raises SyntaxError . Do you know why, >>> a = \"some_string\"\n>>> id(a)\n140420665652016\n>>> id(\"some\" + \"_\" + \"string\")\n140420665652016 the id of both the objects in above snippet is same? And do you know why, >>> timeit.timeit(\"s1 = s1 + s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.25748300552368164\n# using \"+=\", three strings:\n>>> timeit.timeit(\"s1 += s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.012188911437988281 s1 = s1 + s2 + s3 is much slower than s1 += s2 + s3 . And finally, >>> 'a' * 20 is 'aaaaaaaaaaaaaaaaaaaa'\nTrue\n>>> 'a' * 21 is 'aaaaaaaaaaaaaaaaaaaaa'\nFalse\n\n# one last attack!\n>>> a = \"wtf\"\n>>> b = \"wtf\"\n>>> a is b\nTrue\n\n>>> a = \"wtf!\"\n>>> b = \"wtf!\"\n>>> a is b\nFalse\n\n>>> a, b = \"wtf!\", \"wtf!\"\n>>> a is b\nTrue Do you know the reason behind all the above-discussed facts and snippets? Some of them are really puzzling, right? I felt the same when I first came across all these intricacies. But don't worry, such behaviors, are mostly the consequences of strings being [immutable] [sequences] in Python. In this talk we'll be going through the concepts behind such snippets in detail, so that next time when you see such examples, the answer seems natural to you. Finally, we'll try to answer some interesting questions like, How does string concatenation work? What's the best way of building large strings in Python? (It may actually depend on your use-case) What happens when you multiply a string by a boolean? How strings in Python differ from strings in other languages like JavaScript, C++? and many more", + "Last Updated": "18 May, 2018", + "Prerequisites": "Basic familiarity with programming. Prior experience with Python would make the talk more interesting for the attendee", + "Section": "Core python and Standard library", + "Speaker Info": "I'm a Software Developer experienced with Decentralized Applications and Data Science. In my leisure time, I love doing pointless things with programming. Currently on a quest to learn as much as I could about Computer Science. And lastly, I prefer all things Python! (A humble brag ", + "Speaker Links": "Website | Github | Archives Past Speaking Experience PyCon India 2017 (Speaker for a DevSprint ) EuroPython 2017 ( Invited as a Speaker for a workshop , unable to attend though) IWD-Delhi 2018 ( Speaker ) PyDelhi biweekly meetup (Gave a small talk ) OSS DTU (Instructor and moderator)", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Akshay Dahiya (~xadahiya)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3rd-generation-web-apis-using-hydra-and-hydrus~dBpYa/", - "title": "Creating 3rd Generation Web APIs using Hydra and Hydrus" + "author": "Satwik Kansal (~satwik)", + "created_on": "18 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/do-you-really-think-you-know-strings-in-python~boJLa/", + "title": "Do you really think you know strings in Python?" }, - "53": { - "Content URLs": "A library for ANTLR that is being built by me is available here: https://gitlab.com/virresh/coala-antlr ANTLR's official page: http://www.antlr.org/ My blogs related to ANTLR in Python: https://virresh.wordpress.com/tag/antlr/ An example calculator: https://github.com/virresh/ANTLR4-Exampl", - "Description": "This talk aims at introducing ANTLR for python 3, and talk about Abstract Syntax Trees. It will present an overview of the process, the intricacies and will end with a concrete example to show the utility. ANTLRv4 is a tool that can generate parse trees for any compatible grammar, and provide tools to walk through that tree, so I will illustrate how to use that rather than dwelling more on the theory aspect of the parse trees and boost up the development of language tools. There is a speciality with ANTLRv4, we can separate context from the grammar (so we can get very close to the expectation that grammars are context free). I expect the session to be beginner friendly so no pre-requisites save some basic python expected. Also I will cover some basic examples, and also a demo of an actual language grammar to create a meta-program if time permits. The session is expected to have the following things: What is a grammar ? What are Parse trees and how do they compare to ASTs ? What is ANTLR ? (The parser generator and the runtime provided) How do we use a parse tree ? (dwelling on setting up the environment for ANTLR based development and a short, basic calculator building example) Visitors and Listeners A short real world example on detecting technical constricts in actual programming languages (probably Python itself)", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "A working knowledge of python basics and some familiarity with some sort of command line interface is ideal (best suited if you are familiar with any unix/linux based systems, simple script invocation etc", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm a student presently pursuing BTech in CSE at IIIT-Delhi, and am a GSoC student this year at coala.io and have been programming various stuff using python for around two years. I am developing a library to facilitate easy usage of ANTLR for building linting tools. I've worked on a large array of technologies in any area that I get to know about, ranging from Full stack development, to Systems programming to Language tools. I do my best to pick up and experiment with whatever technologies I can, and I love to learn ", - "Speaker Links": "GitHub: https://github.com/virresh Website: https://virresh.github.io/ Blogs: https://virresh.wordpress.com/ LinkedIn: https://www.linkedin.com/in/virresh", - "Target Audience": "Beginner", + { + "Content URLs": ">>> import thi", + "Description": "Tim Peters preached and we memorized that Explicit is better than implicit, but how many understood the deeper meaning enough to imbibe the essence of the zen? In this 20 min talk, we shall go through the zen and look at live examples where the golden words make a programmer's life easy", + "Last Updated": "19 May, 2018", + "Prerequisites": "Familiarity with the syntax of Python", + "Section": "Core python and Standard library", + "Speaker Info": "Anuvrat has spent countless hours wading through utterly un-pythonic, non-modular codebases that contain > 8000 lines in one file and >500 in one function, with nested try-except statements and has almost mastered the skill of keeping his calm and understanding even that", + "Speaker Links": "https://anuvrat.i", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Viresh Gupta (~virresh)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-antlr-with-python~az5ye/", - "title": "Using ANTLR with python" + "author": "Anuvrat Parashar (~bhanuvrat)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-python-with-real-life-examples~epVyb/", + "title": "The Zen Of Python: with real life examples" }, - "54": { - "Description": "We have a word for it now - Domotics . The fun started a year back when I laid hands on this beautiful device from Amazon, which could not only manage your music, reminders, lists but also make calls and send messages. Basically, a smart phone in the cloud to be used without hands. But a developer sees endless possibilities with this powerful tool. Although speech recognition technology itself is nothing new, Amazon Echo has made its way to the homes of regular consumers. This talk is specially focused on giving a head start to the attendees about building and using powerful applications in python using an Alexa device. Being a python developer for the past 10 years and working on alexa skills for the past year, I intend to share my experience with the python community and enthusiasts. Broadly, this talk will be covering the following topics: How the echo framework and Alexa skills work An introduction to creating alexa skills in python with flask-ask Handling requests , responses , contexts and sessions . Testing applications with ngrok and deploying to the cloud. A sneek peek into other home automation possibilities like micropython embedding with popular microprocessors. The talk would be illustration and example driven and will include demos of cool app(s) I have been working on", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "This talk is intended for developers who have a decent grasp on the basics of the python framework and trends, although you do not need knowledge of any specific packages or libraries. Just an enthusiastic mind is enough! The primary takeaway of this talk would be learning how to get started ideating and building applications for an alexa enabled smart home device and discuss some cool developer tips", + { + "Content URLs": "This talk is going to be based on a series of blog posts I have written about the same topic - Python Project Workflows - Part 1 Python Project Workflows - Part 2 (Pipenv) Python Project Workflows - Part 3 (pylint)", + "Description": " Have conflicting dependencies (unpleasantly) surprised you? (Darn: It worked on my laptop!) Do deterministic builds matter? What about those run-time errors, which were a typo while accessing an attribute of a class? Has the codebase already started smelling a bit? Unit tests and what about Dockerization? Typically, when your Python project grows beyond a few modules and your team size is more than a couple of developers, having the right tools built into your project development workflow saves one from a lot of surprises (and perhaps late night calls). In this talk, we start with challenges typically seen in Python Projects and look at ways of overcoming them, so that the velocity of code deployment increases. Specifically we are going to be looking at tools that are out there that allow you to - Properly track dependencies ( pip , virtualenv and the new Pipenv ) Have a separate Dev and Production environment - so that dependencies in Dev environment don't spill into Production environment. Ensure that the builds are deterministic (across developer/build machines and time.) Enforce certain coding guidelines and capture the potential 'run-time' errors right during the development ( pylint ) and Eventually Dockerize your application.", + "Last Updated": "19 May, 2018", + "Prerequisites": "It's an intermediate level talk where you have already done some Python development and are at a point where you want to package, distribute or deploy your pet Project. If you are a beginner in Python, but have been involved in build/release of packages in any other languages, likely this talk is for you. If you do an equivalent of sudo pip install or sudo apt-get install when you want to download and use package foo , chances are you will benefit from this talk quite a bit", "Section": "Developer tools and Automation", - "Speaker Info": "Sonal Raj ( @_sonalraj ) has been an avid pythonista for 10 years. He has been working as an integral part of the financial technology industry for the past 4 years. Sonal holds a masters in Information Technology and has been a research fellow at the Indian Institute of Science, Bangalore. His domains of interest include distributed systems and graph databases, and he loves to explore new gadgets and develop new technology. He is also the author of the best selling book 'Neo4j High Performance' ", - "Speaker Links": " Talk at PyCon India 2014 Talk at PyCon India 2013 Real Time Computation with Apache Storm - IISc Bangalore Human Computer Interaction Systems : Slides Website Github Reasearch Profile", + "Speaker Info": "Running a Consulting Company 'hyphenOs Software Labs' in Pune, India. Python/Go programmer - Mostly for things that pay the bills and ideas that I want to try out. Datacenter Networking Enthusiast (hacking a yet another Container Networking technology, borrowing ideas from different Projects) Eternally grateful to whoever wrote tcpdump and the new Wireshark . Number of problems solved using these tools could run into triple digits. Hates trailing white spaces in a file.", + "Speaker Links": " Stack Overflow Github LinkedIn", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Sonal Raj (~sonal)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/alexa-enabled-smart-home-programming-with-python~dy5nd/", - "title": "Alexa enabled smart home programming with Python" + "author": "Abhijit Gadgil (~gabhijit)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-project-workflows-continuous-deployment-friendly~bq8ya/", + "title": "Python Project Workflows - Continuous Deployment Friendly" }, - "55": { - "Content URLs": "http://github.com/gnsrikanth/simplelinuxbackdoor", - "Description": "In this talk, we discuss how python scripts can be used in the world hacking. Python can be used to automate many tasks and see how we can use network protocols using python. Programming isn't just codes, but it's a way of communication. This talk is more an awareness of the possibilities python can be used and hacking is one of them. We break down steps to hack a system and automate tasks using python. Topics covered: Sockets in python Using TCP, UDP protocols and creating a Server/Client A basic backdoor for windows Using HTTP protocol to steal users data Using encryption to obfuscate network traffic Subprocess module Pyinstaller to make binaries of malware Bypassing antivirus (we will test by uploading exe to virustotal) Using Sqlite3 to retrieve chrome passwords Emailing subprocess outputs with python Send data to google forms as POST Simple Ransomware code Other Python tools for hacking", - "Last Updated": "16 Jun, 2018", - "Prerequisites": "Basics in python, Operating system fundamentals, Networking basics", - "Section": "Networking and Security", - "Speaker Info": "I am Grandhi Srikanth, and truly passionate in cyber security. I hold C|EH, CCNA in Routing and Switching, Cyber Ops certification and interested in creating malware codes and as python makes it simple, I like using python", - "Speaker Links": "Twitter: @gn_srikanth LinkedIn: https://www.linkedin.com/in/grandhi-naga-srikanth/ Blogs: www.thebinarynoob.com Github: https://github.com/gnsrikant", - "Target Audience": "Intermediate", + { + "Content URLs": " https://pytorch.org/docs/stable/index.html Slides (https://slides.com/rahulbaboota/deck)", + "Description": "Talk Abstract This talk aims to introduce Facebook's Deep Learning library - PyTorch. PyTorch is increasing becoming popular due to it's powerful features and shallow learning curve, making it accessible and easy to use to a larger community. This talk discusses about the 'Autograd' package, which is central to all neural networks in PyTorch. It also entails details about the different features and functionalities of PyTorch as well as equip the audience on how to create simple and complex Neural Networks in PyTorch. PyTorch helps to create dynamic computation graphs that allow you to change how the network behaves on the fly unlike static computation graphs. It offers modularity which enhances the ability to debug or see within the network. Outline of the Talk The talk will be broadly divided into 3 broad parts. Part 1 will be an Introduction to PyTorch. This part will focus on the use and need for PyTorch as a deep learning framework. This will be followed by instructions on how to setup PyTorch and a look at the basic building blocks behind the framework. Part 2 will dive more into the features of PyTorch, mainly it's AutoGrad package which lies at the heart of all Neural Networks created in PyTorch and PyTorch's ability to create dynamic computational graphs as opposed to the static computational graphs offered by some of it's counterparts (such as TensorFlow and Caffe). Part 3 will be a more 'hands on' part where the talk will focus on how to create and build simple as well as complex neural networks (such as Convolutional Neural Networks) with the framework", + "Last Updated": "19 May, 2018", + "Prerequisites": " A basic understanding of how Neural Networks work would be beneficial. Some knowledge about Numpy.", + "Section": "Data science", + "Speaker Info": "I am Rahul Baboota, a 3rd Year Undergraduate in India studying Computer Science and Engineering. I have an avid interest in the domain of Data Science, Machine Learning and Deep Learning. I have worked at various Data Science and Machine Learning based startups and labs. In my freshmen year, I worked at a data journalism startup to create and analyze smart data stories. I was also a part of a project funded by the Government of India for the development of a social media based analytics tool for the analysis of healthcare and nutrition in India. I am currently working at the Center for Artificial Intelligence at IIITD in the Autonomous Vehicle Lab 'Swarath'", + "Speaker Links": " https://www.linkedin.com/in/rahulbaboota/ https://github.com/RahulBaboota", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Naga Srikanth Grandhi (~naga_srikanth)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/coding-back-doors-with-python~ax5Bb/", - "title": "Coding Back-doors with Python" + "author": "rahul baboota (~rahul93)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/throwing-light-on-pytorch~er7La/", + "title": "Throwing Light on PyTorch" }, - "56": { - "Content URLs": "Apache_Build_Monitor Jenkins' REST API & Pytho", - "Description": "As a build and release engineer, have you felt how good it would be to know the status of scheduled nightly builds before you reached office ? As a developer, have you wondered, while you were away from the desk, what's the status of quality gate builds that should be passed before the changes can be integrated to the mainline ? Intent of this talk is to outline what's offered via Jenkins's REST API and showcase some of the possibilities by consuming the API using Python", - "Last Updated": "16 Jun, 2018", - "Prerequisites": " Read-up docs on Python libraries XML, JSON Capability to follow and assimilate code snippets", - "Section": "Developer tools and Automation", - "Speaker Info": " Speaker works for a CyberSecurity firm in Bengaluru, India Likes being outdoors and reading books.", - "Speaker Links": "Linkedi", + { + "Content URLs": "(Slides to be uploaded soon", + "Description": "In computer vision, object detection is scanning and searching for an object in an image or a video (which is just sequence of images). Whereas, object tracking is like you are spying on someone and following it. Done in motion images like in animated gifs or videos, we want to track how an object is moving, where is it going, or its speed. Although it has been studied for dozens of years, object detection and tracking remains an open research problem . The difficulty level of this problem highly depends on how you define the object to be detected and tracked. If only a few visual features, such as a specific color, are used as representation of an object, it is fairly easy to identify all pixels with same color as the object. On the other extremity, the face of a specific person, which full of perceptual details and interfering information such as different poses and illumination, is very hard to be accurately detected, recognized and tracked. Thus, I believe it is important to address such challenges via a comparative study of object tracking and object detection in python. Here, I aim to present my own experience in tackling the problems while I tested different algorithms for the same", + "Last Updated": "19 May, 2018", + "Prerequisites": "Basic understanding of pytho", + "Section": "Data science", + "Speaker Info": "Anand Zutshi is currently pursuing his undergraduate B.E. degree from Netaji Subhas Institute Of Technology, Delhi. He has experience in developing and testing basic as well as advanced algorithms in C, C++. He has experience in developing a Learning Management System which uses dynamically trained neural network for scoring its users, and a LDA based tagging in its queries. He has in depth knowledge of Natural Language Processing, mainly with emphasis on word sense disambiguation and language models. His recent work of interest primarily focusses on object detection and object tracking in Python and sound classification and recognition. Currently, he is working on testing a biometric database management system along with predicting self and non-self processes in Operating system using Neural Networks", + "Speaker Links": "https://github.com/zutshianan", "Target Audience": "Beginner", "Type": "Talks", - "author": "Ramanathan Muthaiah (~ramanathan)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/consuming-jenkinss-rest-apis-in-python~dw58a/", - "title": "Consuming Jenkins's REST APIs in Python" + "author": "anand zutshi (~anand09)", + "created_on": "19 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-tracking-vs-object-detection-a-comparative-analysis~avJna/", + "title": "Object tracking vs Object detection- a comparative analysis" }, - "57": { - "Content URLs": " Code will be updated on github very soon.", - "Description": "There are many framework available in the market for free and with a lot\u2019s of feature like Django , Flask , Tornado . These framework help us to build web application and serving the files over the network without worrying about the low level details like how it works , how the files are being severed to the clients , web browser and how it handles the clients to be connected and serving the data to the lot\u2019s of clients with minimum amount of time with managed thread. So in this talk I\u2019ll share my knowledge how does the web server work and how we can build our own framework like other available framework and further enhance it , to make it big, and to handle the clients with multiple processes and threads. In this talk I will be talking about : What is a WebFramework and How does a web framework work? How we can make a simple web sever to serve the \u201chello world\u201d webpage to the browser How we can make the HTTP custom request header to tell the browser about the current status of request on the different situation like 200 , 404 , 500. how to server files like html, css to generate the advance webpages using socket to the browser. Getting the requested URL Params and serving the files over the network. Making a Download link and let the user to download the files over socket. Improvement of request and response time of the web server and optimising it so that the web server can handle more and more clients over the network. ", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "1. Basic python understanding. 2. Python installed on your system. 3 .Socket library (you can install it using the pip installer", - "Section": "Core python and Standard library", - "Speaker Info": "I am Nawneet Kumar, CTO at Elezire Technologies Pvt. Ltd. I have worked in Different Projects and in Different Languages in my past year. I have worked in era like IOT Development , Android Application Development , IOS Development and Web Development", - "Speaker Links": "Linkedin : https://www.linkedin.com/in/nawneet-kumar-77b64814b/ github : https://github.com/navSharma4", - "Target Audience": "Beginner", + { + "Content URLs": " https://github.com/rahulkumaran/Telegram-Syntaxdb-bot There will be some slides that I'll prepare too but most of it is going to be an explanation from the GitHub repo and my talk https://github.com/python-telegram-bot/python-telegram-bot https://syntaxdb.com https://syntaxdb.com/api/v1 https://core.telegram.org/api", + "Description": "In this particular topic, I'll basically be telling people about how easy it is to create a Telegram Bot. The reason I'm interested in taking this up is because there are people who develop beautiful things and might want to let people to use it even on a mobile interface. The problem is not everyone's good with app development. So in such cases, deploying the beautiful things in the form of a bot would be a great idea. Bots can be of 2 types : Conversational Command based I'll be taking up the command based bot to help people get a feeling of this topic. Also, through the example I'll be giving, I'll try to make people understand as to what APIs are and how to use existing one. Later I'll show them how to create your own Python APIs because APIs make lives easier for programmers and it's always a good practise to know how to create an API as you never know when someone else might need it. CONTENTS AND ORDER OF THE TALK I'll be starting off with an introduction about myself and then I'll move on to what are bots. I'll then be explaining about why we could probably use these bots on Telegram, Discord, Slack and so on. Thereafter I'll be talking about the Telegram API for Python to help you interact with the bot and telling you how to use it. Before this, I'll show them how to prepare a bot on Telegram and get the Token. After this, I'll be talking about the importance of an API and utilizing existing ones as it makes your job much simpler. Slowly, I'll shift my focus on to how to build an API. I'll be explaining this using an example. Then using the Telegram Bot API and the API we build for Syntaxdb.com, we'll be creating a Telegram bot. Lastly, I'll summarise and entire talk and will take up a couple of questions. The entire talk will be based on a GitHub repository. The code links will be given to everyone for future reference", + "Last Updated": "20 May, 2018", + "Prerequisites": " Basic Python Usage of libraries in Python", + "Section": "Others", + "Speaker Info": "The speaker, in this case is me, Rahul Arulkumaran . I'm an engineering undergrad currently going into my 3rd year. I'm also the Founder of the startup Free Flow . We still haven't registered it yet though. I started learning how to code when I came into engineering and Python was the first language I learnt. I never really developed anything until last year. It was after creating my first application that I got the interest to develop more using Python. From then to now, I've learnt a lot. I might not be an expert but yes, for my age, I think I'm better than most others. I'm also the President of the Computer Science Club, Enigma in my college Mahindra Ecole Centrale . I'm a Python developer and an open source enthusiast . I also am a Contributing and Managing member of PSF . I work on a lot of open source projects I love learning anything and everything related to coding. I'm also a Machine Learning and Data Science enthusiast ", + "Speaker Links": " https://rahulkumaran.github.io https://github.com/rahulkumaran https://www.linkedin.com/in/rahul-arulkumaran-101a63127", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "nav.sharma47", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-own-webframework-like-django-flask-tornado-to-serve-web-application-using-core-socket-programming~av55e/", - "title": "Building Own WebFramework like Django , Flask , Tornado to serve Web Application using Core Socket Programming" + "author": "Rahul Arulkumaran (~rahulkumaran)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-and-working-with-apis-to-develop-a-telegram-bot~dwgXd/", + "title": "Creating and working with APIs to develop a Telegram Bot" }, - "58": { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/welch/seasonal Example Slides: https://www.slideshare.net/CheukTingHo/pydata-amsterdam-2018-time-series-analysis-with-seasonal-data-9909335", - "Description": "For time series analysis, everyone\u2019s talking about ARIMA or Holt-Winters. But there\u2019s other models which could also break down a seasonal series into trend, seasonality and noise. We will use an open source Python library called Seasonal to analyse B2B worldwide travel data. Times series analysis is an important part of data analysis for lots of businesses. It is very often for stakeholders to be interested in the performance of the business by analyzing measurements of profit, cost, number of sale, number of searches etc over time. In this talk, we will do a case study of showing how we estimate the impact public holidays made on the travel business. The method of analyzing the time series by seasonal breakdown will be explored and the work flow of solving the problem will be explained. In the first half of the talk, an introduction about time series and its characteristic will be explained for audiences who is new to analysis on time series. The data we use will be from a business to business travel company. It has seasonality thought out the year, a weekly cycle and also a growing trend in business. As the company have clients around the world, data from different countries will shows different behaviors as well. Therefore, before we show the analysis, the complexity of the data will be explored. In the second half, we will introduce a open source Python library called Seasonal. Using this package, we will demonstrate how to break down the travel data and extract the fluctuation of the sale in different countries. By comparing the fluctuation and Google calendar, public holidays in different countries can be spotted and their impact on the business can be estimated. This talk is for people who are interested in time series analysis and its application in business. Audiences with or without experience would also found this talk useful in giving them insights in how a business could benefit in making use of the data and doing a proper time series analysis", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", + { + "Content URLs": "Repository for the content", + "Description": "Orbital Mechanics/Astrodynamics is one of the most difficult things to understand and take care of! For this simple reason it is called \"Rocket Science\". poliastro is a python package intended to make Astrodynamics Open Source, and easy to understand and visualise. Through the talk, various modules of the poliastro package will be introduced. I will show how we can solve very complex Orbital Mechanics problem in 2 minutes that takes years for a scientist to solve manually! The talk will cover some parts of AstroPy, numba and a bunch of plotting libraries such as matplotlib and plotly", + "Last Updated": "09 May, 2018", + "Prerequisites": "Basic introduction to plotly , matplotlib . Knowledge of some core packages like numpy, etc is beneficial. Knowledge of some of the core Astronomy libraries such as AstroPy is also beneficial", "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", + "Speaker Info": "I am Shreyas Bapat, half \"Electrical Engineer\" and a passionate developer. I study at Indian Institute of Technology Mandi and constantly contribute to open-source projects. I have contributed to some projects like plotly, dash, poliastro and astroquery. I like Astronomy and related fields a lot and hence keep searching for projects related to that. Also, I am into Deep Learning from quite a time and love tweaking Neural Networks to get amazing results. I am the co-ordinator and maintainer at STAC-IITMandi . I have mentored the Astronomy Code Camp organised by Nehru Planetarium and Astronomical Society of India", + "Speaker Links": "GitHub Profile : shreyasbapat My Website: shreyasb.com My Portfolio: Click here Find my contibutions in Poliastro at #4 : https://github.com/poliastro/poliastro/graphs/contributor", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-time-series-analysis-with-seasonal-data~er5pd/", - "title": "Case Study in Travel Business - Time Series Analysis with Seasonal Data" + "author": "Shreyas Bapat (~shreyasbapat)", + "created_on": "09 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/through-python-to-the-stars-orbital-mechanics-made-easy-and-open-source~dGK5d/", + "title": "Through Python to the Stars! - Orbital Mechanics Made Easy and Open-Source" }, - "59": { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/networkx/networkx Slides (not finalized): https://docs.google.com/presentation/d/1y_Wmuv_hqs8OZTI8XLJ5ajvjEpllK7Xeifa52yTpw-k/edit?usp=sharin", - "Description": "When you make a search for a hotel room, do you know how many travel agents are searching for you at the same time? In this talk, we demonstrate how to use the millions of searches a sourcing company received to build a network of travel agents and finding the main hubs among them using NetworkX. Network analysis is getting more and more attention in Business Intelligence, people hope to get information out of the structure of an organization or a communication network. In this talk, we use the hotel room search requests from travel agents, including online public website, B2C, B2B and B2B2C, to build a relational network among them. By using this network as an example, we demonstrate how insights can be extract by studying network properties. In the first half of the talk, we will explain how the network is built using NetworkX, an open-source python library that is designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. When 2 agents are making the same search at the same time , a link ( or an \u201cedge\u201d in network analysts terms) is made pointing form the initial searcher to the subsequent searcher. Using a list of these searches, a directed graph is built. We will also demonstrate how to pick the biggest connected component out form the graph. In the second half, with the graphs created, we show how different functions of NetworkX can be used to study the graphs. By compare the graph properties of our graph to the other popular network graphs, we can get the insight of how the network was created. Also by studying the graphs, we can understand the behavior of the agents and can even figure out which agents are acting as main hubs in the network. This talk is for people who are interested in network analysis and would like to see how it can be used in a business case. Audiences with any level of python experience can learn some basic concept of network analysis work and how it can be applied to provide business insights", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + { + "Content URLs": "Few resources that I will be using in the workshop. https://github.com/koshikraj/proof-of-ownership https://github.com/koshikraj/neo-python-contracts https://github.com/koshikraj/neo-ico-template", + "Description": "Bitcoin has been gaining popularity in the recent years due to its market value. But more importantly, the underlying technology is gaining the attention among the developers. Many developer communities inspired by bitcoin have created their own platform to use the underlying technology widely known as \"blockchain\" to achieve decentralization. Ethereum is one such platform that has created a blockchain platform which allows developers to develop their own decentralized applications (dApps) in the ethereum network by coding the logic in the execulatable contracts called \"smart contracts\" . Although ethereum has gained a huge fame due to its smart contract implementation to create decentralized applications, it imposes developer to write the logic in an ethereum's domain-specific language called Solidity. In addition to coding in a new language, it mandates the developer to set up a new develop environment. NEO blockchain platform provides a convenient way to develop smart contracts in general purpose programming language. NEO achieves this by providing compilers to compile code written in most of the languages to bytecode that can be executed in NEO virtual machine. Currently, NEO allows compilation of python smart contracts through neo-python project. This is the first blockchain project to provide such a freedom to the developer. NEO project provides plenty of benefits over other blockchain platforms out there. \nIt plans to achieve smart economy by creating a strong digital identity. It achieves faster transaction rate which is the key to scale any platform. NEO is being referred to as the \"New Ethereum\" due to its increasing popularity. I plan on conducting a workshop to create a decentralized application by developing and deploying smart contract using neo-python. Following would be the agenda of the workshop. Introduction to Bitcoin, Blockchain, and consensus to achieve decentralization. (30 mins) Introduction to NEO and Setting up a NEO platform (30 mins) Creating and deploying Hello World contract using Python (15 mins) Creating a Proof of Ownership system (30 mins) Creating a user interface to create a complete Proof of Ownership DApp. (20 mins) Creating an Initial Coin Offering (ICO) using an existing template and Q&A (25 mins) ** This is a rough estimation of time and topics as of now. I will try to fit more topics if possible. An attendee will be able to create an asset management DApp such as document ownership system or launch a basic ICO after attending the workshop", + "Last Updated": "20 May, 2018", + "Prerequisites": " Novice level experience in python programming. Basic knowledge of how bitcoin or blockchain technology is\n implemented would help to grasp the topic pretty well. Although I will be using Ubuntu Linux distribution for the demo, Attendees can use any platform which has python 3.6 installed. Windows users might have to install a docker container manager as installation might create some issues.", + "Section": "Networking and Security", + "Speaker Info": " I completed my masters in Computer science and Information Security after getting fascinated by the security and cryptography field. I have a demonstrated history of working in the computer and network security industry (RSA Security) where I had worked for more than a year. I worked as a senior fullstack developer for a start-up called CoWrks. In the meantime, I got involved in the blockchain and decentralized application. I started devoting my entire time to blockchain and I'm currently writing a research book on the blockchain technology called Foundations of Blockchain", + "Speaker Links": " My Linkedin profile. Few of my opensource contributions. My semi active social profile. Check out my detailed bio at koshikraj.com", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Koshik Raj (~koshikraj)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-decentralized-smart-contracts-using-python~egXra/", + "title": "Creating decentralized smart contracts using Python" + }, + { + "Content URLs": " I'll be sharing the slides after my talk as a Github repository", + "Description": "Abstract In this talk, I would be telling people how to write better and faster Python. I've been developing Python programs, scripts and softwares for over 2 years now and I come across people who have a problem of Python being slow. \nWhenever someone has to write a faster python code they are left with one option of just shifting their entire code from Python to C or C++. This talk will clear that misconception. People can actually write faster codes in Python, the only missing fact is how? . And this is exactly why I am interested to give this talk. Contents of the talk The talk will start with a basic introduction of myself as a Python developer. I will then talk about the misconception about shifting the code to C or C++. Then I will proceed onto some basic usage of Python Programming Language. Introduction to optimization techniques in Python. Then I will talk about when and why should one optimize their application. I will introduce the basic concepts of optimization in Python. Tell people about the available/built-in functions that can come in handy. Then I will proceed onto giving a demonstration on 'Writing better functions'. The talk will conclude with some examples of optimized code that performs better than conventional approaches. The talk will be open to questions, to make it more interactive and fun. The slides will be shared to the audience after the talk", + "Last Updated": "20 May, 2018", + "Prerequisites": " Basic Python Will to learn See, It does not require much", + "Section": "Core python and Standard library", + "Speaker Info": "My name is Manish Devgan . I am a second year Information Technology student at Netaji Subhas Institute of Technology, Delhi . I am an Open Source Contributor and a learner . I have contributed to various different open source projects and won many hackathons . I was FOSSASIA Codeheat 2017 - Grand Prize Winner and Google Code-In 2017- Mentor . Currently I am a GSoC 2018 Student under FOSSASIA and RGSoC 2018 - Coach . I have contributed to Python's ChatterBot Machine Learning Engine , variety of FOSSASIA's Projects , and a wide variety of OSS projects like Github Linguist etc. Python is my favourite programming language . From writing small scripts to building small Machine Learning libraries , I've tried a lot :", + "Speaker Links": " https://github.com/gabru-md https://twitter.com/gabru_md https://facebook.com/gabrumd https://www.linkedin.com/in/gabru-md/", "Target Audience": "Beginner", "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-understanding-agent-connections-using-networkx~bq5pb/", - "title": "Case Study in Travel Business - Understanding agent connections using NetworkX" + "author": "Manish Devgan (~gabru-md)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-faster-python-optimizing-your-code~ejJye/", + "title": "Writing Faster Python : Optimizing your code" }, - "60": { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/seatgeek/fuzzywuzzy Source code available on Github: https://github.com/Cheukting/fuzzy-match-company-name Slides (not finalized): http://slides.com/cheukting_ho/fuzzy-matchin", - "Description": "Ever encounter a tricky situation of knowing there\u2019s names that are the same, but matching strings straight away leads you no where? All you need is FuzzyWuzzy, a simple but powerful open-source Python library and some wit. This talk will demonstrate how to efficiently fuzzy match company names. Matching strings should be one of the first natural language processing problem that human encounter since we start use computer to handle data. Unlike numerical value which has an exact logic to compare them, it is very hard to say how alike two strings are for a computer. One may compare them character by character and have an idea of how many characters in the pair of stings are the same. Unfortunately in most application we need computer to perceive strings like we do and therefore we have to use fuzzy matching. Fuzzy matching on names is never straight forward though, the definition of how \u201cdifference\u201d of two names are really depends case by case. For example with restaurant names, matching of words like \u201ccafe\u201d \u201cbar\u201d and \u201crestaurant\u201d are consider less valuable then matching of some other less common words. Also, do we consider company names that matches partly (like \u201cHappy Unicorn company\u201d and Happy Unicorn co.\u201d) are the same? In the first half of the talk Levenshtein Distance, a measure of the similarity between two strings, will be explained. Different functions in FuzzyWuzzy like \u201cpartial_ratio\u201d and \u201ctoken_sort_ratio\u201d will also be explored and compared for difference. It is very important to understand our tool and choose the right one for our task. Then in the second half, we will start tackling the example problem: matching company names, we will show that besides using FuzzyWuzzy, we have to also handle problem like finding and avoid matching of common words and speeding up the matching process by grouping the names. By combining all tricks and techniques that we demonstrate, we will also evaluate how efficient this method is and the advantage of using this method. This talk is for people in all level of Python experience who would like to learn a trick or two and would like to be able to solve similar problems in the future. Theory of how the library works will be explained and It is easy to be pick up even for beginners", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + { + "Content URLs": " Slides on Introduction to NLP : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction%20to%20NLP%20%26%20Spacy.pdf Jupyter Notebook : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction.ipynb Note : The above slides are not complete and are suited for a quick introduction to NLP in 20 mins I will be introducing the following Libraries (and use them to create chatbots) NLTK : https://www.nltk.org/ SpaCy : https://spacy.io/ I will be developing a bot on the following Chat Platforms with emphasis on Messenger: Messenger : https://developers.facebook.com/docs/messenger-platform/ Slack : https://api.slack.com/ Telegram : https://core.telegram.org/bots", + "Description": "Introduction to NLP Natural Language Processing is a prominent field in Artificial Intelligence that deals with parsing and understand Natural language, (an ordinary language such as English is any language that has evolved naturally in humans through use). NLP lies at the core of Google Duplex and other smart assistants that respond to questions in English and natural languages. I will be explaining the following : Corpus and Datasets Processing and tokenizing Text Tagging, Stemming and Lemmatizing Words WordNet Introduction to libraries NLTK Spacy Sentiment Analysis Word Embedding using BOW and word2vec Developing Chatbots With rising need for customer support, Chatbot are one of the most common applications of NLP. These are applications that are trained conversation with a human by answering some preset list of questions. I will be developing a chatbot on three platforms : Messenger (Facebook) Slack Telegram These will be deployed locally using Django with ngrok for tunneling. Additionally, due to the immense popularity of Messenger, I'll be also explaining the different message templates and other features that Messenger has. If you'd like to see me cover another platform such as Discord, Skype, Google Assistant or Alexa, feel free to drop a commen", + "Last Updated": "20 May, 2018", + "Prerequisites": "Basic knowledge of Python, English Grammar and HTTP Requests", + "Section": "Others", + "Speaker Info": "About me Hello world. I\u2019m Vishal Gupta, a 3rd yr CSE undergrad at SSN, Chennai, India. \nWhile most people generally pick up a topic, or a concept (like say Computer Vision, Big Data, or just Algorithms), understand it and aspire to excel at it\u2026 I fell in love with a language, Python. As someone who has started out by learning C++ in school, learning Python was as easy as surprising. The speed at which I could translate ideas to code was amazing, and oh boy, all I wanted to do was make things, write simple scripts to automate everyday tasks. And hence I continued to explore Python, the countless modules and possibilities with Python. I went to Hackathons, won some but more importantly made something that others could use. Chatbots and me UI/UX has never been my strong suit but Chatbots made it simple to use serve any application in a conversational manner. Over the last 2 years, I have developed over a dozen chatbot for a variety of purposes, from fetching torrent links to code education to keeping track of events. One of my best messenger chatbots is still functional with nearly ~500 subscriptions. PyGeon , scrapes a number of sites everyday for developer events such as meetups, hackathons and contests in 7 indian cities. Newly added events are sent to users every day. Experience : Chatbot intern at GoBumpr , Chennai CV intern at XR Labs , Chennai NLP intern at BicycleAI Google Summer of Code participant with Debian", + "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fuzzy-matching-smart-way-of-finding-similar-names-using-fuzzywuzzy~epKVd/", - "title": "Fuzzy Matching - Smart Way of Finding Similar Names Using FuzzyWuzzy" + "Type": "Workshops", + "author": "Vishal Gupta (~vishal11)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-nlp-and-chatbots~bkMJe/", + "title": "Introduction to NLP and Chatbots" }, - "61": { - "Content URLs": "Project source code on Github: https://github.com/Cheukting/GCP-GPU-Jupyter Demo code: https://github.com/Cheukting/jupyter-cloud-demo Example slides: https://www.slideshare.net/CheukTingHo/pycon-israel-launch-jupyter-to-the-clou", - "Description": "There are lots of reasons using a cloud service is favorable, but how to make sure consistency between development and deployment? With Docker and Terraform, we can create the same environment on cloud easily. For example, we will deploy a Jupyter notebook on Google Cloud Platform using both tools. In this talk, we will use a task: hiring a GPU on Google Cloud Platform to train neural network, as an example to show how an application can be deployed on a cloud platform with Docker and Terraform. The goal is to have Jupyter Notebook running in an environment with Tensorflow (GPU version) and other libraries installed on a Google Compute Engine. First we will briefly explain what is Docker and what is Terraform for audiences who has no experience in either or both of them. Some basic concepts of both tools will also be covered. After that, we will walk-through each steps of the work flow, which includes designing and building a Docker image, setting up a pipeline on Github and Docker Hub, writing the Terrafrom code and the start up script, launching an instance. From that, audiences will have an idea of how both tools can be use together to deploy an app onto a cloud platform and what advantages each tool can bring in the process. This talk is for people with no experience in application deployment on cloud service but would benefit form computational reproducibility and cloud service, potentially data scientists/ analysts or tech practitioners who didn\u2019t have a software developing background. We will use an example that is simple but useful in data science to demonstrate basic usage of Docker and Terraform which would be beneficial to beginners who would like to simplify their work flow with those tools", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Developer tools and Automation", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + { + "Content URLs": "I will post presentation and Relevant codes soon on github. For reference please find the code here :\nhttp://magneplane.readthedocs.io/en/latest/index.htm", + "Description": "Content of My talk will have : Hyperloop : An Introduction How Python plays an Important role? Python Applications in the Project: Project Management, \nScripting the repeating processes, \nPython - ML in CFD, \nRaspberry Pi in Communications.", + "Last Updated": "20 May, 2018", + "Prerequisites": "An intermediate level knowledge of Python Knowledge of a Python and basic Math", + "Section": "Others", + "Speaker Info": "Suyash Singh is post graduate Student of Indian Institute of Technology, Madras Chennai. He is Head of Team Avishkar Hyperloop More Details about Avishkar Hyperloop : http://avishkarhyperloop.com/ He carries 4 years of work experience in Big Data and Data Science. Later his interest in fifth mode of transportation took him to IIT Madras. He has been pure pythonist. He has been a adviser to two small scale startups based out of Indore which deals with data science. He has a vision of transforming Transportation making it more efficient. He thinks Python will be an important tool to make it possible", + "Speaker Links": "LinkedIn Profile: https://linkedin.com/in/suyashao", "Target Audience": "Beginner", "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/launch-jupyter-to-the-cloud-an-example-of-using-docker-and-terraform~boKXb/", - "title": "Launch Jupyter to the Cloud: an example of using Docker and Terraform" + "author": "Suyash Singh (~suyash_singh)", + "created_on": "20 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hyperloop-how-python-helps-building-fifth-mode-of-transportation~el6jb/", + "title": "Hyperloop : How Python helps Building fifth mode of Transportation?" }, - "62": { - "Content URLs": "Source code available on Github: https://github.com/Cheukting/Style-mimicking-text-generator Example slides: https://slides.com/cheukting_ho/pylondinium1", - "Description": "Computers are getting closer to speak like humans. But can we even make them speak in particular ways, like as Trump or Shakespeare? In this hands on talk we will see how this is possible with the latest deep learning techniques combined with word embeddings and other advanced NLP technique. In this talk, first we would introduce two neural network and machine learning mechanisms which in popular and widely used in NLP (natural language processing): Word Embeddings and Recurrent Neural Network. Word Embeddings is a way to extract the context of a word by \u201clearning\u201d its presence in a paragraph; while Recurrent Neural Network, including LSTM (long short-term-memory), enable us to \u201ctrain\u201d sequential data. After that, we will showcase how to implement these mechanisms in a neutral network. With that, we can \u201cbuild\u201d a machine to generate articles, plays or speeches in the style of the training corpus and have lots of fun. In the first half of the talk, concepts of how Word Embeddings and LSTM works will be explained. Audiences will understand why this is essential in the field of NLP and why we are using it. In the second half, a code demo will be used to showcase how to implement these mechanisms. Through an example, audiences will learn how Keras is used together with Tensorflow and Python to build a sequential neutral network. We will showcase generating a paragraph using Shakespeare\u2019s play and another one using Trump\u2019s speech. This talk is for people who have some experience with data science and understand the concept of how a neural network works, but would like to go deeper into the details of how does it applied to NLP to solve more complex AI problems. We used very simple code but did a complex task like text generation, that opens the door for a lot of people who wants to experiment with deep learning", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "Basic concepts of Neural Network like Stochastic Gradient Descent and back propagation, as it will not be covered in the talk due to time limit", + { + "Content URLs": "https://github.com/atulsinghphd/NL", + "Description": "In this hands-on course using Python, we will learn how to use machine learning for Natural Language Processing (NLP) through interactive notebooks. Natural Language Processing (NLP) is a field that covers computer understanding and manipulation of human language. Machine learning is a branch of Artificial Intelligence that focuses on the ability to automatically learn from existing information. Language processing uses models that attempt to understand and represent the information at various levels that includes morphology, syntax, semantics, pragmatics and discourse. In this training, we will learn how to use machine learning to build these models. This training includes the following topics: Representing text as a vector using count, TF-IDF and co-occurrence matrix Detecting similar documents Sentiment Analysis Identifying the themes in a set of documents Extracting the entities and the relationship between the entities (stretch goal depending on time) The course will introduce the participants to NLP libraries such as nltk, gensim and Spacy", + "Last Updated": "21 May, 2018", + "Prerequisites": "This is an advanced machine learning course. To benefit from this course the participants are expected to have:\n1. Understanding of supervised and unsupervised machine learning \n2. Knowledge of python, or a high-level programming language like Java or C#.\n3. Using jupyter Python notebook environmen", "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Speaker Info": "Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), geo-spatial analytics, and reinforcement learning. Sasidhar Donaparthi I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company", + "Speaker Links": "Linkedin Profiles https://www.linkedin.com/in/sasidonaparthi https://www.linkedin.com/in/atulsinghphd/ Twitter Profiles @sdonapa", "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-keras-building-an-ai-that-talks-like-shakespeare-or-trump~enX7b/", - "title": "Deep Learning with Keras : Building an AI that Talks like Shakespeare or Trump" + "Type": "Workshops", + "author": "Atul Singh (~atul98)", + "created_on": "21 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deciphering-human-language-using-machine-learning~bm0Ra/", + "title": "Deciphering human language using Machine Learning" }, - "63": { - "Content URLs": " Hello world of chatbots world - wordbot An Experiment with Opensource chatbot engine - RASA NLU ", - "Description": "Google Assistant and Siris\u2019 of the world have tickled our curiosity enough to deep dive and understand under the hood technologies that make a chatbot. Though we don\u2019t have Google level of data to create a generalized chatbot, we can use the existing NLP engines and create chatbots that produce valuable results in a specific domain. For eg., anything that goes in your FAQ page can be converted into content for a chatbot. In this talk, I\u2019ll share my 2-year journey with chatbots. Existing bot platforms and how to leverage it to build your own chatbots and connect it with messaging platforms like slack, telegram etc., \nI\u2019ll also share my experience from my experiment on trying to build your own NLP engine. Key Takeaways Chatbot\u2019s architecture Natural language Processing, Understanding, and Generation what and how it plays an important role in building chatbots How to use existing chatbot engines to build a chatbot How to connect chatbots to Slack, FB Messenger etc., How to build your own chatbot engine", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of Pytho", + { + "Description": "In this talk the main aim is to demystify data science and introduce the audience with the concepts of data science and machine learning in python. Goals : What is Data Science ? What is Machine Learning ? Why Python for Data Science ? How to solve a Real world problem with data science ?", + "Last Updated": "21 May, 2018", + "Prerequisites": "No Prerequisite", "Section": "Data science", - "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape - Tech Enthusiast - Django & Chatbot specialist - Mentor/Speaker Build2learn , Chennai Geeks. Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", - "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavan", + "Speaker Info": "Jatin Ahuja is a self taught data scientist and machine learning practitioner. He's currently working in Data Science domain . He's the core team member (designated as PR Director) and city ambassador of AI Saturdays which is a community of over 5000+ students(over 100+ cities) to spread the knowledge of AI free of cost. He actively blogs about machine learning in his personal blog site named as everythingai . He mentors the aspirants in their journey to become a successful data scientist , machine learning engineer or deep learning engineer at MentorCruise.com ", + "Speaker Links": " Website ; https://everythingai.co.in Github : https://github.com/A-Jatin LinkedIn : https://linkedin.com/in/jatin-ahuja-89677614a/ ", "Target Audience": "Beginner", "Type": "Talks", - "author": "Bhavani Ravi (~bhavaniravi)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatbots-101-peeping-under-the-hood~bm6Gd/", - "title": "Chatbots 101 - Peeping under the hood" + "author": "JATIN AHUJA (~jatin)", + "created_on": "21 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-science-with-python~enm5d/", + "title": "Data Science with python" }, - "64": { - "Content URLs": "GitHub Repo: https://github.com/sleebapaul/gospel_of_rnn.git Google Colab Notebook: https://drive.google.com/file/d/1qh94MdQr9SeTLxGkMJc6kZGguRID8LqW/view?usp=sharing Blog: https://sleebapaul.github.io/rnn-tutorial", - "Description": "Language modeling was a complex task of previous days. But advancements in Deep Learning has solved this problem very effectively. Using many to one architecture of Recurrent Neural Networks, I've built a language model which can effectively generate the fifth gospel of bible by learning from four existing gospels. This model is also able to divide verses and chapters along with meaningful passages", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Recurrent Neural Networks basics Deep learning basics Language modeling basics Familiarization with PyTorch", + { + "Content URLs": "wikipedia article on the brain computer interface Text Summarizer neural network model code is in the following lin", + "Description": "Brain Mapping Using Python: Over the past few years, machine learning and artificial intelligence has been making headlines and advancing quickly by creating products that can make optimistic decisions. Now this machine learning technology can be implemented in making a machine which can perform complex actions just like in brain which can make human life easier. Now the real challenge is can we create a neural network model which can perform complex\nactions like human brain? How Python can be used to accomplish this task and how far we can achieve this feat?\nThis talk will be focusing on the methods approached by brain to generate conclusions or make decisions which can be replicated in computers and generate results. Contents of the talk About me - Basic introduction of myself. What is Brain Mapping? Functionalities of Human Brain. Neural Networks Using Python. Types of Data Summarisation techniques in Python. How Computers can make decisions. What can we expect from Brain Mapping in future.", + "Last Updated": "21 May, 2018", + "Prerequisites": " basic syntax knowledge of python basic machine learning terminology neural network models functionality", "Section": "Data science", - "Speaker Info": "Sleeba Paul is a Power System graduate and published researcher who loves intelligent machines. He currently works as a Machine Learning Engineer at Refly; an AI startup in India where he works on content enhancement and video analytics", - "Speaker Links": "Personal website: http://sleebapaul.github.io/ LinkedIn: https://www.linkedin.com/in/sleebapaul/ Github: https://github.com/sleebapau", + "Speaker Info": " ROHITH PUDARI Rohith is a B Tech student who is passionate about integrating the most complex organ known to human which is brain with computers. He is winner of the Hyderabad best coder championship conducted by JNTUH. He is one of the few persons in India who is selected for the google Udacity scholarship. He is always interested in decreasing the interaction gap between computers and humans and started his research in creating an interface which will allow humans to interact with computers in a more natural way. He created a neural network model which generates a summary of a given essay which won the title \"Best innovative idea\" at IIT Kanpur", + "Speaker Links": "you can see the projects and previous work of Rohith in the following link to his github profile. and linkedIn profile Rohith contributed to the following open source projects: Atom- open source code Editor OpenWISP- software platform that implements a complete Wi-Fi service Sugar Labs- desktop environment and learning platform Sustainable Computing Research Group (SCoRe)", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Sleeba Paul (~sleeba)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gospel-of-lstm-how-i-wrote-5th-gospel-of-bible-using-lstms~elLMe/", - "title": "Gospel of LSTM : How I wrote 5th Gospel of Bible using LSTMs" + "author": "dvlpr_rohith", + "created_on": "21 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/brain-mapping-with-python~bonYa/", + "title": "Brain Mapping with Python" }, - "65": { - "Content URLs": " Research Paper Github repository of project with over 80 stars: pyCAIR Beta release on PyPI: pyCAIR Docs: pycair.readthedocs.io", - "Description": "In this talk, I will speak about a simple yet very powerful image manipulation mechanism. The naive user utilizes the services of any standard toolkit, be it a web service or a remote application for image manipulation. The black box approach to this process is: A user provides an image and other parameters as input to the toolkit which in turn produces the results and returns it back to the user. Often these results are not up to the mark. The image sometimes gets distorted, misaligned or blurred. Deviating from the standard mechanisms, I would like to talk about a technique called as Content aware image resizing . The primary factor in this technique is the content . It is the content which drives the entire technique. The image is cropped, enlarged or modified keeping in mind the primary factor. I will talk about an algorithm called as Seam Carving which is used under the hood to achieve the aforementioned technique. It is this algorithm and the power of Python libraries , that makes this technique perform better than the standard mechanisms. Agenda of Talk: Introduction: Basics of seam carving, how the algorithm works Understanding energy concepts, basics of computer vision and dynamic programming Walk over the pseudo-code and dry run of algorithm Comparative analysis of this technique with standard mechanisms Q&A Session Conclusion", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", + { + "Content URLs": " Will share my slides after my talk as a Github repository.", + "Description": " Abstract This talk is for Python web developers interested in learning what are\nthe core ideas behind microservices, what problems they try to solve,\nand what are the viable options to implement them in Python, both from\ntechnical and teamwork point of views. Some of the topics that will be\ndiscussed include the role of APIs, the improvements microservices\nbring to application scalability, upgrades, and maintenance, and the\nchallenges in breaking up a monolithic application. Contents of the talk About me - Basic introduction of myself. What are Microservices? Monolithic Python Web Application. Problems with Monoliths. Microservice Example. Advantages of Microservices. Disadvantages of Microservices. How to refactor a monolithic application into microservices? ", + "Last Updated": "22 May, 2018", + "Prerequisites": " Basic Python", + "Section": "Core python and Standard library", + "Speaker Info": " My name is Kasam Sharif (Passionate Programmer | Startup Enthusiast |\nProblem Solver). I am currently Software Engineer at Agrostar, Pune.\nPreviously was working at Symantec having 3 year of experience in IT\nindustry. In free time love to learn new things.", + "Speaker Links": " Linkedln : https://www.linkedin.com/in/kasam-sharif-2027628b/ Twitter: https://twitter.com/kasam_sharif94 Github: https://github.com/kasamsharif", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pycair-smart-image-resizing-using-python~bkK6b/", - "title": "pyCAIR: Smart Image Resizing using Python" + "author": "Kasam Sharif (~kasamsharif)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-microservices~dyA6d/", + "title": "Python Microservices" }, - "66": { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "Problem description : Deep learning algorithms have shown great results in speech recognition domain, So here we have used deep learning techniques to enable the machines to read the lips from a video without sound better than humans. By analysing the movement of lips of a person we are trying to predict what that person is trying to speak.\nAutomated Lip reading can be helpful in many ways. Some of them are: Silent dictation in public spaces. Covert conversation. Helping the people with speaking ade in talking to other people. Improved hearing aids. Speech recognition in a noisy environment. The talk will be focused on : How the problem should be tackled. Discussion of different phases Algorithms and python libraries used for implementation.", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations Basic understanding of Recurrent Neural Networks : An excellent resource to understand this is Understanding LSTM Networks . Similar to CNN the motive should be to understand the basic working of Recurrent Neural Networks. The coding part will be discussed in the talk.", - "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal", + { + "Content URLs": " I'll be sharing the slides after my talk as a Github repository", + "Description": "RabbitMQ is a powerful messaging broker based on the Advanced Message Queueing Protocol (AMQP). Microservices do what they say on the tin. They\u2019re small, isolated services that represent an equally small portion of your business domain. Recently there's a trend to build an application using Microservices which place an emphasis on small processes. As an increase in Microservices, we need to a mechanism where we could use some channel(Pub-Sub) to talk between these Services. Contents 1) Introduction to RabbitMQ and Its Terminology 2) Microservices using Pub-Sub 3) Sample Execution At the end of this session, participants will be able to use the rabbitMQ for there application(Could be ETL's/ MicroServices etc", + "Last Updated": "22 May, 2018", + "Prerequisites": "1) Basic Pytho", + "Section": "Others", + "Speaker Info": "My name is Jigar Shah. I have completed my BTech from Walchand College of Engg Sangli. I am currently working as a Software Developer @Browserstack. Interests: Building Backend Architecture, System Design, Data Structures, Algorithms More Inf", + "Speaker Links": "Github Linkedl", "Target Audience": "Beginner", "Type": "Talks", - "author": "Saqhas", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-lip-reading-using-convolutional-neural-networks-in-python~ejMvd/", - "title": "Automated Lip reading using convolutional Neural Networks in python" + "author": "Jigar Shah (~jigarshahindia)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rabbitmq-in-python-for-event-based-communication-between-microservices~az4qd/", + "title": "RabbitMQ in Python for event-based communication between MicroServices" }, - "67": { - "Content URLs": "Will be provided soo", - "Description": "Everyone need not to know everything to build something great. If you are a student and wants to build a major/minor or a professional level project without worrying about the DevOps/Servers and its cost. If you are a Data Scientist and works with files/data and want to make your analytical tool public but you don't want to get in Server handling and learning some web framework . If you are a Frontend developer or work in a fast paced organisation where shipping out fast, better, robust and always running services are required. If you want to prepare a POC or a working model API fast without the requirement of server engineer. Then, this Talk is the place which your are looking for. This talk will be focused on How one can build really scalable and robust web APIs without learning any web framework that too in a very very easy manner. We will be talking about a python package I have made called Lamlight which makes the process of building web APIs as simple as a Git push . This package provides a CLI tool and answers the limitations imposed by the services like AWS lambdas . Lamlight enables Developer to: Make web APIs without learning any web framework or DevOps. Just focus on the core business logic because everything else it will provide you. (Eg: full python boilerplate, CLI automation tool ) Live code Changes. Put large dependencies on your Serverless web api like Numpy, Scipy, Pandas. Save 80% of time by making the process as simple as Git push. Objective of the Talk: Problems faced in a Servered Architecture. Introduction to Serverless Web APIs. Why Shift to Serverless Web Architecture. Platforms providing these Services and their limitations. Get Faster and beat these Limitations. Problems solved by Lamlight. Explanation of its working. Live demo. Q & A The talk would be extremely beneficial for students, Algorithm developer, Frontend Developer, Data scientists and others who are not familiar with server side development and server technologies or want to save time of server handling but still want their work to be done", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Love for Python Linux AWS(Optional)", - "Section": "Developer tools and Automation", - "Speaker Info": "Hello I am Rohit Negi. I am a developer with 1 year of professional experience and +2 years of freelancing experience. I have a Bachelor's degree and I am currently working as a developer in Elucidata Corporation, where I work on making technical architectures for the system to get connected and work robustly , designing Server APIs, Working with Frontend technologies like Angular to make the robust Frontend apps. I am very passionate about creating new and better stuff", - "Speaker Links": " https://www.linkedin.com/in/rohit25negi/ Email: rohit25.negi@gmail.com", + { + "Content URLs": " The main sunpy website - SunPy.org The code repository - sunpy My Experience with working on the SunPy project - Blog SunPy Gallery - Examples My Contributions to the SunPy Project - Code + Examples Contribution", + "Description": "The Problem The Sun releases huge amount of magnetic energy in the form of X-rays, EUV (Extreme ultraviolet) and high energy particles. This kind of radiation bursts can cause damage to space and ground based technological infrastructure. \nHence monitoring such solar activity is crucial. Research Work There has been considerable research in the field of solar activity monitoring as done by NASA Space Stations. Primary research includes locating sunspot regions or potential regions of high solar density along with detecting solar flares from the solar data. Solar Physics in Python In the field of solar physics, IDL is regarded as the primary programming language for solar data analysis purpose. But due to its less popularity and complexity there has been transition to using a much simpler yet robust language Python. The SunPy Project is such a community developed open source project for solar data analysis purpose based in Python. So how using python we can benefit the astrophysics and helio-physics community to query solar data and analyze them much more efficiently and produce much more insightful results ? In this talk we will be discussing how we can analyze sunspots and solar flares through image-processing tools using a python package called sunpy . A small example Locating Solar Spikes in the solar Map Original observed AIA image After locating such regions Extras More examples - SunPy Gallery Machine Learning with Solar Data", + "Last Updated": "22 May, 2018", + "Prerequisites": " Knowledge of Python (Beginner/ Intermediate) Little bit knowledge about the sunpy package (not mandatory) Python modules like scipy and matplotlib since there is heavy use of this two modules. A lot of excitement and passion for open science", + "Section": "Data science", + "Speaker Info": "Prateek has been an open source enthusiast for the past 2 years with a deep love in the field of astronomy and helio-physics . He is currently an undergraduate in computer science also a GitHub Campus Expert working directly with GitHub Education to build open source communities and support them on campus. He is a core contributor to the SunPy project for around more than a year which is lead by researchers from different universities along with scientists at the NASA Goddard Space Flight Center", + "Speaker Links": " GitHub Profile - prateekiiest Twitter - prateekiiest Website - prateekiiest,github.io GitHub Campus Expert - prateekiiest @campus_expert Blog - Medium", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Rohit Negi (~rohit17)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lamlight-develop-webmobile-apps-without-learning-django-flask-and-any-other-web-framework~egKke/", - "title": "Lamlight: Develop web/mobile apps without learning Django, Flask and any other web framework" + "author": "Prateek Chanda (~prateekiiest)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/predicting-sunspots-and-solar-flares-with-a-tinge-of-python~dBXQa/", + "title": "Predicting Sunspots and Solar Flares with a tinge of Python" }, - "68": { - "Content URLs": "GitHub More content will be updated soon", - "Description": "What is Transfer Learning? Transfer Learning is the method of reusing our existing knowledge developed for one task to solve a similar task. Say, you want to detect cars on night-time images and instead of learning from scratch we could reuse our existing knowledge from a model which has been trained on day-time images. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. I believe Transfer Learning is a major achievement in our quest for Artificial General Intelligence (AGI) as Transfer Learning allows us to generalize our knowledge which is something we humans excel at. Andrew Ng, ex-chief scientist at Baidu, co-founder of Coursera and professor at Stanford, said during his widely popular NIPS 2016 tutorial, \u201cTransfer Learning will be the next driver of ML success.\u201d Training Deep Neural Networks from scratch is an expensive process. Not only does it require a lot of compute resources and time, deep Learning models require a huge amount of data and it is a major bottleneck when it comes to start-ups and niche areas of research like health care. What you will learn :- How to build an image classifier in a few minutes using Transfer Learning When and how to fine-tune pretrained models Freezing layers of a pretrained model depending upon the scenario Using ConvNet as a feature extractor Using differential learning rates Constraints of using pretrained models Transfer Learning : Beyond Computer Vision Cross-Lingual Domain Adaptation : Using the knowledge we have learnt from one language and applying our knowledge to another language is another application of transfer learning with huge potential. Cross-lingual adaptation methods would allow us to leverage the vast amounts of labeled data we have in English and apply them to any language, particularly languages with very less labeled data such as Indian languages. Reinforcement Learning and Learning from Simulations : Training an agent (in Reinforcement Learning) to achieve general artificial intelligence directly in the real world is too costly and hinders learning initially through unnecessary complexity. It is better to train an agent in a simulated environment such as the OpenAI Gym before deploying it in the real world. Eg: Self-driving cars Agenda 1.Introduction to Computer Vision (3 min) 2.Introduction to Transfer Learning (3 min) 3.Why should you use Transfer Learning? (2 min) 4.When to use Transfer Learning? (2 min) 5.Build an image classifier in minutes using Transfer Learning (2 min) 6.Effective Transfer Learning techniques (6 min) 7.Feature Extraction using pretrained models (3 min) 8.Constraints of using pretrained models (1 min) 9.Transfer Learning beyond Computer Vision (3 min) 10.Transfer Learning : A right step towards Artificial General Intelligence (AGI) (2 min) 11.Q&A session (3 min", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of deep learning Love for Pytho", - "Section": "Data science", - "Speaker Info": "Hi! I\u2019m fascinated by AI and it\u2019s applications particularly in art and culture - generating art, fashion styles, music, literature, etc. I\u2019m a 3rd year student (just started) at SRM Institute of Science and Technology, Chennai studying Computer Science Engineering. I\u2019m also part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in AI, Blockchain, Computational Biology, Electrical Systems, Internet of Things, and Mixed Reality. I\u2019m currently working as a Computer Vision intern at Cogknit Semantics, Bangalore. I'm working on a fashion recommender system which analyses an image of a shirt/pant/shoe and suggests matching clothes to go along with it. I love Python because of it\u2019s simplistic philosophy and lucid coding style which allows me to think more about model architectures rather than fixing bugs in my code", - "Speaker Links": "Connect with me on LinkedIn Find me on GitHub Follow me on Twitter E-mail me at : niladrishekhardutt@gmail.co", + { + "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", + "Description": "Malware is a serious threat to all kind of Cyberinfrastructure. Since the first known malware (formerly or generally known as Virus) there have been malware detection techniques. There is the arms race between new incoming of Malware and defense against it. Traditionally, anti-virus software uses signature-based techniques to detect malware and protect the underlying system. Due to some critical limitations of signature-based techniques, anti-virus, and security agency looking for alternative techniques and investing in machine learning based techniques for malware detection.\nThis workshop aimed to train the participants through various steps involved in building malware classifier based on machine learning algorithms. Python is very suitable for the task due to its large number of useful modules suitable for each and every step. During this workshop, following topics will be explained with proper hands-on using Python. Explanation of the topic and draw out the various required steps. Data collection: How to collect Malware and Benign samples for the experiment. Pre-processing: How to carry out various pre-processing tasks\n (duplicate removal, file type identification etc.) to prepare the suitable dataset for the experiment. Labeling: How to label the sample i.e. malware v/s benign. (Required\n for supervised learning.) Feature extraction: How to extract features from the sample and\n build the proper representation of features to be used with various\n Machine learning algorithms. (We will restrict to static features\n for this workshop). Model training and Testing: How to train various machine learning\n algorithms and test their performance to select the best model. Making model persistence: How to make the selected model persistence\n to further use. ", + "Last Updated": "23 May, 2018", + "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general. Required module/library:\n1. pefile\n2. androguard\n3. scikit-learn\n4. CS", + "Section": "Networking and Security", + "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", + "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", "Target Audience": "Intermediate", - "Type": "Talks", - "author": "niladri99", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-subtle-art-of-effective-transfer-learning~dw5ra/", - "title": "The Subtle Art of Effective Transfer Learning" + "Type": "Workshops", + "author": "urwithajit9", + "created_on": "23 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-malware-classifier-from-sample-collection-to-persistance-model-using-python~eEXWd/", + "title": "Building Malware Classifier: From Sample Collection to Persistance Model using Python" }, - "69": { - "Content URLs": "https://www.slideshare.net/mobile/karx01/micro-python-pycon-india-2018-proposal-kartik-aror", - "Description": "This session will aim to achieve 2 objectives Introduce you to (in a fun and practical way), what is microPython. equip you to be up and running to build your own systems!", - "Last Updated": "13 Jun, 2018", - "Prerequisites": "Must know a guy who owns a raspberry Pi", - "Section": "Embedded python", - "Speaker Info": "Hello World. I am Kartik Arora, founder at Akriya Technologies . Before starting my journey in the wild, I worked for Rivigo for a few months, and in Bing Team during my 2 years at Microsoft", - "Speaker Links": "https://twitter.com/karx_brb https://www.facebook.com/karx01 https://www.linkedin.com/in/karx01 https://github.com/kar", - "Target Audience": "Beginner", + { + "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", + "Description": "Python is a versatile, powerful, and general purpose language, its easy and clear syntax makes it very popular for the beginner as well as the advanced programmer. Malware is one of the top threats to today's digital society. Due to heavy financial loss along with other infrastructure losses, the software industry is investing hue money for malware research and at the same time due to the wide need of effective and efficient anti-malware solution, the anti-virus industry is emphasizing on malware research.\nThis talk will focus on the array of python resources (script, modules, library, frameworks etc.) available for various dimensions of malware research. During the talk, I will share my experience with various tasks or problems related to malware research and how with the use of Python, those were solved. This talk will try to draw a parallel connection with various tasks related to malware research and suitable Python resources available for achieving those tasks. The talk will be supplemented with the brief explanation of concepts and python snippets for the same. \nSome of the modules and topics that I will touch upon are: yara Accessing VirusTotal API with Python Cuckoo-sandbox Androguard pefile pyew file type filtration ClamAV and pyClamd etc.", + "Last Updated": "23 May, 2018", + "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general", + "Section": "Networking and Security", + "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", + "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Kartik Arora (~kartik53)", - "created_on": "13 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/micropython-time-to-get-building~av58e/", - "title": "MicroPython : time to get building" - }, - "70": { - "Content URLs": "My python script", - "Description": "Information is being generated at an exponential rate everyday. There are multiple sources generating information. It becomes really tedious for a person to go and visit all the sources to obtain information. It could be of great help to the person if there can be a single source which cumulatively providing all the links of news generated by different newspapers. This is where web scraping and automation comes into picture. In this talk I want to explain how to scrape webpages hassle free , gather information and represent the gathered content in a easy to visualize format. By executing just a single Python file we can get all the data what we want from the web. Its not just about collecting the data, it is to reduce the repetitive work which a person does again and again to achieve the same goal. We can put repetitive work into a module and leave it upon the computer to do the same. This in turn will help us channelize our time more on the information rather than gathering that information. Agenda of Talk: Introduction: Web scraping, automation tools, parsing and scraping python libraries. How it helps in learning python extensively: My experience with web scraping and various use-cases on which I utilized. Q&A session.", - "Last Updated": "12 Jun, 2018", - "Prerequisites": " Basics of python", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking.", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "author": "urwithajit9", + "created_on": "23 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-arsenal-for-malware-research~dGXKe/", + "title": "Python Arsenal for Malware Research" + }, + { + "Description": "The Talk will focus on the importance of satellite image processing with main focus on the utilisation of GDAL library to conduct various operations on satellite data. Datasets will include Optical imagery and Synthetic Aperture Radar Imagery. The power of GDAL library alongwith numpy and matplotlib will be demonstrated. Brief analysis of satellite images using python will be given", + "Last Updated": "23 May, 2018", + "Prerequisites": "Basic Knowledge of numpy and matplotlib libraries", + "Section": "Data science", + "Speaker Info": "Shubham Sharma is a Junior Research fellow currently working on a collaborative project with Calibration and Validation Division of Space Applications Centre, ISRO, Ahmedabad. He has a rich experience in handling and processing of Synthetic Aperture Radar Images. Also, he has experience in building software tools in python for satellite Image analysis", + "Speaker Links": "https://in.linkedin.com/in/shubham-sharma-5468578", "Target Audience": "Beginner", "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/importance-of-webscraping-and-automation-using-powerful-python-libraries~er52d/", - "title": "Importance of webscraping and automation using powerful python libraries." + "author": "shubham_thb", + "created_on": "23 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/satellite-image-processing-with-python~dJKKe/", + "title": "Satellite Image Processing with Python" }, - "71": { - "Content URLs": "Will be updated on github before the conference", - "Description": " It is always essential to understand the genesis of evolution or the roots of revolution. Keeping in mind the above saying, in this workshop, I will provide a hands-on understanding of Blockchain technology using Python. There are multiple resources to get a firm understanding about this domain, but the best way to understand it is by using the concept of \"Learning-By-Doing\" . Following are few reasons why I want to willingly contribute to this domain: Blockchain is the underlying technology behind most of the\n cryptocurrencies and it has a potential of changing the way we work\n and communicate, making it more secure, efficient, and trustworthy. There is a immense amount of speculation going around in this domain\n with the rise of Bitcoin. What\u2019s happening with blockchain\n technology, I would say, is similar to the great American gold rush\n that happened in the mid 1800s. Innovators, investors, entrepreneurs, technologists all are hovering\n over the same underlying idea on how these cryptocurrencies work and\n how could blockchain be leveraged to create use-cases beyond\n crypto-systems. Also, I would love to mention few quotes to support the escalating phenomenon of Blockchain : The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping\neverything along its way by the force of its progression. -- William\nMougayar Over the next decade, there will be disruption as significant as the Internet was for publishing, where blockchain is going to disrupt\ndozens of industries, one being capital markets and Wall Street. -- Patrick M. Byrne I will help people in understanding the bits and bytes of this domain, including the basic cryptography concepts, algorithms and how to utilize the power of Python language to build their own blockchain. As we progress, we would engage into more advanced concepts pertaining to scalability and deployment once we build a minimalist prototype of aforementioned. Using on-the-go learning while developing will serve as a pivotal entry point for all the people who are willing to enter into this space and planning to build smart-contracts or invest in cryptocurrencies. Agenda for workshop : Introduction to Blockchain: Existing problems, what is Blockchain, why it matters, gist of few use-cases, related concepts. Python revisited: Functions, libraries, object-oriented programming terminologies, basic data structures, basics of zen of python. Blockchain under the hood: Cryptography 101, underlying data structure and algorithms, conceptual terminologies. Python and Blockchain amalgamated: Create blockchain using python. User-friendly front-end: Integrating the scripts in previous section with a basic front-end. Discussion regarding scalability methods and resources. Generating self-help focused Pypi library called pymyblockchain . (optional) Q&A session. Note: The above agenda is subject to change. It is tentative for now. Any changes will be updated here itself", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basic python: Functions , Classes and Objects , Use of Libraries *No prerequisites apart from aforementioned. Even a person who is new to python will be able to grasp everything in workshop", + { + "Description": "Many at times, we need to encapsulate our core logic in order to protect it from being reverse engineered and being exploited. Having a strong IP may not be the only protection. Once the code is open for the analysts, they can easily implement a modified version to achieve their goals. Some areas where the code obfuscation plays an important role are financial domain, security, web/mobile. Many times developers / teams fail to achieve the right level of code obfuscation which in turn fails to provide the level of protection to their code. We will be walking through the existing code obfuscation techniques in python and the level of protection they offer. I will be sharing my experiments and learnings during the journey to achieve a better obfuscation mechanism for python code", + "Last Updated": "22 May, 2018", + "Prerequisites": "Required : None. As we will be covering the required basic for code obfuscation in the talk it self. Good to have : Understanding the python run time process and how the code gets converted to executable binaries can be helpful", "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Speaker Info": "I am Kailash, currently working as a Senior Software Engineer in Visa. I have been into python programming for the past 6 years now. I had worked on multiple levels of python projects ranging from scripting and automation, DevOps, Machine Learning, Computer Vision, Algorithmic Trading, Website Backends", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Venkata Naga Kailash Anantha (~avnkailash)", + "created_on": "22 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/effective-code-obfuscation-protecting-your-python-code-from-being-copied-reverse-engineered~axzld/", + "title": "Effective Code Obfuscation : Protecting your python code from being copied / reverse-engineered" + }, + { + "Content URLs": "I'll share my slides after my talk as a GitHub repository", + "Description": "This talk is for Python enthusiasts who are interested in building test automation framework and test suites for REST API functional testing. It would throw a light on how to write useful, business-oriented and maintainable functional API test suites in Python on top of existing test frameworks like lemoncheesecake . Contents: About myself REST API and it's testing - A quick introduction Choosing a test framework to write your tests on Making API requests from Python Writing suite configuration and teardown code Introduction to the \"component-tests\" model for structuring the test code JSON parsing, use of matchers, asserts for writing test case validation criteria Importance of logging and reporting - How logs and readable reports can ease the job of debugging bugs found using tests Bringing everything together", + "Last Updated": "24 May, 2018", + "Prerequisites": " Python basics REST API basics Basics of test frameworks like pytest Passion for test automation", + "Section": "Developer tools and Automation", + "Speaker Info": "I'm currently working as a SDET Lead with AgroStar, India's largest agri-tech platform for the Indian farmer. I'm passionate about technology and automation, I'm willing to contribute in building robust software test frameworks accompanied with some of the best industry practices like CI/CD that would help ensuring the best possible software quality from time-to-time. The \u201calways exploring and learning\u201d attitude is something that keeps me going", + "Speaker Links": " LinkedIn Facebook Twitter", "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchain-by-implementing-it-from-scratch-in-python~bq57b/", - "title": "Understanding blockchain by implementing it from scratch in Python" + "Type": "Talks", + "author": "Akshay Maldhure (~akshay61)", + "created_on": "24 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rest-api-functional-testing-with-python~aK7Ga/", + "title": "REST API functional testing with Python" }, - "72": { - "Content URLs": "https://www.tensorflow.org/ https://github.com/aymericdamien/TensorFlow-Example", - "Description": "Hey everybody!\nIf you have ever heard of this thing called as neural network , than this workshop is definitely for you .Neural networks are not new they been there for a long time . but they have become quite famous recently\ntensorflow is consisdered one of the best frameworks for getting started with neural networks and deep learning . About TensorFlow TensorFlow\u2122 is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google\u2019s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. We will also try and build an image recognition model using deep learning from scratch . Tensorlfow helps getting started with deep leaning and building neural networks ", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basics of python and an open mind to learn new things ", - "Section": "Data science", - "Speaker Info": "Python lover . Machine learning enthusiast . Currently working on BIG ML ( training machine learning models on big data ) and efficient deployment of machine learning models on production ", - "Speaker Links": "Contributor at https://github.com/polyaxon/polyaxo", + { + "Content URLs": "will be sharing the slides after my talk as a Github repositor", + "Description": "AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment. CloudFormation allows you to use a simple JSON or YAML file to model and provision, in an automated and secure manner, all the resources needed for your applications across all regions and accounts. This file serves as the single source of truth for your cloud environment. In this talk, I will be using Python to generate the JSON and YAML files with which AWS CloudFormation can be done. During this talk I will be covering the below points What is AWS CloudFormation? Library in Python for AWS CloudFormation. What are S3 and EC2 AWS services. Creating basic S3(Simple Storage Service) and EC2(Elastic Compute Cloud) instance using Python. Installing MySQL in the EC2 instance. Code pipeline (Automatic Deployment from Github to production server)", + "Last Updated": "25 May, 2018", + "Prerequisites": "Basic Understanding of Python and how to use Libraries", + "Section": "Developer tools and Automation", + "Speaker Info": "I am Mohan currently working as a Software Engineer at Amzur InfoTech Visakhapatnam.I have been in to Python Programming for the past 1 year. I have 2 years of experience as a Developer. I had worked on Data Migration. I am currently working on Data Science,MicroGrids Automation and AWS", + "Speaker Links": "www.linkedin.com/in/mohan-pavan-kumar-bailapudi-5628a296 https://github.com/MohanBailapud", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-build-neural-networks-from-scratch-using-tensorflow~boKYb/", - "title": "Learning to build Neural networks from scratch using tensorflow" + "Type": "Talks", + "author": "Mohan Bailapudi (~mohan57)", + "created_on": "25 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-cloudformation-with-python~dL1De/", + "title": "AWS CloudFormation with Python" }, - "73": { - "Content URLs": "Any related material will be shared soo", - "Description": "Financial data is difficult. It is sensitive to many unknown factors. So we need a good strategy for trading with deep learning. That's where reinforcement leaning comes in. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over.\nBy the end of the talk, you will learn:- What trading is? Why it's hard? How Can Deep Learning solve the trading problem? Why is reinforcement learning an effective solution?", - "Last Updated": "11 Jun, 2018", - "Prerequisites": " Willingness to learn Basic python", + { + "Content URLs": "Fo now, I just have a gist: But I will create a proper package before the event: https://gist.github.com/dhilipsiva/3d7586e7bb941919f28afa70ccc39dd", + "Description": "Microservices are fun. But what would make them even more fun to work with, is if we can avoid duplicating the data layer across your micro-services. Django ORM is amazing. Let's share the joy of Django ORM with other languages. I have written a tool to automatically expose Django ORM to other languages and which can also generate respective client libraries in other languages. I heavily rely on Protobuf and gRPC and a lot of AST parsing", + "Last Updated": "25 May, 2018", + "Prerequisites": "You will need to know basics of: Django ORM Protobuf gRPC (or cap'n proto or any other RPC framework) Microservices", + "Section": "Developer tools and Automation", + "Speaker Info": "Wannabe Astrophysicist. Full Stack + DevOps. I code for fun and profit. Mostly in Python. FOSS. Dad of 2. Environmentalist. Atheist. Story Teller", + "Speaker Links": " http://dhilipsiva.com/ https://twitter.com/dhilipsiva https://github.com/dhilipsiva/", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "dhilipsiva Dhilip (~dhilipsiva)", + "created_on": "25 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automagically-exposing-djagno-orm-over-grpc-for-microservices-written-in-other-languages~aMKmd/", + "title": "Automagically Exposing Djagno ORM over gRPC for microservices written in other languages" + }, + { + "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", + "Description": "The era of Artificial Intelligence is moving quite rapidly across the globe. It's being used in almost every application we know , from medical diagnosis to self driving cars and it's use is still growing exponentially. But should we blindly trust AI ? Is this technology robust enough? Are we capable enough to handle it's power? In this talk we will step back for a moment and look forward about the security issues and robustness of this technology. I'll be discussing the problems we can face , the precautions we have to take, etc. with the help of a famous problem, known as One Pixel Attack ", + "Last Updated": "25 May, 2018", + "Prerequisites": " A bit of Python Some knowledge of Machine Learning And a broader perspective ", "Section": "Data science", - "Speaker Info": "I have always been amazed by computers and how much you can do with soo little. Curiosity lead to passion. Passion lead me to work on some amazing things. AI is the buzzword around and I have been working on AI for quite some time and it's been a really great journey, challenging but rewarding. Recently, I started working with some startups. Currently, I'm working for a Silicon Valley startup, who has been working on making serious predictions on small data. I have also been interested in Fintech data. I started with simple fraud detection models and now I'm working on solving the trading problem with reinforcement learning", - "Speaker Links": "Connect on Twitte", + "Speaker Info": "The speaker, Srajan Kant Jha, is a final year B.E. student who has been working on Machine Learning and Data Science from quite a while now. Nonetheless, he pivoted from C/C++ to Python and during the transition, has also developed some projects on the same. He used to blog at his leisure time and is still on a venture to provide the knowledge of ML and Data Science to enthusiasts through a project site. Srajan is also the City Ambassador (and one of the speakers) of AI-Saturdays, which is a community of over 5000+ students(over 100+ cities) that helps people try their hands on Deep Learning and Artificial Intelligence, free of cost. Inspite of this, he still has a lot to discover in this growing industry. (Follow him on social media to know more", + "Speaker Links": " LinkedIn : https://www.linkedin.com/in/srajan-jha Github : http://github.com/srajan23 (not much updated) Facebook : https://www.facebook.com/srajan23", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Himanshu Singh (~himanshu61)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-trade-with-reinforcement-learning~enX5b/", - "title": "Learning to Trade with Reinforcement Learning" + "author": "Srajan Jha (~srajan)", + "created_on": "25 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-robust-is-artificial-intelligence-ai-using-python~dNK2e/", + "title": "How ROBUST is Artificial Intelligence ? ~ AI using Python" }, - "74": { - "Content URLs": "Will be uploading soon !", - "Description": "My philosophy has been : If you haven't build it you don't know it. So lets build a hadoop clone and see how it works . This workshop is basically about building your distributed processing system . It will take you through some basics of distributed system and we will try and build our very own distributed system in python ", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Google \"what is hadoop\" Google \"what is a distributed system", - "Section": "Networking and Security", - "Speaker Info": "class Pankesh (human)", - "Speaker Links": "class Pankesh (Human): def __init__ ( python=\"Python3\" ) :\n\n super.name = \"Pankesh gupta\"\n\n super.age = 25\n\n curiosity = True\n\n experience = 2\n\n education = \"Thapar University , Patiala", + { + "Content URLs": " Github reposistories: Keras_aud Audio-Vision Drive links: Content link : (Slides to be uploaded soon)", + "Description": "In this workshop, we will try to teach how to understand Deep Learning, various paths to follow, Domains to explore and the most important part- how to start with the paper selection and implementation. We will also learn how to deploy a simple model into production. This workshop aims at providing the attendees of all level a foundation of research and further prospectives in deep learning. Contents Paths and prospects in Industry and Academia (10 minutes) Difference between AI, ML, and DL. (5 minutes) Introduction to Deep Learning frameworks (Hands-on) (5 minutes) Paper selection (10 minutes) Implementation (Hands-on) (60 minutes) Understanding the dataset Feature Extraction Model Selection Data Formatting Comparison Demonstration of our work (General Overview) Audio Tagging Acoustic scene classification Visual Question Answering Publish/Deploy (Hands-on) (30 minutes) Stay Motivated Opportunites to explore The participants should have interest in Research. Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first-time learner\u2019s of AI to comprehend", + "Last Updated": "27 May, 2018", + "Prerequisites": "Preferred Basic Python concepts Basic knowledge about Machine Learning Algorithms. Preferred (but not necessary) Interest in working on Research problems Installed libraries: Keras Theano or Tensorflow", + "Section": "Data science", + "Speaker Info": "Aditya Arora and Akshita Gupta are currently final year semester exchange students at Indian Institute of Technology, Roorkee. They have been working on research problems using deep learning specifically in Audio processing and visual Q&A. Aditya is a member of various open source societies such as rust-community while Akshita has experience in Academia research and is a selected as an Outreachy intern at Mozilla 2018. They have been working in python for the past 4 years and have been moving forward working on Computer Vision and Audio processing problems", + "Speaker Links": " Twitter : https://twitter.com/imaarora Twitter : https://twitter.com/akshitac8 Linkeldn: https://linkedin.com/in/aditya-arora145/ Linkeldn: https://www.linkedin.com/in/akshita-gupta152/ Github : https://github.com/channelcs Blog : http://channelcs.github.io/", "Target Audience": "Intermediate", "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lets-build-a-hadoop-clone-in-python~bm6Rd/", - "title": "Lets Build a Hadoop clone in python !!" + "author": "Akshita Gupta (~akshitac8)", + "created_on": "27 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-into-the-world-of-deep-learning~aOXRb/", + "title": "Deep Dive into the world of Deep Learning" }, - "75": { - "Content URLs": "-> How does a web framework work -> WSGI basics -> Getting hands dirty with coding More information will be uploaded soo", - "Description": "Build your own web framework using python .\nLets unleash the power of python by building a web framework from scratch . \nIt will help you understand what actually happens under the hood in most famous web framework", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Web development basics\nCuriosity\nTrust in python :", + { + "Content URLs": "The repository where I have implemented concepts related to this talk https://github.com/tanayseven/http_quiz Contents for the presentation for the talk https://github.com/tanayseven/pycon_2018_python_web_app_tes", + "Description": "Abstract One of the first projects that I worked in the industry was in Flask . This talk is based on my experiences in the project with respect to the test suite and different things that I learnt in that. On the bases of those learnings, I started my own open source project on Github and enhanced on those ideas on how all the things necessary for testing are done. This is based on Flask as the web framework and all the ideas are implemented in it. The topics it covers are those things that you can do to achieve a robust set of tests in your code. Outline of the talk Pushing for 100% code coverage Making your test execution fast! The evil of \u2018over mocking\u2019 The necessity of using dependency injection Test Pyramid or Test Cone? TDDing while making changes Layers that make the web app architecture How does this map to UI testing", + "Last Updated": "27 May, 2018", + "Prerequisites": "Although most of the things are implemented in Flask, it is not necessary to know it, although it is very much recommended to know some web framework or having some knowledge of web app programming", "Section": "Web development", - "Speaker Info": "Not so useful BTech ( biotechnology ) from Thapar University\n2 years of experience working in pytho", + "Speaker Info": "A passionate developer with Python as his primary language. Have worked with Flask in the industry in the past. Passionate about testing and writing the code in a way that is very clean and maintainable. A strong believer in TDD and massive test coverage", + "Speaker Links": "https://tanayseven.com https://github.com/tanayseven https://www.linkedin.com/in/tanay-prabhudesai/ https://twitter.com/tanayseve", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-our-own-web-framework-like-flask-in-python-from-scratch~el0je/", - "title": "Building our own web framework like flask in python from scratch" - }, - "76": { - "Content URLs": " Will have own slides. Link will be shared with all This GitHub Repo contains some of the content that will be delivered during the course of the talk. A lot of other websites from where I pick a point or 2", - "Description": "Everyday we listen to this word \"DATA\".\nBut after listening to that word, some questions might pop up in your mind. WHAT IS DATA? WHY DOES ANYONE NEED TO WORK WITH DATA? HOW TO UTILISE AND WORK WITH THIS DATA? Data is now one of the most important things for any business to run. From small startups to large companies, everyone looks at data to improve their business.\nEveryone looks at data to increase their profits. Everyone looks at data to understand why they failed and where they failed. Everyone looks at data to understand how a product gained success in the market. Basically Data is everything today for companies. Data is available everywhere now and it's become more important than ever to actually work with data and luckily we have great modules to work with data in Python. I'll be focusing on these modules and the power that data possesses. My primary focus here would be about the power of data. I surely will be talking about how to use this data in Python to make the most out of it, but before that I'd like the entire crowd to know what the power of data is. This would be a good talk for beginners honestly. Even if you have no idea about how data could be used or what is data, after this talk, you'll get a decent idea about it. Through this talk the 3 questions mentioned above in bold will be answered. The talk would progress in the following manner : Self introduction (3 minutes) Introduction about the topic (2 minutes) What is data? (3 minutes) Where is this data? (2 minutes) How to make the most out of data? (3 minutes) How Python helps in this process? (2 mins) Name and explain about different Python modules like Pandas, Numpy, Matplotlib and Seaborn in brief (10 mins)", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "No prerequisites required. This talk will deal about everything from scratch and will give you a basic understanding of what modules could be used in Python. So you could research on those modules after the talk, but for the talk, no prerequisites required", - "Section": "Data science", - "Speaker Info": "Hey everyone, I'm Rahul Arulkumaran, a B.Tech 3rd year Student pursuing my major in Computer Science Engineering from Mahindra \u00c9cole Centrale, Hyderabad. I'm an open source and data science enthusiast. Coding is one thing I love doing all day and all night. Never feel like quitting.\nPython is my go to language. Anything I think of developing comes to life using Python. I have a very strong connection with Python as it was the first programming language I learnt. I'm also a full stack developer and perform data science on various datasets. I'm a Contributing and Managing Member in the PSF. I also am the President of the Computer Science Club in my college. Apart from that, I head the website development team for TEDxMahindra\u00c9coleCentrale and the Marketing and Promotions team for Aether (the techno cultural fest of MEC). I'm the Co-Founder and CEO of a startup which goes by the name FreeFlo. It is a product based company that looks at developing products related to Machine Learning, Blockchain and other related fields. I'm also currently interning in IIIT-Hyderabad in the Machine Translations and NLP Lab in the field of sentiment analysis. It might seem although I'm not interested in the non tech aspects of businesses, but I actually love working in teams related to business development and marketing. So that's mostly about it. Looking forward to interact with all of you out there ", - "Speaker Links": " GitHub My Blog Facebook LinkedIn Twitter Telegram Gmail ", - "Target Audience": "Beginner", "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/power-of-data-and-working-with-it-using-python~bkgJb/", - "title": "Power of Data and Working with it using Python" + "author": "Tanay PrabhuDesai (~tanay)", + "created_on": "27 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/having-a-robust-test-suite-for-your-python-web-app~dPKAb/", + "title": "Having a robust test suite for your Python web app" }, - "77": { - "Content URLs": "Will be updated soon", - "Description": "Fog and haze (referred to as the atmospheric light) are the main cause of distortions, degradation in the quality of images clicked during foggy situations. But with the advancement in technology, thanks to Python and OpenCV libraries and brilliant minds of people out here in this small world, recovering almost a fog-free image has been made possible in recent times. And now we are moving towards making this algorithm more optimized so that it can work in real time for videos and live camera feed. Different mathematical models have been presented over the time for this algorithm but there are very few real-life implementations in any particular programming language, so here the Python implementation of this algorithm will be discussed. Basic steps and the ideas implemented will be discussed in a brief and different implementation will also be shown in the session", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of the numpy functions. An idea about the OpenCV computer vision libraries and the different filters implemented there. Love for Python", - "Section": "Developer tools and Automation", - "Speaker Info": "Speaker: Vivek Modi Final Year undergrad at NIT Durgapur Tech Head at GNU/LINUX USERS' GROUP NIT Durgapur Summer Intern at DRDO (Integrated Test Range) Contributor in the project: Soumam Banerjee Final Year undergrad at NIT Durgapur", - "Speaker Links": "modiher", - "Target Audience": "Intermediate", + { + "Content URLs": "https://tools.ietf.org/html/rfc7047\nhttps://github.com/openstack/ovsdbapp\nhttp://www.openvswitch.org/support/dist-docs/ovsdb-server.1.htm", + "Description": "OpenvSwitch is an OpenFlow virtual switch implementation. It has its own database implementation based on JSON-RPC (https://tools.ietf.org/html/rfc7047) to store its internal state and data.\nThis session gives an overview of this database implementation and how it used in OVN, an SDN controller from the OpenvSwitch community and in OpenStack networking. This session will look\ninto how it is different from other traditional SQL databases and the python clients available to interact with the OVSDB server and the APIs it provides to carryout the CRUD operations with the OVSDB server", + "Last Updated": "28 May, 2018", + "Prerequisites": "A basic understanding of databases", + "Section": "Core python and Standard library", + "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", + "Speaker Links": " https://numans.blog/about http://stackalytics.com/?metric=commits&release=all&user_id=numansiddique https://github.com/openvswitch/ovs/commits?author=numansiddique", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Vivek Modi (~modihere)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-and-opencv-for-removing-fog-and-haze-from-an-image~ejBye/", - "title": "Using Python and OpenCV for removing Fog and Haze from an Image" + "author": "Numan Siddique (~numan)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/openvswitch-database-based-on-json-rpc~dRKVe/", + "title": "OpenvSwitch Database based on JSON-RPC" }, - "78": { - "Content URLs": " http://github.com/vaideesg/omsdk http://github.com/dell/omsdk", - "Description": "Abstract Ever wonder creating your own super-type-manager leveraging the python's own type constructs? Ever explored alternatives to APIs for integration? In this talk, we will cover our experience in building a new type manager (as part of developing open source OpenManage(tm) Software Development Kit) leveraging pythons own type constructs and explore how this new type manager provides a credible alternative to APIs, especially in those information-heavy environments like Device Management. Description Devices (like Servers, Switches, Telecom Switches) are data-intensive systems. Their information model is so intensive, that practically all operations (health, inventory, metrics, configuration) on the device ends up in primarily as CRUD operations on the information model they expose. Only a paltry few operations are exposed as APIs. When building an API for managing these devices, we realized that providing classic function-style APIs only degraded the user experience. What we realized was there was significant information available on the Servers, and providing an API for exposing traditional CRUD (Create, Retrieve, Update and Delete) for all information nuggets was just exploding the API sets. It was not necessarily covering all the scenarios that could be possible for management and did not seem to scale. Our approach was to take this information model within the devices and expose them as a huge navigable data structure representing the entire spectrum of the device and provide a language native experience. We created a new type manager leveraging the python class special operators ( getattr (), setattr (), le () etc.) to create a whole new type manager that provides additional controls and safeguards. Some of the safeguards include: Not allowing edits to read-only components Allowing only applicable changes only (ranges, enumerations) Providing native python experience for special types (IP Address Types etc.) Providing mechanisms to validate cross-attribute validations Providing custom indices for arrays (like Virtual Disks, Users) Providing mechanism for tracking changes to configuration Apply changes to the device optimally Provide mechanisms for identifying configuration drifts Outline : Outline of the presentation: Introduction Device Configuration - Aspects & Peculiarities Pitfalls of API approach for Device Configuration Type Manager - introduction Super Types - Enumerations, Fields, Classes and Arrays Bringing in Native Type Experience Data as API - Enriched user experience Demo Q&A Key takeways to audience Audience will get an exposure: How to create your own type manager by overloading python type constructs Exposure to alternative approach to creating APIs for data-heavy systems & explore benefits Learn how type manager simplifies your life as well as the life of your consumers. Secrets of the python inbuilt __ operators - and how you can leverage them to provide native type experience even for your own custom classes How you can create a better user experience for customers in a simple way How you can incorporate Object Oriented SOLID principles", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " General familiarity with type concepts (fields, arrays, classes, enums) is needed Exposure to in-built operators like ( getattr etc. will help) Exposure to Systems Management would be useful.", - "Section": "Core python and Standard library", - "Speaker Info": "Vaideeswaran Ganesan, Senior Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and data center products. His passion is compiler design, analytics, systems management, networking protocols and automation. Ajaya Senapati, Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and storage products", - "Speaker Links": "Vaideeswaran Ganesan\n 1. My Github Repository 2. My Linkedin Article which I wrote while implementing this Fun with Python Code Generation Ajaya Senapati\n1. Lin", + { + "Content URLs": "https://en.wikipedia.org/wiki/OpenFlow\nhttps://www.openvswitch.org/\nhttps://3vf60mmveq1g8vzn48q2o71a-wpengine.netdna-ssl.com/wp-content/uploads/2014/10/openflow-switch-v1.5.1.pd", + "Description": "Networking is a key aspect of any cloud infrastructure solution. All the VMs and containers\nspawned in a cloud deployment should have seemless layer 2 and layer 3 connectivity. All this is\npossible because of virtual switching and virtual routing. This session talks about what is OpenFlow specification, OpenvSwitch (which implements OpenFlow)\nand how it is used as an important SDN layer in cloud infrastructure solutions (taking OpenStack and OVN as an example)", + "Last Updated": "28 May, 2018", + "Prerequisites": "A basic understanding of networking", + "Section": "Networking and Security", + "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", + "Speaker Links": "https://numans.blog/about/\nhttp://stackalytics.com/?metric=commits&release=all&user_id=numansiddique\nhttps://github.com/openvswitch/ovs/commits?author=numansiddiqu", "Target Audience": "Advanced", "Type": "Talks", - "author": "Vaideeswaran Ganesan (~vaideeswaran)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-as-api-building-a-type-manager-with-python~egyrb/", - "title": "Data as API: Building a Type Manager with Python" + "author": "Numan Siddique (~numan)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-introduction-to-openflow-and-openvswitch~aQKGd/", + "title": "An introduction to OpenFlow and OpenvSwitch" }, - "79": { - "Content URLs": "Any related material will be shared soo", - "Description": "Natural language processing(NLP) is a branch of artificial intelligence concerned with automated interpretation and generation of human language. From keyword search to Virtual Assistants, from spell checkers to language translators and from sentiment analysers to Chat bots, NLP finds its applications in most of our day to day applications.\nThis workshop aims at delivering a basic Hands on tutorial to get started with NLP in Python. It commences with an introduction to NLP, discussion on various applications and a linguistic breakdown of Language (English). By the end of this workshop you will be able to : Install relevant packages such as nltk, gensim and pattern . Applying text processing techniques such as Tokenization, Stemming, Lemmatization and Chunking . Forming a Document Term Matrix using Bag of Words Model . Building a simple Spam/Ham classifier using Bag of Words Model . Generating Word Vectors using Gensim Word2Vec module. Building a Sentiment Analyzer . This workshop provides preliminary insight and a simple explanation to enthusiasts who wish to explore the field of Natural Language Processing.\nIt enables you to talk to your computer!", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of Python. Any knowledge of Python modules such as Numpy, Pandas etc. is and add on.", - "Section": "Data science", - "Speaker Info": "Hello, I am Osheen Nayak, working as a Software Engineer at Texas Instruments Bangalore. I belong to Delhi Technological University batch of 2017.\nI am a Machine learning and Data Science enthusiast and I have been actively driving various Machine Learning activities. I have delivered few talks on Machine Learning in the past one of them including \"A primer on Machine Learning and Artificial Intelligence\" in the IEEE forum to and audience of 50 people. I am an avid football fan and also an amateur player.Also, I like to play video games, cricket and chess", - "Speaker Links": "Connect on LinkedIn : https://www.linkedin.com/in/osheen-nayak-31022a10b", + { + "Content URLs": "https://speakerdeck.com/aravindputrevu/introduction-to-application-performance-monitorin", + "Description": "Often late, the time to debug that particular bug/issue occurring in production with respect to your application is increasing. It might also cause business disruption and affect your organization financially. In this talk, I'd explain how you could use Application Performance Monitoring to understand your application. Application Performance Monitoring (APM) is a solution built on Elastic Stack. APM helps you to build/store data points in Elasticsearch and visualize. It automatically collects information from your python application/service. This talk mainly targets at introducing the solution, why it is needed and what you can do with data. It ends with once data is stored within Elasticsearch, what else you can use the same data for (ex. Infrastructure Monitoring, Machine Learning)? Agenda What is APM?\nWhy APM?\nWhat it can do to your Application?\nDem", + "Last Updated": "28 May, 2018", + "Section": "Developer tools and Automation", + "Speaker Info": "Aravind is a loquacious person, who has something to talk about everything. He is passionate about evangelising technology, meeting developers and helping in solving their problems. He is a backend developer and has six years of development experience. Currently, he works as a Developer Advocate At Elastic and interact with developer community in South East Asia and India. He has deep interest in Machine Learning, Security Incident Analysis and IoT tech. In his free time, he plays around Raspi or a Arduino", + "Speaker Links": "https://aravindputrevu.in will have links to all my social accounts. I have been doing community work for last 3 years. Presenting the same talk at PyCon Bangkok on June 16-17. https://th.pycon.org/talks/#monitoring-your-python-applicatio", "Target Audience": "Beginner", - "Type": "Workshops", - "author": "osheen nayak (~osheen)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-talk-to-your-computer-a-101-on-natural-language-processing-with-python~e0M5a/", - "title": "How to talk to your computer - A 101 on Natural Language Processing with Python" + "Type": "Talks", + "author": "Aravind Putrevu (~aravind34)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-your-python-application~eV2ze/", + "title": "Monitoring your Python Application" }, - "80": { - "Content URLs": "Slides TBD Code repository TB", - "Description": "Abstract Today, massive systems are running on microservices communicating with each other using REST APIs. HTTP is easy to get started, loosely structured and does good job in exchanging messages. But it's convenience comes with a performance trade-off, which takes us back to other optimal alternative: gRPC Description In this talk we will see what gRPC is and how it is different from REST. We will get started with GRPC by generating stubs for python and \nbuild a simple gRPC API server. We will try to find out the advantages of gRPC over REST by doing a side by side comparison of our APIs. We then deploy our server in Kubernetes and discuss how we could scale our microservices. Outline Introduction to gRPC (3 min) gRPC concepts (5 min) Designing the APIs REST-fully (3 min) Going the gRPC way (5 min) Generating python stubs Duel: gRPC vs REST python servers (4 min) Demo (4 min) Deploying our gRPC apis in kubernetes Summary (3 min) Q & A (3 min) Key take aways to audience Audience will get a practical introduction to gRPC and protocol buffers. Now the audience will know an alternative to HTTP/REST. This allows them to design better microservices\nbased on their use cases. Bonus: Deploying and scaling python microservices in Kubernetes. Links Companies using gRPC in production Protocol buffers ", - "Last Updated": "09 Jun, 2018", - "Prerequisites": "This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners", - "Section": "Web development", - "Speaker Info": "Naren is a Product Engineer with specific focus on building robust backend systems. Past 5 years, he has built dozens of microservices and scalable systems using Python, Go and AWS cloud. He is an open source enthusiast who loves speaking at tech conferences and currently works as Senior Software Consultant at Tarka Labs. In his industry experience he\u2019s worn plenty of hats- like the one of a Trainer, Embedded Engineer, Product Engineer and Consultant and sometimes even helmets- while he\u2019s out cycling.\nWhen he\u2019s not stirring up code, you can find him whipping up a delicious gluten-free treat or training for cycling races.\nHe also blogs about software, productivity and goes by the handle DudeWhoCode across the internet", - "Speaker Links": "Past 5 years I have been architecting and building scalable backend systems using Python. I have built a dozen of microservices at scale. Recently I built a production infrastructure in Python that handles 20+ millions of API calls per day. At one point of time, I realised I should know some alternatives other than REST to communicate between the microservices. Out of curiosity I explored and used gRPC in few of my microservices. Since then, I wanted to share the knowledge so that developers will get to know other options while architecting their infrastructure. This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners. I have spoken in various conferences, my recent one was PyCon Singapore 2018. Below are some of my previous talks and speaker portfolio: Speaker Portfolio Featured talk 1 Featured talk 2 Featured talk 3 portfolio blog Github", + { + "Content URLs": "I will share the slides on my github repo for the evaluation by the team in some days.\nOther content will be shared on github after the talk", + "Description": "Training a machine learning / deep learning model is one thing and deploying it to a production is completely different beast. Not only you have to deploy it to a production, but you will have to retrain the model every now and then and redeploy the updates. With many machine learning / deep learning projects / POCs running in parallel with multiple environments such as dev, test prod, managing model life cycle from training to deployment can quickly become overwhelming.\nIn this talk, I will discuss an approach to handle this complexity using Docker and Python.\nRough outline of the talk is, Introduction to the topic Problem statement Quick introduction to Docker Discussing the proposed architecture Alternative architecture using AWS infrastructure Demo", + "Last Updated": "28 May, 2018", + "Prerequisites": " Basic Python Basic Docker", + "Section": "Developer tools and Automation", + "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company.\nI have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures.\nSince past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", + "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Narendran R (~narendran)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-better-python-microservices-using-grpc~e9jJa/", - "title": "Building better Python microservices using GRPC" + "author": "saurabh1deshpande", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-devops-and-ab-testing-using-docker-and-python~bWKEb/", + "title": "Machine Learning DevOps and A/B testing using docker and python" }, - "81": { - "Content URLs": "I will upload slides soon", - "Description": "Object-Relational Mapper (ORM) is one of the powerful feature of Django. It allows us to interact with database without writing long complex SQL queries. The contents that will be covered in the discussion are as follows. Introduction to ORM, How it works ? What is queryset ? how it works ? Explaining use of values, values_list, only and defer to run ORM query efficiently How to use select_related and prefetch_related to optimize queries Some examples to show, how to query very complex data using only ORM What not to do while using ORM to avoid slow performance", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic knowledge of Python and Python web framework (Django) Some experience in quering relational databases", - "Section": "Web development", - "Speaker Info": "My name is Hiren Patel. I am working at Aubergine solutions pvt ltd and I have been doing full stack web development there from last 2.5 years. While working on some web projects, I have always focused on learning django in more detail and try to optimize APIs to return response faster", - "Speaker Links": " Github: https://github.com/hirenalken LinkedIn: https://www.linkedin.com/in/hiren-patel-046672ab/ StackOverFlow: https://stackoverflow.com/users/3553279/hiren-patel?tab=profile Medium: https://medium.com/@hirenpatel_38103 I had presented a talk on this same topic in meetup organised by Ahmedabad based meetup group. here is the link to meetup: lin", + { + "Content URLs": "https://docs.microsoft.com/en-us/python/api/overview/azure/?view=azure-pytho", + "Description": "Python SDK for Azure is natively available. We would explore how this SDK can be used for automation and management of Azure. Python makes it easier for IT Pros and Developers to build a rock solid DevOps pipeline with simple script", + "Last Updated": "28 May, 2018", + "Prerequisites": "Basic understanding of Azure or any cloud\nBasic Python knowledg", + "Section": "Developer tools and Automation", + "Speaker Info": "Wriju works for Microsoft as Cloud Solution Architect. He is with Microsoft for more than 13 years and total of 17 years of industry experience. He is one of the first to play with Azure in its very early stage back in 2008. His day to day job is to help a big Oil and Gas Enterprise to adopt cloud as the strategic platform. His key area of focus is to help customer migrate their line of business applications to Microsoft Azure. Application modernization is another aspect. This involves designing and implementing Serverless workflow and Microservices. He helps Architects to design and implement the solutions which are cloud scale", + "Speaker Links": "Twitter handle: @wrijugh\nBlog: https://blogs.technet.microsoft.com/wriju\nLinkedIn: https://www.linkedin.com/in/wrijughosh", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Wriju Ghosh (~wriju)", + "created_on": "28 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-and-automating-azure-with-python~eXXve/", + "title": "Managing and Automating Azure with Python" + }, + { + "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", + "Description": "Artificial Intelligence is spreading in the modern world and it has changed the face of technologies in past several years, especially Information technology. Today we are much engaged with using and developing so-called intelligent computing systems and devices. This paradigm has evolved in many sub-areas likewise Machine Learning, Deep Learning & Neural Networks. These sub-areas of AI have a greater role in solving Vision problems( e.g. image recognition, object & activity detection etc.), Speech problems( e.g. ASR, trigger word detection, language translation etc.) and many more complex problem domains with help of robust algorithms & models. this talk will be focused on Sequence Neural Models used for solving the Speech and text problems and we will be introduced to real-world applications. topics covered during the talk Introduction Recurrent Neural Networks Word embeddings Attention Models(Trigger word detection) Real World Applications", + "Last Updated": "29 May, 2018", + "Prerequisites": "Machine Learning\nBasics of Neural Networks\nPython Programming Machine Learning( Basics) Basics of Neural Networks Python", + "Section": "Data science", + "Speaker Info": "The speaker, Prashant Kumar Rai, is a final year M.C.A. student at Department of Computer Science (Pondicherry University, Puducherry) who has been working on Machine Learning and data science for quite a while. he pivoted from C to Python in his first year of Master's and currently using this for his projects. He used to blog at his leisure time. Prashant is also a course mentor for 'Sequence Models' part of Prof. Andrew Ng' s Deep Learning Specialization on Coursera, where he helps learners who need in-course assistance and feedback to successfully complete a course", + "Speaker Links": "Github Twitter Quora LinkedIn Mediu", "Target Audience": "Beginner", "Type": "Talks", - "author": "Hiren Patel (~hirenalken)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/efficient-use-of-django-orm~b8gja/", - "title": "Efficient use of Django ORM" + "author": "PRASHANT KUMAR RAI (~pkraison)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/follow-the-sequence-in-deep-way-introducing-sequence-models~bYYAb/", + "title": "Follow the Sequence in Deep way - Introducing Sequence Models" }, - "82": { - "Description": "This workshop is dedicated to discuss and extrapolate on the core of Object Oriented Programming its finer details and nuances. The objective of the talk is to introduce concepts that will ensure OOP becomes second nature to a programmer. What you will gain after this session Detailed overview of Object Oriented Programming Intuition on the finer nuances of Object Oriented Programming. Tips on keeping the OOP code clean and readable. Expanding your horizon by understanding some lesser known concepts in Python. The session will focus on the following aspects with examples Inheritance and everything about it. Method Resolution Order Method Types Custom Base Object, Collections, and Dict Objects Extending Built-in Types Data Models Meta Classes and where they help Decorator and Class Decorators. Factory Design pattern Singleton Things to remember while writing code Conclusion", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic Python syntax Some understanding of Object Oriented Programming", + { + "Content URLs": "Slides Repositor", + "Description": "I'll be sharing how Python has been of help in my transformation from a hobby developer to a researcher.\nCoding and in particular, simulations are used extensively in the field of research to verify results and sometimes serve as experiments when it is physically not feasible. I'll describe step by step, how to design a real-time simulator using the example of an aerial swarm of drones in a survivor rescue scenario with the help of common Python libraries", + "Last Updated": "29 May, 2018", + "Prerequisites": " Basic understanding of Python classes and objects Enthusiasm to learn something new Love for Python", "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", + "Speaker Info": "Aniq Ur Rahman, Final year undergraduate student from NIT Durgapur. Summer '18 Research Intern at CERN GSoC '17 Intern at RoboComp Summer '17 Research Intern at SWAN Labs, IIT Kharagpur", + "Speaker Links": "Linked In Blo", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Aniq Ur Rahman (~Aniq55)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-research~eZGQa/", + "title": "Python and Research" + }, + { + "Content URLs": "https://github.com/hasura/gitkub", + "Description": "Gitkube is an open-source project that brings the developer experience of Heroku, on your own kubernetes vendor within 60 seconds . This means that you can take your python app, deploy it with a git push & scale it massively all on infrastructure you own at a fraction of the cost on Heroku. After a brief introduction, this talk will be a live-coding demo + tutorial. \nAudience members are encouraged to bring their own laptops with python apps and follow along in the talk to deploy their app. Permitting time, the talk will cover how gitkube works and how developers can contribute", + "Last Updated": "29 May, 2018", + "Prerequisites": "Python\nGi", + "Section": "Developer tools and Automation", + "Speaker Info": "Tanmai runs a startup, Hasura, where they're building tools to make it easier for developers to move to GraphQL and Kubernetes. \nThey were early adopters in the container ecosystem (pre-1.0 adopters for both Docker and Kubernetes) and have grown and contributed to the ecosystem as a company especially in India. Before this, Tanmai ran a consulting firm where their work included everything from MVPs for startups to helping one of the largest banks in the world migrate from legacy monoliths to containerised microservices. Tanmai has been building applications for over 8 years with a variety of frameworks. He is a firm advocate of democratising the power to develop applications and is the proud teacher of one of the largest tech MOOCs in India, imad.tech", + "Speaker Links": "Kubecon talk on gitkube: https://www.youtube.com/watch?v=gDGT4Gf_4JM Hasura: https://hasura.io LinkedIn: https://www.linkedin.com/in/tanmaig/ Twitter: https://twitter.com/tanmaig", "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Tanmai Gopal (~tanmai)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demo-tutorial-git-push-to-deploy-your-python-app-to-kubernetes-heroku-style~e1pZd/", + "title": "Demo + tutorial: Git push to deploy your python app to kubernetes - heroku style!" + }, + { + "Content URLs": "Content will be shared on github after the workshop. I will share detailed plan for the workshop in a while for the review", + "Description": "Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero ( https://deepmind.com/blog/alphago-zero-learning-scratch/ ). \nOpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms. In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding. Content Introduction to Reinforcement Learning (~ 15 mins) Introduction to Reinforcement Learning algorithms (~ 15 mins) Setting up OpenAI Gym and other dependencies Implementing simple algorithm using one of the atari games from OpenAI Gym (~ 1 Hr 15 mins) Quick overview of deep reinforcement learning and important papers in the area (~ 15 mins)", + "Last Updated": "29 May, 2018", + "Prerequisites": "Participants must be well versed with python. Some exposure to analytics libraries in python such as numpy, pandas, keras, tensorflow, pytorch would help", + "Section": "Data science", + "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company. I have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures. Since past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", + "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", + "Target Audience": "Advanced", "Type": "Workshops", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-object-oriented-programming~e7MQb/", - "title": "Advanced Object Oriented Programming" + "author": "saurabh1deshpande", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-reinforcement-learning-using-openai-gym~b2qMa/", + "title": "Introduction to reinforcement learning using OpenAI Gym" }, - "83": { - "Content URLs": "Will be sharing soon", - "Description": "Your introduction to concurrent programming in python. This talk is dedicated to a developer to enable him/her get started in asynchronous programming. The contents that will be covered in the discussion are as follows. What is asyncio? Why should we bother? Multi Threading vs Multiprocessing vs asyncio understanding the differences. All about what an event loop is with examples Futures Tasks and coroutines Streams Multiple Coroutines. Scheduling Calls Synchronization primitives Queues Working Example with a few notes on sockets and summary. The talk provides preliminary insight and a simple explanation to programmers who wish to explore asyncio and/or concurrent programming. ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Basic understanding of python syntax. Some OS concepts like differences b/w multiprocessing and multithreading. Understanding UNIX (not mandatory).", + { + "Content URLs": "I'll be sharing the slides after my talk as a Github repository. Soon will be sharing a gist", + "Description": "Abstract One of the feature people love about Python is how it\u2019s dynamically typed. A lot of people are very reluctant on hearing this idea of static typing, they will come back bashing on what's the use of Python then when we introduce static typing in it. With the torch bearers of Python in the industry like Google, Quora, Instagram, and a lot of others retaining their stack on Python and introducing static checking there have to be some non-superficial benefits, which are worth discussing. This is Python class Employee(NamedTuple):\n name: str\n id: int = 3\n\ndef fib(n: int) -> Iterator[int]:\n a, b = 0, 1\n while a < n:\n yield a\n a, b = b, a+b Contents of the talk What's static typing Need of static typing Static typing in Python 3.6 Type checkers Demo mypy vs pytype Pros and Cons QnA and discussion", + "Last Updated": "29 May, 2018", + "Prerequisites": "Basic Python knowledge and a little overview of what is dynamic and statically typed languages", "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", + "Speaker Info": "Harshil Rastogi is working as a backend software engineer @Innovaccer, previously he has worked as an NLP Scientist @Evalueserve", + "Speaker Links": "Find me on github , ohh you like QnA forums stackoverflow . Oops were you looking for a professional platform? Okay, LinkedIn it's", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-asyncio~b6MOa/", - "title": "Introduction to Asyncio" + "author": "Harshil Rastogi (~harshil9968)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/static-typing-with-python-what-why-and-why-not-to~e3rAd/", + "title": "Static typing with Python. What? Why? and Why not to." }, - "84": { - "Content URLs": "Part 1 Part 2 Github Rep", - "Description": "Websites and blogs have become a common trend amongst professionals to display not just their resumes but also their daily work items. Static blog generators have gained popularity over the last few years . People who have been using Wordpress, Blogspot or Blogger are now shifting to Pelican , Jekyll etc. One major annoyance was that Wordpress had a huge attack surface. Everytime someone found out a Wordpress exploit, your site was at risk. When comparing Blogger vs Pelican, the Slant community recommends Pelican for most people. In the question \u201cWhat are the best solutions for a personal blog?\u201d Pelican is ranked 10th while Blogger is ranked 14th. Python is becoming more and more popular amongst programmers and so is Pelican . \nPelican is a static blog generator and supports several formats like Markdown , ASCII etc . It turns Markdown and some Jinja templates into the Full Stack Python site. Its beauty lies in its simplicity and even a non programmer can get started with Pelican in just a few lines of code and plain text . Over the past few years people have shifted from Wordpress to Pelican .This is because a static site has basically no attack surface, and can be hosted on free or inexpensive hosts like Github Pages .\nThis talk is focused on introducing a simple static site generator to beginners and even avid bloggers who aren't coders . This talk will cover:- Basic installation of Pelican Writing a blog post with Pelican Changing themes of a blog/site Comparison between Jekyll and Pelican The main aim of this talk is to familiarize people with the concept of edifice . I have met a lot of non coders who have asked me about creating a basic website for personal use . This talk is also targeted to all those you are interested in blogging and everyone out there has something to say and something to blog ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "Absolutely nothing ", + { + "Content URLs": " https://fasttext.cc/ https://github.com/PacktPublishing/Learn-fastText https://github.com/facebookresearch/fastText/tree/master/python", + "Description": "FastText has been open-sourced by Facebook in 2016 and with its release, it became the fastest and most cutting edge library in Python for text classification and word representation. It is to be seen as a substitute for gensim package's word2vec. It includes the implementation of two extremely important methodologies in NLP i.e Continuous Bag of Words and Skip-gram model. Fasttext performs exceptionally well with supervised as well as unsupervised learning. The tutorial will be divided in following four segments : 0-10 minutes: The talk will begin with explaining common paradigms that are present right now. Are deep learning really necessary? 10-15 mins: what are word representations 15-25 minutes: The code will be shown and explained line by line for both the models (CBOW and Skip-gram) on a standard textual labelled dataset. Showing how you can do fast prototyping with minimal code. 25-30: How to use the pre-trained word embeddings released by FastText on various languages and where to use them. Why python3 is the best language for multi-language support and a note on general deep learning using fasttext. 30-40 minutes: For QA session. ", + "Last Updated": "29 May, 2018", + "Prerequisites": " Basic python knowledge. Some Knowledge on common NLP techniques.", + "Section": "Data science", + "Speaker Info": "Joydeep is a machine learning engineer/python developer and is a Principal Engineer at Nineleaps. 5 years back he saw the Zen of Python, fell in love with Python and has been in love with it since then. Apart from his day to day work is involved in blogging and podcasting on medium and flawcode. Teaching is another passion of his and he is a python/ML trainer at tecmax", + "Speaker Links": " Medium: https://medium.com/@joydeepubuntu/latest Github : https://github.com/infinite-Joy LinkedIn : https://www.linkedin.com/in/joydeep-bhattacharjee-934a1157/ Machine Learning Podcast: https://flawcode.com/episode/show/12 twitter: https://flawcode.com/episode/show/12", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Joydeep Bhattacharjee (~infinite-Joy)", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cutting-edge-nlp-classifiers-in-one-hour-with-python-and-fasttext~b4v7e/", + "title": "Cutting edge NLP classifiers in one hour with Python and fastText" + }, + { + "Content URLs": "https://docs.google.com/presentation/d/1PZ56AYSH6GZ8s-V8rfxHuZ16UCmDg03Y1L2EiTCBiUs/edit#slide=id.p \n(Subjected to changes, not final one)", + "Description": "Talk is about how python is useful in web development, what are the most powerful and popular python frameworks used i.e., Django, Pyramid, Flask and how they are used in making web applications. My talk covers : What a web framework means Why to choose python frameworks over the normal other frameworks Explanation on Django, Pyramid, Flask. Which framework should be chosen based on dependencies. Starting Web development with python. Django, Pyramid, Flask will be explained in short with the help of small code snippets. Examples of organizations using these frameworks will be given. Uses of one framework over the other will be told in detail", + "Last Updated": "29 May, 2018", + "Prerequisites": "No prerequisite is required. Desire to learn is enough to attend this talk", "Section": "Web development", - "Speaker Info": "Anumeha Agrawal is a Pythonista and an open source enthusiast . She is in her third year of undergraduate program in Information Technology at NITK Surathkal . She is also a Google Summer of Code 2018 student at Systers . In her project at Systers , she has used python to write scripts to retrieve data from GitHub API and use it in her MEAN stack project . She uses python scripts to simplify most of her work like API data collection and web scraping . Python was the first language she was introduced to when she began programming and it is her weapon of choice . Owing to the simplicity of python syntax, she also used python to code her algorithms for her talks and workshops at college . Apart from being a full stack developer ,she is also a Data science enthusiast and employs python for designing most of her Deep Learning models and algorithms ", - "Speaker Links": "Link to Github Link to Linkedin Profile Link to Medium Blog Link to GSoC projec", + "Speaker Info": "About Me I am Jameer, a third year Computer Science and Engineering undergrad at Amrita Vishwa Vidyapeetham, Kerala, India. I love to code in Python. So, I started my open source career by contributing to Coala organisation. Due to my open source enthusiasm, I started learning how python is useful in Web development and using Django, Flask etc., I am also an OSFY author and published an article related to how Hadoop is being used in Big Data Analysis. I am also a ACM-ICPC Regional participant at Amritapuri. I also have a keen interest in Chatbots", + "Speaker Links": "https://github.com/JameerBabu https://www.linkedin.com/in/jameer-babu-0199a2137", "Target Audience": "Beginner", "Type": "Talks", - "author": "Anumeha Agrawal (~anumeha)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pelican-magic-for-beginner-bloggers~e5MYe/", - "title": "Pelican - Magic for beginner bloggers" + "author": "Jameer", + "created_on": "29 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-web-development~e5wYb/", + "title": "Python - Web Development" }, - "85": { - "Content URLs": "http://click.pocoo.org (Cool power-point and Github repo coming up", - "Description": "Who hasn't used Git in the terminal? An absolute beast of a tool. But did you ever have an idea to build your own cool Command Line tool for something you believed could simplify life for other devs but you didn't because you were too lazy to research? Worry not! I present to you Click! Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It\u2019s the \u201cCommand Line Interface Creation Kit\u201d . It\u2019s highly configurable but comes with sensible defaults out of the box. In this talk, I'll go through the process of designing a simple (or complex) Command Line Interface called thanos which tells you whether you survived the SNAP or not. I'll be taking you through the process of designing, building and publishing our thanos package. We'll then upload it to the Python Package index so that you can do pip install thanos from any system worldwide and find out if you perished or not. Outline What is a CLI ? Building our own CLI called Thanos , to find out whether you survived the snap or not. >>thanos snap\n You didn't make the snap. Creating complex commands using beautifully decorated code. Exploring arguments, flags and options within the CLI. What's PyPI, and why do we need it? Uploading your new Thanos package to Python Package Index. QA", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Should have seen or used a terminal before. (Mandatory) Basic Python knowledge preferred.", - "Section": "Developer tools and Automation", - "Speaker Info": " Adarsh is a visionary who strives to build amazing tools for people. He is currently pursuing bachelors in CSE. Currently he is Google Summer of Code Intern at CloudCV , an organisation which works on making reproducible AI research, where he is building a versatile CLI for EvalAI project. He was one of the youngest speakers at FOSSASIA International Summit 2018 in Singapore for his work on Python based NLP POSTagger. Worships Open Source software and have contributed to multiple organisations like FOSSASIA, Zulip where he was also a mentor for Google Code-In 2016 .", - "Speaker Links": "https://www.youtube.com/watch?v=TzIr9THCUJg https://2018.fossasia.org/event/schedule.html#s-4267 https://github.com/isht3/ https://www.linkedin.com/in/guyandtheworld", - "Target Audience": "Beginner", + { + "Content URLs": "I will share the slides after my talk as a Github repository", + "Description": "If you are working in the field of research than you might be wondering about symbolic solutions which must be needed while working in such arduous fields like Mechanical Engineering or Computer Science or Quantum Mechanics. Sympy is the solution for that. Sympy deals with the computation of mathematical objects symbolically. This means that the mathematical objects are represented exactly, not approximately, and mathematical expressions with unevaluated variables are left in symbolic form. This talk will cover Introduction and Uses of Sympy Library", + "Last Updated": "30 May, 2018", + "Prerequisites": "Basics of Python is good. \nDon't know Python? It's still okay. You will definitely find something new", + "Section": "Core python and Standard library", + "Speaker Info": "Nikunj Parmar is a Sophomore year student at Nirma University. His major field is Flexible Robotics. He has been working with Python for last 2 Years as a Researcher. As a Junior Undergraduate student, He has worked on many projects focused on Robotics, Machine Learning, and Core OS Programming. His interests lie in the fields of Robotics, Design and Control Engineering, Computational Engineering, and its applications in a broad range of circumstances", + "Speaker Links": "https://www.linkedin.com/in/nikunj-parmar-b87739138/ https://github.com/nikunjparmar82", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "isht3", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-your-own-command-line-application-and-upload-it-to-pypi~b427e/", - "title": "Build your own Command Line Application and upload it to PyPI!" + "author": "Nikunj Parmar (~nikunjparmar828)", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sympy-symbolic-computation-with-python~b6xOe/", + "title": "Sympy : Symbolic Computation with Python" }, - "86": { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "In today's Era, the IT sector is moving more and more towards automation. Now every company is trying to provide its users with the facility to perform their task without the need for any human intervention.\nIn this talk, we are addressing a similar problem of automating the vehicle parking systems. Problem description: Automated license plate recognition(ALPR) is a well-known problem where we try to extract the license number from a cars number plate using machine learning algorithms. The scope of its real-world application ranges from highway toll plaza to automated parking and charging of future electric cars.\nThis problem has been targeted with a variety of algorithms like traditional template matching to advance deep learning algorithms like YOLO . Here we will be presenting a combination of little template matching clubbed with some deep learning to solve this problem in the most simplistic way", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations", + { + "Content URLs": "https://github.com/aj-jeste", + "Description": "Google Cloud Platform Deployment Manager (GCP DM) allows you to codify your infrastructure with minimal setup, just need to download the gcloud library and you're off to the races. While its simple to get started with GCP DM, its a whole 'nother ball game to write extensible and reusable DM code. In this talk I will show you how to scaffold your code into two distinct groups: configs and templates. By separating these out you can reuse the same templates across multiple deployments with different configs and make your codebase a little bit smaller. How to write a basic DM deployment. Convert the basic DM deployment into a template. Launch multiple deployments with different configs but same template. Create custom helper functions in DM Best practices when using DM", + "Last Updated": "30 May, 2018", + "Prerequisites": "Understanding of Google Cloud Platfor", "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal", + "Speaker Info": "As a freelance Site Reliability Engineer and Cloud Architect, AJ has traveled all over the world helping startups setup and manage Cloud infrastructure. He has also architected and deployed large Hybrid on-prem/cloud infrastructure for existing well established companies that wanted a taste of the cloud but needed to keep their physical data-centers as well. This is his 11th year as a SRE/CA and has automated, scaled and monitored infrastructure anywhere from 150 to 3500+ nodes, both physical and virtual. Currently he is looking for his next challenge, perhaps its this pycon talk. Brought up and currently lives in New York City but travels all over the world in search of the best train journeys and awesome foods which seems to bring him back to India again and again", "Target Audience": "Beginner", "Type": "Talks", - "author": "Saqhas", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-license-number-recognition-in-python~e33Ae/", - "title": "Automated License number recognition in python" + "author": "aj", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-cloud-platform-deployment-manager-scaffolding~b8zje/", + "title": "Google Cloud Platform Deployment Manager Scaffolding" }, - "87": { - "Content URLs": "Would update soon after feedback", - "Description": "Most machine learning algorithms require feature vectors as inputs. In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object (image, text, sound). Feature engineering, the practice of extraction of features from objects is a combination of art and science; it requires the experimentation of multiple possibilities and automated techniques with the intuition and knowledge of the domain expert. Automating this process is called \"feature learning,\" where a machine learns the features itself. One way to obtain features is to use the 'Bag-of-Features' model, the idea behind which is to simplify object representation as a collection of its subparts. Originally used for representing text data, the \"Bag-of-Words\" methodology can be extended to different types of objects resulting in models such as \"Bag-of-Visual-Words,\" \"Bag-of-Audio-Words.\" The significance of these models in the age of self-learning deep networks still holds because of their ability to work with limited data. The contents of the talk are: Introduction to Feature Engineering Working with Text Data Understanding 'Bag-of-Words' Example: Text Classification Working with Image Data Introduction to 'Bag-of-Visual-Words' Example: Image Classification Comparing the performance to CNN Overview of 'Bag-of-Audio-Words' Generalizing 'Bag-of-Features' This talk primarily discusses Bag-of-Words, Bag-of-Visual-Words through an example of text classification and image classification respectively. It also covers the concepts that generalize to models other than Bag-of-Features. The goal is to acquaint the audience who have previously worked on numeric data with some ideas to get started with text and multimedia data", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Intermediate knowledge of Python Familiarity with classification problems Familiarity with basic NLP/CV is helpful (but not necessary)", - "Section": "Data science", - "Speaker Info": "I'm a fresh graduate in Computer Science & Engineering. I am passionate about Data Science, and I spent most of my time learning about skills required to excel in the domain. Outside of my professional interests, I am fond of rock music and reading", - "Speaker Links": " Blog: https://pranavsuri.com GitHub: https://github.com/pranavsuri LinkedIn: https://linkedin.com/in/suripranav Twitter: https://twitter.com/pranav_suri", + { + "Content URLs": " https://github.com/errbotio/errbot http://errbot.io/en/latest/", + "Description": "The wikipedia definition of ChatOps is, a collaborative, conversation-centric way of working that brings people, discussions, bots, tools and files together in one central location: the workplace messaging app. That's it! That's what exactly I am gonna talk about. I am gonna talk about Chatops bot, Errbot which is written in python and can be used across various messaging apps like Hipchat, Slack, telegram, skype, etc. Using chatops one can automate the tedious, boring tasks and let the bot do the work for you. It also enables various engineering teams to collaborate and exchange information easily at one place: their official messaging app. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce chatops - culture, uses, possibilities. I will talk about the possible scenarios where we could use chatops in our daily tasks. I will then introduce Errbot and its plugin architecture. Tell audience about various features of errbot and its builtin plugins. Demonstrate errbot to audience by creating a command and using it in Slack. How to set up a alternate storage for errbot. I will conclude the talk explaining the ACLs(Access control List) in errbot.", + "Last Updated": "30 May, 2018", + "Prerequisites": " Basic Python Passion for automation Will to learn", + "Section": "Developer tools and Automation", + "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", + "Speaker Links": "https://www.linkedin.com/in/hari95kishore", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Pranav Suri (~pranavsuri)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bag-of-features-representing-text-image-data-as-numerical-vectors~b2XMe/", - "title": "Bag-of-Features: Representing Text & Image Data as Numerical Vectors" + "author": "hari95kishore", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatops-using-python-bringing-developers-and-operations-together-making-tasks-easier~e9AJe/", + "title": "Chatops using Python - Bringing developers and operations together, making tasks easier!" }, - "88": { - "Content URLs": "https://github.com/Laneone/askfm-pytho", - "Description": "Hey everybody! Ever tried to webscrape? Ever faced a \"No robots allowed! No web scraping allowed!\" message from a favorite site? This talk is for meant for you. Usually when you're done building a fancy web scraper and begin running the homebrew'd tool on your favorite site there's chances you'll face a block on your IP address preventing your computer from accessing more resources and therefore downloading the contents of the website. Your tool maybe fast, it might be scalable, it might be the best written scraper out there, but with just one IP address under your belt, it's easy for giants to block your ip address and prevent you from getting that precious data, especially if you've built a threadsafe and multi-node webscraper. Enter The Onion Router, The ToR project, allows you to use the the internet vis-a-vis a proxy and visit the same website under a different endpoint ip address, but that's just for one instance of ToR. What if you ran, say 200? at once? 200 ip addresses > 1 ip address. With 200 endpoints and the latest update to the requests library, you can now use your multi-threaded and resource hungry webscraper and it can(not) be stopped! Whatever your rate of data collection, you can 200x it! The stack is simple, you open a SOCKS5 proxy per ToR endpoint, connect it to a request with it's own port number and you're good for that one request, same for multiple requests. You can build a task scheduler to orchestrate the url to scrape and the port number the tor endpoint is on and have the entire application running on a cloud service provider to ensure you face no bandwidth issues. The demo centered around the talk will attempt to rapidly and quickly scrape users from the famous social network Ask.fm which is known to restrict users from retreiving from their site if you attempt to download more than 4 users in under a second, but with the hack in place, you'll be retrieving close to maximum efficiency on a DigitalOcean droplet , but this can be applied to virtually any website and any cloud provider. Never pay for webscraping again! Thanks and see you at PyCon! \n-Lokesh Poovaraga", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic concepts of web scraping, Regex, Task scheduler, ports and proxies", + { + "Content URLs": " https://www.djangoproject.com/ http://www.celeryproject.org/ https://sensu.io/", + "Description": "Monitoring is a key aspect for any business. It enables us to find and be notified about the problem way ahead our customer notices it, which enables us to keep our businesses running and making customers happy. I will be talking about how we SREs at Opentable Inc, tries to solve the good old monitoring problem, sensu with puppet, using Django, Sensu and Celery. If you are fed up with the limitations of what current monitoring tools offer, this is the talk you wanna look out. At the end of talk, audience would have an alternative approach for monitoring using python. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce monitoring and how we use currently at Opentable Inc. Describe limitations we have with our previous monitoring stack. Alternate new generation monitoring architecture using python tools Django and Celery, keeping sensu intact. How we developed a site using Django, which help us to maintain the checks and add new check definition. How we used Celery distribution system to run checks on multiple worker nodes and send results to sensu. I will talk about how we scaled celery worker nodes by setting up different queues, and prioritising the tasks and by using Flower.", + "Last Updated": "30 May, 2018", + "Prerequisites": " Basic knowledge of Sensu. Basic knowledge of Django and Celery. Will to learn", "Section": "Developer tools and Automation", - "Speaker Info": "Hi I'm Loki! (Lokesh Poovaragan) A full-stack developer from Dayananda Sagar, Bangalore, and I love to code in python! In my free time I love to web scrape and gather good amounts of public data and encompass them into json format for data(sentiment) analysis. I also build prototypes of interesting combinations of technology to solve unique problem statements. I love exploring new and interesting areas of work and I love to play with code", - "Speaker Links": "Blog: http://laneoneblog.blogspot.in GitHub: http://github.com/Laneon", + "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", + "Speaker Links": "https://www.linkedin.com/in/hari95kishore", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "hari95kishore", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-infrastructure-and-application-using-django-sensu-and-celery~e0o5d/", + "title": "Monitoring infrastructure and application using Django, Sensu and Celery." + }, + { + "Content URLs": "The Magenta Project Music Composition using Recurrent Neural Network", + "Description": "Music is mainly an artistic act of inspired creation and is unlike some of the traditional math problems. But, a sequence of specific chords and notes can be observed when we listen to music. With the recent advancements of the AI tech, sequence models are used invariably in innumerous fields, one such sequence model, LSTM( Long Short Term Memory Networks) can be used to generate melodies and beats. So, this talk is about how deep learning models, specifically LSTMs were used to produce music - catering particularly to the Electronic Dance Music Industry. CONTENTS AND ORDER OF THE TALK Learning how LSTMs help in generating music, and the concepts behind it. Preprocessing the MIDI data for the melodies and beats using MIDI packages created by the Python community. Building the LSTM network using Keras with Tensorflow as backend and understanding it. Train the network with the melodical data to create the LSTM network for melodies and same thing for beats. Generating melodies and beats(using pretrained model) and combining the two to create different type of genres of music. I am including a piece of music generated by an MIT alumnus, but I will be explaining the steps from scratch . Generated Techno Beat", + "Last Updated": "30 May, 2018", + "Prerequisites": "Tensorflow, Keras, Recurrent Networks and a Good taste in music ;", + "Section": "Others", + "Speaker Info": "I am Kumar Abhijeet, a sophomore from RV College of Engineering, Bengaluru and an AI enthusiast. I am a budding EDM producer and a python programmer as well(no doubt in that). I have worked with small AI startups in building their frameworks. I am an open source contributor and a GSOC aspirant. I have always loved the idea of mixing technology with regular phenomena, which I will be doing with music. I love going to meetups and meet different kinds of communities to learn from them", + "Speaker Links": "LinkedIn ID Github Lin", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kumar Abhijeet (~kumar80)", + "created_on": "30 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-beats-and-melodies-with-lstms-using-python-and-tensorflow~ejgya/", + "title": "Generating beats and melodies with LSTMs using Python and Tensorflow" + }, + { + "Content URLs": "To get a feel of Numba see - first step", + "Description": "Thinking parallel is an art, applying it is another. While applying it, the first hurdle for us is to move to another language like C or C++ to get performance gains. \nWhat if we write simple python code and someone magically helps us gain C like performance? Sounds like a dream, it ain't ! . Enter Numba :) In this workshop you will - Witness how Numba help you get insane performance gains to your code without changing a line of it. Learn to harness the power of your GPU/CPU for performing math intensive computations. See how it compares to other libraries like Numpy , etc. and how they can complement it. Use Numba to parallelize the very famous Particle Swarm Optimization Algorithm Flow of the workshop - Where to use Numba in your code - (time profiling, small examples) The wow of Numba in my life, a small example of how it helped in my research Introduction to jit complier, internals of Numba Introduction to the Particle Swarm Optimization (this is where the fun starts :) ) Code up basic PSO Profile PSO to find pain areas Try to speed up the pain areas using Numba Kick up a hierarchical swarm (just for fun, if time permits) QA Session", + "Last Updated": "31 May, 2018", + "Prerequisites": "numpy, matplotlib, jupyter, ipython, numba, line_profiler , llvmlite. A more specific description is available her", + "Section": "Others", + "Speaker Info": "Hi, I am Shubham Bhardwaj. I am currently a Research Intern at Jio CoE for AI/ML and a final year undergrad at VIT University, Vellore. I am a die-hard pythonista. \nMy daily work involves developing and implementing algorithms for interesting problems in AI. Apart from this I am also an organizer at GDGVIT, I love dev :) and contribute to various open source organisations, organise workshops, promote python whenever I can", + "Speaker Links": " LinkedIn Github", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Shubham Bhardwaj (~shubham0704)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/leveraging-the-power-of-your-gpucpu-for-math-intensive-computations-with-python~bkjJa/", + "title": "Leveraging the power of your GPU/CPU for math intensive computations with python" + }, + { + "Content URLs": "https://github.com/radhikascs/cryptography-pytho", + "Description": "This talk is meant for the end users who aspire to learn basics of cryptography and its implementation in real world projects. \nThis tutorial is also useful for networking professionals as well as hackers who want to implement new frameworks instead of following traditional approach", + "Last Updated": "31 May, 2018", + "Prerequisites": "It is expected that the end user should know basics of cryptography and algorithms. The knowledge of cryptography algorithms becomes a cakewalk for a user who reads this tutorial", + "Section": "Core python and Standard library", + "Speaker Info": "A pinch of optimism with a blend of hard work and focus defines Radhika Subramanian. She works as an Academic Writer and Tutor with various organizations. She has completed MSc(CA) from Symbiosis International University. She also includes a passion for research work in Artificial Neural networks and it's technologies. She is currently working as an Author with BPB Publications and Apress Media LLC", + "Speaker Links": "https://www.linkedin.com/in/radhika-subramanian-486a771a/ https://www.unanth.com/tutor/radhika-subramanian-14135", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Laneone (~Laneone)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-intermediates-guide-to-theoretically-unlimited-webscraping-with-python-using-requests-lxml-tor~e1MZe/", - "title": "A Intermediate's Guide to (theoretically unlimited) WebScraping with Python using Requests & lxml & ToR" + "author": "Radhika Subramanian (~radhika14)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cryptography-and-python~elkjd/", + "title": "Cryptography and Python" + }, + { + "Content URLs": " Postman Jmeter Burp", + "Description": "API testing is fun! For a small team of 7 (Dev + QA), having dedicated resources to do functional, Security and Performance of the APIs is close to impossible.\nHence, We came up with a framework which automates the process of API testing covering the basic functionality, Security, and Performance so that we don't miss out testing any of these layers. I would cover up the basics of Postman, Burp and JMeter components used for the framework", + "Last Updated": "31 May, 2018", + "Prerequisites": " Interest in automating the Webservices testing :)", + "Section": "Developer tools and Automation", + "Speaker Info": "A tech enthusiast who has 7+ years of experience in the Software Testing in Startups. I love to explore new technologies and automate mostly everything which takes more time. A strong believer in processes. Love testing Webservices. Would love to share the experience we had in building the framework for API testing", + "Speaker Links": "https://www.linkedin.com/in/sarala-v-620b0b1a/ https://twitter.com/saralaVeerann", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Sarala V (~sarala)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-rest-api-testing-for-functional-security-and-performance-testing~bmkRe/", + "title": "Automating REST API testing for functional, security and performance testing" + }, + { + "Content URLs": "Slides: https://docs.google.com/presentation/d/1z-pWhSOERi-vl_wPLVsdCNpl54G3IA0D8K7ve13HFZI/htmlpresent Source code for the examples: https://github.com/minhajuddin/collaborative-canvas-demo", + "Description": "Outline/structure of the Session\n1. An introduction to Elixir\n2. An introduction to Phoenix\n3. Outline and design overview of our canvas app\n4. Implementing our app\n5. Deploying it to a server\n6. Q&A Learning Outcome\nLearn how easy it is to use Elixir and Phoenix to create real time applications at a massive scale", + "Last Updated": "31 May, 2018", + "Prerequisites": "Basic understanding of the web applications", + "Section": "Web development", + "Speaker Info": "I am a very passionate programmer. I am also the CEO of a Micro ISV, Cosmicvent Software. I have been in the software industry for 10 years.I love writing code and have worked with Elixir, Golang, Ruby, .NET and Javascript among other technologies", + "Speaker Links": "Follow me on twitter https://twitter.com/minhajuddin Follow me on GitHub https://github.com/minhajuddin/ My Blog: https://minhajuddin.com/ Previous presentation: https://www.youtube.com/watch?v=WabGxSZhPE", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Khaja Minhajuddin (~minhajuddin)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-collaborative-canvas-using-elixir-and-phoenix~enl5b/", + "title": "Building a collaborative canvas using Elixir and Phoenix" + }, + { + "Content URLs": "https://www.py4e.com/\nhttps://www.coursera.org/specializations/pytho", + "Description": "This session will take a look at the \u201cPython for Everybody\u201d series of courses on the Coursera platform. This course has impacted over 1.3 million students over the last five years. We will look a the history and goals of the course and how the course works to create a learning community. We will show how the free open educational resources (OERs) and book associated with the course have been used by teachers, students, and courses around the world to form a network of educational activities centered around Python. We will also cover briefly the Tsugi (www.tsugi.org) software that is used to build the learning assessments and distribute the OER materials in a way that enables maximum reusability of the materials for other teachers", + "Last Updated": "31 May, 2018", + "Prerequisites": "No pre-requisite", + "Section": "Core python and Standard library", + "Speaker Info": "http://www.dr-chuck.com/\nhttps://www.si.umich.edu/people/charles-severance\nhttps://twitter.com/drchuck/\nhttps://github.com/csev\nhttps://www.sakaiproject.org\nhttps://www.tsugi.org\nhttps://www.slideshare.net/cse", + "Speaker Links": "http://www.dr-chuck.com/dr-chuck/resume/index.htm Charles is a Clinical Professor and teaches in the School of Information at the University of Michigan. He is the Chair of the Sakai Project Magament Committee (PMC). Previously he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project and worked with the IMS Global Learning Consortium promoting and developing standards for teaching and learning technology. Charles teaches ten popular MOOCs and two specializations to students worldwide on the Coursera platform: Internet History, Technology, and Security, Web Applications for Everybody, and Python for Everybody and is a long-time advocate of open educational resources to empower teachers. Charles was the editor of the Computing Conversations column in IEEE Computer magazine from 2011-2017 that features a monthly article and video interview of a computing pioneer. Charles is the author of several books including: Python for Everybody, Sakai: Building an Open Source Community\", \"Using Google App Engine\", from O'Reilly and Associates and the O'Reilly book titled, \"High Performance Computing\". Charles has a background in standards including serving as the vice-chair for the IEEE Posix P1003 standards effort and edited the Standards Column in IEEE Computer Magazine from 1995-1999. Charles is active in media as a hobby, he has co-hosted several television shows including \"Nothin but Net\" produced by MediaOne and a nationally televised program about the Internet called \"Internet:TCI\". Charles appeared for over 10 years as an expert on Internet and Technology as a co-host of a live call-in radio program on the local Public Radio affiliate (www.wkar.org). Chuck's hobbies include off-road motorcycle riding, karaoke and playing hockey. Charles has a B.S., M.S., and Ph.D. in Computer Science from Michigan State University", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Charles Severance (~charles)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/inside-the-worlds-largest-python-course-on-coursera~bomYe/", + "title": "Inside the World's Largest Python Course on Coursera" + }, + { + "Content URLs": "---In progress, will be ready to share by July last week can make it to July first week if urgent--", + "Description": "Signal processing is a fundamental part of ECE and is also used in many other fields. Students for years have been using expensive Matlab for learning this skill. The talk/workshop/interactive session can be used by students to get a better understanding of signal processing and implementing it with python. The use of python language in signal processing is preferred as it is portable, easily available and fast to deploy Topics covered include but are not limited to Sound and Signals Noise Fourier Transform Filtering Modulation Sampling LTI Systems The talk will be at a simple level so that even a high school student can understand signal processing and implement it. If time allows another session on using python to solve electrical networks and visualizing them can also be implemented", + "Last Updated": "31 May, 2018", + "Prerequisites": "Basic knowledge of python and Signals and systems (WikiPedia knowledge is enough.) NumPy (Used for array manipulation ) SciPy (For computation) matplotlib (For plotting various signals etc.)", + "Section": "Others", + "Speaker Info": " Speaker is a 3rd year ECE student with experience in python for numerical computations, web development and most importantly signal processing , and electrical networks Interested in using python in modern electronics like the pyboard and raspberry pi and advocates the use of python over expensive software. An avid python user, always tries to find a way to implement given task in python and believes that where there is a task to be done there is a suitable python library.", + "Speaker Links": "LinkedIn Faceboo", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Abel Joseph John (~abel91)", + "created_on": "31 May, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/digital-signal-processing-with-python-and-applications-in-audio~epnQb/", + "title": "Digital Signal Processing with Python and Applications in Audio" + }, + { + "Content URLs": "Kubernetes Docker Azure Kubernetes Service aka AK", + "Description": "Kubernetes is considered as the new Kernel of the Cloud. It's a distributed computing platform letting users not have to care about infra and helping them concentrate mainly on business logic. By having your web app deployed on a kubernetes cluster you can make sure your app is highly available, and can fail-over when there's a problem. One of the main goals of the Kubernetes project is to democratize distributed computing. With Kubernetes being open source, Companies do not have to redo the mundane task of writing a distributed computing platform to achieve high availability, automated deployment, scaling and management of your applications. Kuberentes will take care of that for you. Kubernetes is also considered as a container orchestrator, as it manages containers to achieve the above said goals. In this talk: We will first write a basic python web app. Next, We will go through what a container is Containers are becoming the de-facto way of deploying applications as they remove the complexities of dependency management,etc. Running apps on Individual Containers provide the isolation almost to that of a Virtual Machine without having the overhead of having individual Kernels as they all share the host kernel. Isolation is provided by using kernel level features like cgroups and namespaces. We will containerize the application using docker and push it to a Container Registry. Once we have the image deployed to a registry, this image will be used to create instances i.e containers of the web app. We will next create a kubernetes cluster on Azure, all along going through what a Kubernetes cluster is, and its components. We will then deploy our python web app onto the cluster. Now As we have our python web app up and running, We can then do some experiments on how Kubernetes self-heals the application when a node goes down,etc. After that I will run down some points on where Kubernetes is being\n used, its impact. To Finally answer the question, Is Containers and Kubernetes worth all the Hype ? This talk will be demo focused, But before going to a demo we will have some slides explaining the overview of the components and how they work. By the end of the talk, Audience will have a brief overview of what containers and kubernetes are, and how to deploy a web app on Kubernetes. From this overview, Audience can start digging deeper online and know more", + "Last Updated": "01 Jun, 2018", + "Prerequisites": "Understanding of Python. Basic Understanding of Deployment of a web app. It's good if you already have some basic understanding on what containers and kubernetes are", + "Section": "Developer tools and Automation", + "Speaker Info": "Tarun Pothulapati is currently pursuing his B.Tech in Computer Science and Engineering in Hyderabad.\nHe is a Tech Enthusiast and codes mostly in Python and C#. He is very much interested in distributed computing platforms like Kubernetes and Microsoft's Service Fabric which are trying to democratize \nthe technology which was before only a privilege of the Big-Tech firms.\nHe spends most of the time learning about it and trying to contribute to their repositories. He is also very enthusiastic about sharing the knowledge about these cutting edge technologies.\nTarun has also worked on many projects on chatbots, Web apps etc and have won some\nhackathons held by IEEE, IBM & Amazon and he was one of India's 40 finalists of AICTE's \nStartup Contest 2017", + "Speaker Links": "Twitter Github Linkedin Websit", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Tarun Pothulapati (~Pothulapati)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deploying-a-python-web-app-onto-a-kubernetes-cluster~bqo7e/", + "title": "Deploying a Python web app onto a Kubernetes Cluster" + }, + { + "Content URLs": "https://github.com/vivekaris/firebase-io", + "Description": "Now Days Internet of Things are Trending technology for every makers. Lets Build Python based Automation controller for any Hardware (tested on Raspberry Pi and Node MCU).\nWe will use firebase as a data storage and Action handling.\nWith the help of Firebase Realtime Database ,we can control hardware from any geographical location", + "Last Updated": "01 Jun, 2018", + "Prerequisites": " Keen to learn Basic of Python Knowledge of PIP Knowledge JSON Basic Knowledge of C for Arduino(Node MCU Programming) Laptop with Linux/Mac/Win 7 onwards. Node MCU v3 2 LED with 4 Jumper Wire Internet Connectivity Google Account enter code her", + "Section": "Web development", + "Speaker Info": "I am opensource tech lover", + "Speaker Links": " https://github.com/vivekaris https://twitter.com/vivdroid http://makerspacekanpur.com/blog/", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-firebase-build-amazing-iot-application~erp2b/", + "title": "\"Python and Firebase\" Build Amazing IoT Application" + }, + { + "Content URLs": "share here soon", + "Description": "Flutter is Google\u2019s mobile app SDK for crafting high-quality native interfaces on iOS and Android in record time. So lets create web services for Flutter app using python/Flask framework", + "Last Updated": "01 Jun, 2018", + "Prerequisites": " Basic of Python Knowledge of Webservices REST and JSON Hello world Knowledge of Mobile App. Familiar with Android Studio and Pycharm", + "Section": "Web development", + "Speaker Info": "I am opensource lover. I love to explore opensource technologies for mankind. I am organiser of \"Arduino and IoT ,Kanpur\" . I teach kids under coderdojo program", + "Speaker Links": " https://twitter.com/vivdroid https://github.com/vivekaris", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/write-python-web-services-for-flutter-app~avw8b/", + "title": "Write Python Web services for Flutter App" + }, + { + "Content URLs": "Programs in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=", + "Description": "Mention of \u201cCancer\u201d evokes words like tumor, chemotherapy, hair loss, vomiting and pain. Interestingly our knowledge and thereby cancer treatment has changed radically in the past few years and is changing rapidly every passing day. In 2003, human genome was sequenced and for the first time we could read entire human DNA from end to end. Interestingly DNA and cancer are deeply connected. Scientists deciphered that always a change in DNA (mutation) led to cancer (oncogenic mutation). Cigarette smoking, alcohol, pollution etc only led to such DNA change (oncogenic mutations). This led to numerous diagnostic companies starting to extract and sequence tumor DNA, to detect the root cause of each patient tumor. While drug companies formulated new drugs that targeted specific DNA change (mutation). These were called targeted therapies which were very different from chemotherapy in being very precise, less toxic, less side effects and they could be taken orally just like any regular pill. Thus, an oncologist (cancer doctor) could treat a cancer tumor effectively if s/he knew the precise location of mutation in the entire patient tumor DNA and the drug that targeted it. Suddenly oncologists in India and elsewhere, found themselves struggling to comprehend tumor DNA and the technology around it. Already burdened with tomes of ever changing patient treatment guidelines, now they were needed to integrate tumor DNA information to make accurate treatment decisions. For eg. NCCN (National Comprehensive Cancer Network, USA) which publishes treatment guidelines for all cancer for oncologists across the world, published lung cancer guidelines that is 271 pages long. To this, add the complex data of patient\u2019s tumor DNA, various mutation databases, clinical trials and research papers. Modern day oncologist are often overwhelmed. They need tools to simplify and hasten their decision making. I am a molecular biologist who understands the tumor DNA and the technologies around it. As Chief Scientist (molecular oncology) of Neuberg diagnostic lab, I also write patient DNA reports that guide oncologists to take treatment decisions. While meeting various oncologists and marketing them different DNA tests for different type of cancers, I got acutely aware of the problems oncologists faced. To simplify their decision making, I created algorithms that combined patient\u2019s clinical history, histo-pathology data, molecular test decisions, mutational databases and NCCN guidelines. Subsequently I coded these integrated and complex decision algorithms as Python programs that can be executed from a browser. They are available for free and oncologists are/can use it.\nPrograms in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=0 \nMy article on need of Python programing for cancer treatment: https://sites.google.com/view/molecularpathology/programming/is-it-time-for-precision-medicine-app?authuser=", + "Last Updated": "01 Jun, 2018", + "Prerequisites": "Interest in using programing to resolve healthcare problems in India", + "Section": "Others", + "Speaker Info": "I am a PhD in Biochemistry with significant research experience at the University of North Carolina at Chapel Hill, in the areas of molecular oncology, cardiovascular biology and biology of infectious diseases. Currently, I prepare molecular diagnostic reports for cancer patients as Chief Scientist (Molecular Oncology), Neuberg Center of Genomic Medicine, Ahmedabad", + "Speaker Links": " Molecular pathology of cancer: https://sites.google.com/view/molecularpathology/home?authuser=0 The DNA Labs: https://sites.google.com/site/thednalab/ , https://www.facebook.com/TheDNALab , https://www.youtube.com/channel/UCf2HKt1vgjhe8MXbvMSwELg/feed", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "siddharth srivastava (~siddharth40)", + "created_on": "01 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/helping-oncologists-to-take-complex-decisions-in-treating-cancer~axylb/", + "title": "Helping oncologists to take complex decisions in treating cancer." + }, + { + "Content URLs": " Initial version of slides (will update regularly and mark it complete once done)", + "Description": "Abstract Being one of the most used collaboration tools used by software engineers and data scientists, \"Jupyter Notebooks\" are transforming the way \"data science\" is happening in the industry. Started as a smart Python interpreter, the Jupyter project has grown into a common platform that supports the development of data science and scientific computing tools across multiple programming languages. This talk is aimed at understanding the technical internals of Jupyter project. Agenda A brief introduction to Jupyter How is it different from IPython Component architecture Kernel Frontend Communication protocol used between a frontend and kernel How does a kernel work Magic commands How to create one Let's create a Jupyter frontend Wait! What if you can use Slack as a Jupyter notebook? Jupyter, Interactive computing, and possibilities What will you learn Process that powers an interactive Jupyter session Do you know how does the tab-completion work? Extending the capabilities offered by Jupyter ecosystem for a custom use-case We will learn how to create magic commands and frontend Black magic", + "Last Updated": "02 Jun, 2018", + "Prerequisites": " Basic understanding of Python, comfortable with functions/classes Experience working with Jupyter/IPython notebooks (Optional) Interested in knowing how stuff works", + "Section": "Data science", + "Speaker Info": " Tech & Product at Vernacular.ai Data-driven journalism practitioner Featured in Tech in Asia and Global Investigative Journalism Network Contributor to Go programming language", + "Speaker Links": " Website GitHub Twitter", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Pravendra Singh (~pravj)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyter-notebooks-internals-and-extension~dyz6e/", + "title": "Jupyter Notebooks: Internals and Extension" + }, + { + "Description": "The goal of this talk is to explain this quote : \u201cYou shall know a \u2018word\u2019 by the company it keeps!\u201d In this talk, we will go through as to how to build a model for text summarisation (from scratch) and its possible applications in the real world scenario. An intuitive explanation will be provided (the talk would not be all mathematical!) as to how to do the data preprocessing for a large dataset and provide a reasoning as to why we choose a specific model for training. We will also talk about how certain Python libraries make it easier to structure a machine learning pipeline. We will also walk through the best practices and various caveats while building these kinds of complex models and how to circumvent these", + "Last Updated": "02 Jun, 2018", + "Prerequisites": "The prospective audience should have a basic understanding of neural networks and natural language processing", + "Section": "Data science", + "Speaker Info": "Harshdeep is currently a student at the University of Manchester pursuing his Bachelors in Artificial Intelligence and is interested in Natural Language Processing. My experience with Python started at IBM Bristol where I worked for a year developing the compliance automation tool. After that, I worked on my final year research project using Python which was based on finding summaries and sentiment of news articles. I have previously spoken at PyCon APAC in Malaysia last year in August which was a talk about the basics of Neural Networks. After university, I will be working with some early stage startups in India related to AI and Aviation", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Harshdeep Harshdeep (~harshdeep)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/text-summarisation-made-fun~azAqe/", + "title": "Text summarisation made fun!" + }, + { + "Content URLs": "Slides will be updated soon. Django2 release note", + "Description": "Django is one of the most used Python framework in the world of Python and is even used more than Tensorflow(Stack Overflow 2018 Developer Survey). Django is an excellent web-application framework to build scalable, extensible and high-performance web applications that can serve hundreds of thousands of requests per second -- while keeping the development cycle optimal and maintaining the sanity of developer mind-space. The latest version of Django 2.0 has been just released this year. The new Django 2.0 begins a new era without any backward incompatible changes except the removal of Python2.7 in the latest version and it aims to completely remove Python2 support for Django environment when LTS Django 1.11 expires in 2020 with Python2 . This release also starts the Django using the loose form of semantic versioning. Django 2 has introduced a lot of major changes like : SImplified URL routing syntax Performance optimisation and improvements Mobile Friendly Admin site Newer functions like Windows and more modified aggregate functions\n-Stricter schema Made Mysql isolation as read committed Talk Outlines What is Django and why use Django? Django design patterns - MTV kind of MVC How does Django work? Simplified URL routing syntax in Django2 Other new features in Django2 When should you move your old project to Django2 and Django release Cycle Tips on converting your legacy code to Django2 This talk aims to provide some general insights on Django and latest Django2 version. Apart from being a talk focussed exclusively on Django, the talk aims to give an introduction to what server-side programming is and in general to Web Development", + "Last Updated": "02 Jun, 2018", + "Prerequisites": " Python Django (preferable) After all, this is a Hitchhiker\u2019s guide, this talk will focus on a general introduction to Django and don\u2019t be afraid all the noobs in Python and Django will be welcomed and be accommodated in this tal", + "Section": "Web development", + "Speaker Info": "Kurian is currently in his sophomore year, pursuing an undergraduate degree in Computer Science from Govt. Model Engineering College, Kochi. He has interned in multiple startups like Entri.me, WiM as a product intern developing products using Python and web frameworks like Django. He is also a Open source Enthusiast and have contributed to multiple organisation like Zulip , FOSS Asia. He is an active member of FOSS club in his college(FOSSMEC) and of Kochi Python Club(Python Meetup Group of Kerala)", + "Speaker Links": "Github LinkedIn Medium Twitte", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kurian Benoy (~kurianbenoy)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-hitchhikers-guide-to-django-2~aAr9b/", + "title": "The Hitchhiker\u2019s Guide to Django 2" + }, + { + "Content URLs": "PyCon India 201", + "Description": "What's a good way to Set up many development version(s) ? Developers need consistent isolated development environment, running exact same container(s) as what runs in production , automated test tools, package, ship & deliver. Let's touch features of docker to make it run for Python programs/web apps. Outlines First 5 minutes, I'll be talking about current developers need and present solution. Next 5 minutes, what is docker and how it can solve these problems. Next 10 minutes, I'll be demonstrating, how I use docker for in my Python development tasks (Python library, Python web app). After 20 minutes I will have delivered the enough knowledge for the docker, and next 5 minutes I will let the audience know about the some advance features in docker that they can learn from various resources, to get the maximum power of docker. Q/A along with this. Detail description Basic terms of docker Docker Container Docker Image Dockerfile Docker Compose Docker Repository and Docker Hub Docker Daemon, Docker Client and Docker Engine Docker Swarm Docker Machine Docker for Developers Reproducibility and Developer teams Isolation Security Environment Management Continuous Integration Creating Custom Images and Containerizing Your Application Sample Dockerfile to build an image of an small python program. We will run the image and play with this container. Using Docker Compose in development adds an important constraint: your services are not on the same machine anymore. Container Logs Learn how you can see or capture the logs of the container(s) and services. Docker for Python developers In this section I will demonstrate, how you can setup a development version of real world software.\nI will setup the development version. After creating an image and running it in a container, I will show volume sharing techniques as well. Audience will understand how I have created an consistent isolated container, integrated CI which is easy and fast to ship. Docker for Python Web applications Django and Flask web app will be run under the docker container, different environments in one system. We will learn how to use microservices and advantages of making services using docker-compose. Advance and new features of docker Now audience have understood the docker and they can learn many more powerful features of docker. I will share some good resources and let them know about docker swarm, docker machine, Dealing with Logs, etc ", + "Last Updated": "02 Jun, 2018", + "Prerequisites": "Prior experience with docker is not a necessity but having some exposure to Python development, version control system, Unix System is recommended. At the starting talk basic developers need, basic docker features will be covered. So starting point, anyone (entry/intermediate) can understand the docker concepts. Slowly moving to docker for developers, expert Python developers will get ideas to use docker in their development system and how they can solve most of the development conflicts because of using having multiple environments", + "Section": "Developer tools and Automation", + "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", + "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Shekhar Prasad Rajak (~Shekharrajak)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/containerizing-your-application-is-the-solution~dBvQd/", + "title": "Containerizing Your Application is the solution" + }, + { + "Content URLs": "We will share the Github repository for the workshop here couple of weeks before the conference", + "Description": "\"Our Business Is Our Business None Of Your Business\u2026\" Yes, they wish, but we want to know everything about Bollywood! Who is more popular, Katrina Kaif or Deepika Padukone ? Do you think you look like a Bollywood celebrity? Does deep learning thinks the same? :) What movie is the most similar to PK based on the storyline? Which city in India is home of the most active actresses and actors? And lots of other questions. Do you want to know the answers? And even better, would you like to discover them yourself by using Python and popular libraries such as pandas, Gensim, scikit-learn and pytorch? And cutting-edge data science techniques? Join us for a workshop full of insights where you will be able to answer your own questions while learning the most advanced Python libraries and algorithms. The workshop is designed for Python programmers new to data science. Everybody is welcome, but data analysts and people experienced with pandas will find some parts basic. What will we cover? Loading, merging, cleaning and analysing your data with pandas Advanced data visualisation with Bokeh Embeddings and natural language processing with Gensim Basic machine learning with scikit-learn Deep learning building a face extractor and a classifier with pytorch All this while answering the questions above, and letting you answer your own questions", + "Last Updated": "02 Jun, 2018", + "Prerequisites": " Laptop with Anaconda3 installed Clone of the workshop repository Knowledge of Python Good knowledge of Bollywood desirable :)", + "Section": "Data science", + "Speaker Info": "Simmi Mourya is a researcher at IIIT Delhi in collaboration with All India Institute of Medical Sciences. Her work involves developing end to end deep learning pipelines for Multiple Myeloma detection from histopathology images. Simmi is a regular speaker at Python conferences, including PyCon India and Europython, and other conferences like Fossasia Open Technology Summit. She is also a regular open source contributor, including as a Google Summer of Code Student. She is a huge Irrfan Khan fan. Himanshu Awasthi is the organiser of Kanpur Python and PyData Kanpur. Free and open source software enthusiast, and passionate about Python and data analysis, He is currently working for KanpurFOSS organization which organize free technical workshops in India. Yai Workshop\u2026 Data Analysis Ke Workshop Hai\u2026 Kisi Ke Data Analysis sikha kar He Khatam Hoge... Marc Garcia is a pandas core developer. He has worked as software engineer and data scientist for companies like Bank of America, Tesco, Unilever or NTT Communications. He is a regular organiser of sprints, and speaker at PyCon and PyData conferences. His favourite actor is Aamir Khan, but wouldn't mind teaching Python to Asin", + "Speaker Links": "Simmi : https://twitter.com/simmimourya | https://github.com/simmimourya1 | https://www.linkedin.com/in/simmi-mourya-34406886/ Himanshu : https://twitter.com/IHackPY | https://www.slideshare.net/HimanshuAwasthi14/ | https://speakerdeck.com/johim9493 Marc : https://twitter.com/datapythonista | https://www.linkedin.com/in/datapythonista/ | http://datapythonista.github.io", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Marc Garcia (~marc)", + "created_on": "02 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decoding-bollywood-with-python-data-science-and-deep-learning~eEyWe/", + "title": "Decoding Bollywood with Python, data science and deep learning" + }, + { + "Description": "With the advent of Tableau and languages like Python and R, converting raw data into meaningful insights is much easier and convenient than before. Tableau is a tool used to visually represent data and is powerful enough to analyze the given data at any required level. At an industry perspective, the tool comes handy in finding the trends in marketing and sales with a click of a button. Introducing Python to Tableau using TabPy can help define calculated fields in Python, thereby giving it the power to leverage a large number of Machine-learning libraries right from the visualizations. This widens the scope of its applications to any field that deals with big data and its analytics. Optimisation and cross-sharing of data models facilitated by TabPy immensely enhance the efficiency and usability of the tool. With just a few lines of code, we can churn out predictive models and increase the accuracy of future predictions. The talk will primarily focus on: An introduction to data manipulation and visualization using Tableau. An overview of the steps to leverage TabPy in Tableau. The impact and advantages of Tableau-TabPy combination in the real world.", + "Last Updated": "03 Jun, 2018", + "Prerequisites": "A rudimentary understanding of Data Science and Python scripting", + "Section": "Data science", + "Speaker Info": "I am a sophomore undergrad in computer science from Amrita School of Engineering, India of which I am a part of an intra-college FOSS initiative called FOSS@Amrita. Developing small but useful things that improve lives of the common and affects the open-source community has always been my passion. I believe that with the right technology applied, it can do wonders for the lives of people. Furthermore, I have completed the Google Summer of Code\u201917 with The Wikimedia Foundation and was also a Google Code-In mentor for the same community. Worked on the project that aimed at the improvement and enhancement of the ProofreadPage Extension and Wikisource , through important bug fixes that are left as backlog and implementation of significant features that would make it more user-friendly. This was done so that the extension and Wikisource become easier to use and are raised to the contemporary Mediawiki standards. Apart from this, I'd love to \u200bexpress\u200b \u200bviews\u200b on\u200b \u200bcontemporary\u200b \u200bworld issues,\u200b \u200bget\u200b to know\u200b \u200bthe\u200b \u200bdifferent dimensions\u200b of\u200b \u200bit and analyze the\u200b \u200bmultiple\u200b\u200b ways\u200b \u200bin\u200b\u200b which\u200b \u200bthe\u200b \u200bproblems\u200b \u200bcould be rectified", + "Speaker Links": "Linkedin Blog Gerrit GitHu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Amrit Sreekumar (~amrit95)", + "created_on": "03 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-leveraging-python-in-tableau~dGAKa/", + "title": "Data Analysis: Leveraging Python in Tableau" + }, + { + "Description": "The Jupyter ecosystem of tools lets you interleave code and stories for a literate computing experience, where you can visualize your data as html, plain text, svg and images. You could also view the same rich displays in multiple environments - on the web, on your desktop, in your shell or even your IDE . But how is this possible without duplicating logic, re-inventing the wheel multiple times? How do visualization libraries like Bokeh, Plotly work across frontends - like jupyter notebook, jupyterlab and nteract? This talk explores Jupyter's display system and how it handles multiple display formats in multiple environments. We will see how this idea is applied in some open visualization libraries. After this talk, you will know how to integrate your python objects better with the notebook. You will also get an idea of how to create a visualization library that works across the Jupyter ecosystem of tools. Duration 45 mins (Content can be modified to fit into 30-minute slot too) Outline - Setting some terminology for the rest of the talk (what is a frontend, kernel, displayhooks) (5 mins) - How to use Jupyter's display hooks for your python objects with the notebook (10 mins) - The Jupyter messaging protocol - specifically, the display_data and update_data messages (5 mins) - Custom mime-types (and this is the secret to Jupyter's display system!) - separating what to display from how to display it (10 mins) - Examples of custom mime-types in the wild (a look at altair , vdom , plotly and more) (10 mins) Additional notes This proposal might seem to overlap with another - Jupyter Notebooks: Internals and Extension - which explores how jupyter works under the hood and how to create alternative frontends. My talk's focus will be different, and will dive into a very specific part of Jupyter - the display system - in depth", + "Last Updated": "04 Jun, 2018", + "Prerequisites": "Some experience using either the jupyter notebook or jupyterlab ", + "Section": "Others", + "Speaker Info": "I am a software developer at D.E.Shaw, Hyderabad. I've occasionally contributed to projects in the jupyter ecosystem - the notebook, ipywidgets, hydrogen, nteract", + "Speaker Links": "Github Twitte", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Madhumitha psg (~madhumitha)", + "created_on": "04 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyters-rich-display-system~dJ1Kb/", + "title": "Jupyter's Rich Display System" + }, + { + "Content URLs": "Brief content is here: https://github.com/yashug/Pandas Actual workshop will cover more inf", + "Description": "The Goal of this workshop is to make you more fluent at pandas to answer data science questions. Python has long been great for data munging and preparation, but less so for data analysis and modelling. pandas help fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R", + "Last Updated": "04 Jun, 2018", + "Prerequisites": " Laptop with Anaconda installed Basics of Python", + "Section": "Data science", + "Speaker Info": "Yaswanth is a Senior Software Engineer, currently working in ZeMoSo Technologies and Graduated from IIT Guwahati. Free and open source software enthusiast, and passionate about Python and Machine Learning", + "Speaker Links": "Linkedin | Githu", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Gosula Yaswanth (~yashug)", + "created_on": "04 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-pandas-for-better-data-science~aKGGa/", + "title": "Using Pandas for Better Data Science" + }, + { + "Content URLs": "Will share the code, slides, and resources as a GitHub repository after the talk", + "Description": "Automatic Visual Speech Recognition comes very handily in scenarios that have noisy audio signals. A video image of a person talking is analyzed and shapes made by the lips are examined which are then turned into sounds by comparing to a dictionary to create matches to the words being spoken. In this talk, we will use a VGG+GRU network which is based on CNN+LSTM layers to predict the text spoken by the speaker and classify it into 20 classes from audio-less videos, consisting of 10 words and 10 phrases. This will be done on the audiovisual MIRACL-VC1 dataset. The talk will cover how a CNN+LSTM can be used to recognize a sequence of shapes formed by the mouth and then match it to a specific word or sequence of words spoken from Visual Feed. It will include data-preprocessing, creation of CNN and LSTM layers using Python and applying them on the dataset", + "Last Updated": "06 Jun, 2018", + "Prerequisites": "Basics of Python Syntax, Tensorflow, Keras, Neural Network", + "Section": "Data science", + "Speaker Info": "Kanika Modi holds a Bachelor's in Computer Engineering from Netaji Subhas Institute of Technology, University of Delhi. Having finished her coursework, she will join Amazon as a Software Development Engineer(SDE). She is an open source enthusiast and has contributed to organizations such as Systers, Fossasia, etc. She is also a Google Summer of Code'18 mentor at Systers, a GirlScript Summer of Code'18 mentor and mentor at RightApprise. Her interests also extend to the fields of artificial intelligence and machine learning. She prefers Python as her weapon of choice", + "Speaker Links": "Link to LinkedIn Link to GitHub Link to Twitte", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "kanika_96", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-lip-reading-system-to-recognise-visual-speech-using-python~dNG2e/", + "title": "Building A Lip Reading System To Recognise Visual Speech Using Python" + }, + { + "Description": "Considering the fact that businesses these days make a lot of money by recommending customers the things that match their likes, knowing how to build a Recommendation System would be of great use to many aspiring Deep Learning enthusiasts. This workshop is all about understanding and implementing Auto-Encoders. Auto-Encoders are the Unsupervised Deep Learning Models which are widely used for Dimensionality Reduction and Feature Discovery. New types of Auto-Encoders have enabled us to build very nice Recommendation Systems. The talk will focus on understanding Auto-Encoders, their types, and building a Recommender System that Predicts Rating (1 - 5) using PyTorch. The flow of the workshop will be as follows: Self Introduction Introduction to Unsupervised Deep Learning Diving DEEP into Auto-Encoders (Theory, Architecture, and Working) Introduction to Sparse Auto-Encoders Introduction to Denoising Auto-Encoders Introduction to Contractive Auto-Encoders Introduction to Stacked Auto-Encoders Understanding the Deep Auto-Encoders Training Auto-Encoders Building a Recommender System that Predicts Ratings (1 - 5) Understanding the Problem of Overcomplete Hidden Layers End of talk Questions and Answers Session", + "Last Updated": "06 Jun, 2018", + "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras, TensorFlow, or PyTorch will be good but not necessary.", + "Section": "Data science", + "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", + "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "greatdevaks", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-auto-encoders-using-python~aOGRa/", + "title": "Understanding and Implementing Auto-Encoders Using Python" + }, + { + "Content URLs": "I delivered a talk on Recurrent Neural Networks at GeoPython 2018, Switzerland. The proposed talk will be enhanced version of my previous talk. This time, I will be covering more topics to make it a more detailed talk.\nLink to my previous talk: https://github.com/greatdevaks/GeoPython_Basel_201", + "Description": "Recurrent Neural Networks (RNNs) have become famous over time due to their property of retaining internal memory. These neural nets are widely used in recognizing patterns in sequences of data, like numerical timer series data, images, handwritten text, spoken words, genome sequences, and much more. Since these nets possess memory, there is a certain analogy that we can make to the human brain in order to learn how RNNs work. RNNs can be thought of as a network of neurons with feedback connections, unlike feedforward connections which exist in other types of Artificial Neural Networks. The flow of the talk will be as follows: Self Introduction Introduction to Deep Learning Artificial Neural Networks (ANNs) Diving DEEP into Recurrent Neural Networks (RNNs) Comparing Feedforward Networks with Feedback Networks Quick walkthrough: Implementing RNNs using Python (Keras) Understanding Backpropagation Through Time (BPTT) and Vanishing Gradient Problem Towards more sophisticated RNNs: Gated Recurrent Units (GRUs)/Long Short-Term Memory (LSTMs) End of talk Questions and Answers Session", + "Last Updated": "06 Jun, 2018", + "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras or TensorFlow will be good but not necessary.", + "Section": "Data science", + "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", + "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "greatdevaks", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-recurrent-neural-networks-using-python~dPGAb/", + "title": "Understanding and Implementing Recurrent Neural Networks using Python" + }, + { + "Description": "Data Wrangling involves detection, correction, removal, or otherwise dealing with inaccurate and corrupted data. The most common file formats in which data can be stored are CSV, JSON, and XML. However, many times, the data is not available in the desired format and rather is available in some unconventional file formats like PDF or PPT. Parsing PDFs may seem like a daunting task to many as it is quite an unpredictable format. Simply stated, PDF is a hard-to-parse format. This workshop will help you understand the concept of Wrangling PDFs in an easy and fun way. Following will be the flow of this workshop: Self Introduction Brief Introduction to Data Wrangling Why prefer CSV, JSON, or XML? Why avoid using PDFs? Basics of RegEx based Pattern Matching Parsing PDFs Programmatically using \"slate\" and \"pdfminer\": Getting hands-on Inefficient Parsing? Consider Data Cleaning Exploring PDF Wrangling with \"pdftables\" Where to go from here? Question and Answers Session The End :) Key Takeaways: Gain confidence in Data Wrangling using Python. Get familiar with the daunting PDF Parsing task. Get hands-on with popular PDF Wrangling libraries in Python: \"slate\", \"pdfminer\", and \"pdftables\". Understand the concept and importance of Data Cleaning.", + "Last Updated": "06 Jun, 2018", + "Prerequisites": " Basic knowledge of programming in Python language. Familiarity with wrangling CSV, JSON, or XML files will be good but is not necessary.", + "Section": "Core python and Standard library", + "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", + "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "greatdevaks", + "created_on": "06 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/wrangling-unconventional-file-formats-with-python-playing-with-pdfs~aQXGe/", + "title": "Wrangling Unconventional File Formats with Python: Playing with PDFs" + }, + { + "Content URLs": "A few topics I will be covering, I would not be covering everything in detail, but hope to highlight important aspects from these links over the talk session: http://openmusictheory.com/ https://in-thread.sonic-pi.net/ https://github.com/gkvoelkl/python-sonic http://www.daveconservatoire.org/course/introduction-to-sonic-pi By the end of this talk, I aim to instil a much better idea about Live Coding and Programming Musi", + "Description": "Sonic Pi: An open-source live coding platform developed by Dr Sam Aaron aims to explore and teach programming concepts based primarily on the process of creating new sound.\nWe will venture deeper into the live coding platform and produced different genres/styles on music while coding live and dwell further into performing algorithmic music on a wider scale. I have tinkered with different styles of tones and sounds in sonic-pi and Python and re-created a rendition of popular 21st century music, only through algorithmic-generation, and seek to promote appreciation about open-source software such as sonic-pi and aim to demonstrate it's applications, along with the use of Python over the course of a thirty minute-talk and demo, in the rendition of producing Algorithmic-Music Live , during the course of the talk. By the end of the session, I aim to establish a better understanding of Live-coding, Programming Music and Intelligent-dance music Artists such as Aphex Twin. The flow of the talk will be as follows: Self Introduction Introduction to Music-theory and Sound Generation Introduction to Live Coding and Python-sonic Understanding the algorithmic workflow Diving beyond: Guitars, drums and Piano Produce an algorithmic-track! End of talk Q&A Session We shall also fiddle with a physical midi-controller if we find time, and demonstrate various interesting forms and styles of music; \nWe will also be producing a popular 21st century track from scratch ", + "Last Updated": "07 Jun, 2018", + "Prerequisites": " A curiosity for algorithmically-produced music, Python and open-source software. Basic Music theory knowledge is appreciated, but anything relevant will be covered during the talk.", + "Section": "Others", + "Speaker Info": "My name is Sushen Kumar. I am a currently pursuing a Bachelor of Engineering in Computer Science at Sir M Visvesvaraya Institute Of Technology, Bangalore. Over the course of my academia I have dabbled into a few open-source projects, as well as contributed to open-source organisations on GitHub: Attended several hackathons around India: (Winner-ValuePitch Hack, Runners' up- IESA Makeathon) Given talks and held beginner sessions on Creative Coding in Python and sonic-pi. Completed three grades in hindustani-classical music-theory, with 8+ years of experience in playing the Guitar and Harmonium. Received 3 Honours and Awards (National level). I absolutely love Music and Coding, and aim to merge this passion and demonstrate the applications of Python and open-source frameworks in Music Production by means of this talk :)", + "Speaker Links": " https://github.com/nehsus https://www.linkedin.com/in/sushenk/", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Nehsus (~nehsus)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-algorithmic-music-and-melodies-with-python-sonic~dRXVa/", + "title": "Generating Algorithmic Music and Melodies with Python-sonic" + }, + { + "Description": "In Data Science, Garbage In = Garbage Out. Feature engineering is one of most of the important yet most neglected step in life cycle of Machine learning projects. Kaggle competitions have showed us that top Kagglers spend more than half of their time in feature engineering. Through various experiments, its also proved again & again that better features with simple model triumphs even advance models. In this talk I am planning to discuss basic as well advance feature engineering techniques which can be used by everyone in their projects Outline What is Feature Engineering ? Techniques for Numerical Variables Techniques for Categorical Variables Techniques for Textual data Advance techniques Feature Selection & Dimensionality reduction QA", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Basic knowledge of Python & Machine learning", + "Section": "Data science", + "Speaker Info": " Sudarshan Gadhave is a Data Science ,Data Engineering & Data\n Integration professional with over 8 years of experience working on\n Machine Learning , Data Engineering , Data Visualization and Data\n Warehousing Projects. Currently he is working as a Specialist Data Scientist in Analytics R&D team of\n Nice Actimize ( Nice Systems) working on developing Anomaly & Fraud detection models. Earlier experience of working in Advance Analytics & Data Warehousing\n teams of NEC, Japan & John Deere (Deere & Company). Pythonista & expert in Python Machine learning stack (Numpy,Pandas,\n Scikit-Learn, Matplotlib) Active & Core member of Python Pune meetup group.Presented several\n talks on Python & machine learning in meetups, conferences and\n colleges all over Pune.", + "Speaker Links": " Github:- https://github.com/sudarshan1413 Linkedin:- https://www.linkedin.com/in/sudarshan-gadhave-73567b23/", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "sudarshan1413", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/art-of-feature-engineering-for-machine-learning~eVWza/", + "title": "Art of Feature Engineering for Machine Learning" + }, + { + "Content URLs": "Slides : https://docs.google.com/presentation/d/1zNFGNy2BMBYQvZypkH8Iql-WRx--6Ddg8Ft33intWjM/edit?usp=sharin", + "Description": "Large Python codebases can be hard to maintain. If we make it easier to understand our code bases, we make everyone more productive and help each other write fewer bugs. Static typing is one of remedies that can improve readability and maintainability of the code. That's why Python now features optional static typing as described in PEP-484 , implemented as Mypy . Mypy is an experimental variant of Python that let's you add optional type annotations to type check your Python code. And it works great on both Python 2.7 and 3.3+. Adopting static typing is easier that you think, you can start on a small set of code and move on to bigger pieces. In this talk I'll share about, PEP-484 and Introduction of type annotations in Python 3.5 Use cases of Mypy and how to use it with Python 2 and 3 Project typeshed and how to leverage it Lessons I learned by type hinting the project Twine We\u2019ll also discuss how to make it a seamless part of your project; what order to approach things in; and some powerful new packages that make it even easier today to add static types to your Python codebase than ever before", + "Last Updated": "07 Jun, 2018", + "Prerequisites": " Knowledge of Python Difference between dynamic and statically typed languages", + "Section": "Core python and Standard library", + "Speaker Info": "Wasim is a Senior Software Engineer at Zemoso Labs, Hyderabad. He's an open source fanatic who loves to create meaningful software and contribute to open source projects. Some of his contributions are included in projects like Sendgrid, Warehouse, Twine and Hazelcast. Apart from programming he also tweets . You can find him interesting on his GitHub profile ", + "Speaker Links": "Article on Medium about Mypy Stub file for the project Texttable Open source contributions can be found at my GitHub profile ", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Wasim Thabraze (~waseem18)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mypy-optional-static-typing-for-python~bW1Ee/", + "title": "Mypy: Optional Static Typing for Python" + }, + { + "Content URLs": "https://www.artima.com/weblogs/viewpost.jsp?thread=214235 http://www.dabeaz.com/python/GIL.pdf -slides tb", + "Description": "Python is an amazing language, known for its vast standard library and use in rapid prototyping. When we were trying to build a robotics system that is primarily modular and upgradeable, we ended up using Python to power the brain of the project. In this talk, we'll discuss how we designed the event loop, responsible for controlling the mechanical actions and state of a robot snake. Animating multiple motors concurrently at different speeds to different positions. Foreground and background tasks. Interrupting ongoing tasks. We will discuss best practices when performing asynchronous actions in Python, and how to ensure actions are completed within a bounded time.\nFinally we touch one of the lesser known 'features' of Python, the Global Interpreter Lock. GIL is a mutex that protects access to Python objects, preventing multiple threads from executing at once. Two threads calling a function may take twice as much time as a single thread calling the function twice. We'll discuss some of the real world implications of the GIL, along with some considerations that must be taken while writing highly synchronous Python code", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Knowledge of common Python syntax would be great", + "Section": "Core python and Standard library", + "Speaker Info": "Hi, I'm Pranith, a final year undergrad student at NMIT, Bangalore. I'm a robotics enthusiast with a passion for cypherpunk, virtual reality, and generally, the future. Apart from the usual frameworks, I've used Python across the field, ranging from web technologies implemented on raw CGI to microPython on the ESP8266. I try to apply Python in odd ways to bridge various layers of the stack, and as a result have a fair amount of experience breaking it", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Pranith Hengavalli (~prnthh)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/robot-snakes-and-the-global-interpreter-lock~eXPve/", + "title": "Robot Snakes and the Global Interpreter Lock" + }, + { + "Content URLs": "Shall be updated soon", + "Description": "Here, We will talk about how you can make a bot to help you automate your life and make your very personal Assistant, and maybe you will end up making something better than Google Assistant or Siri. We will be using modules to perform a task, so you can keep making them as you go and your assistance will keep becoming more powerful and yes all this will be done in python. In this talk: - We will start with setting up project creating simple python GUI. - Making some modules to perform a simple task. ~ Composing email with speach ~ Some other cool modules - Explaining what else we can achieve with this. ~ Let's make, its personality using tensorflow for talking stuff - Showing my work and explaining how it works Here, Is in early development phase Then we will end with some questions and how they can continue with this project", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Basic Understanding of Python", + "Section": "Developer tools and Automation", + "Speaker Info": "He is a student, a self-taught programmer loves to dig deep and know more about the computers. Fell in love with python and now loves to Automated things with python. He is GSoC aspirant. He is an active volunteer at PyDelhi and ALiAS . When he is not automating things he loves to contribute to open-source and closing issues", + "Speaker Links": "Website: omkar.site Github: @omi1085", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "omkar yadav (~omkar10)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/superpybot-your-personal-assistant~bYZAd/", + "title": "SuperPyBot: Your Personal Assistant" + }, + { + "Content URLs": "This one is the essence of it but closed source and in java: https://lifehacker.com/how-to-build-your-own-amazon-echo-with-a-raspberry-pi-1787726931", + "Description": "Voice is the new touch. It's not going to be too long before the likes of Alexa or Google Home take over our day to day life like the Internet and the mobile phones have. There are countless tutorials on how to hook up a home automation system using a Raspberry Pi like here and here . Pair that up with voice capabilities and you can basically tell your lights to turn themselves off or the TV to change the channel. In this talk I'll cover the following: Hook up a microphone to a raspberry pi and be able to capture wav files on python. Use an online API like Google's Speech API to convert the wav to text. Give a background on what intents and entities (slots) are. Installing open source software like Snips Encoding our intents and example sentences and training the open sources software Calling a functions to do particular activities At the end there'll be a cool demo", + "Last Updated": "07 Jun, 2018", + "Prerequisites": " Knowledge of what a Raspberry Pi and Python is. And maybe played with an Alexa, Siri or Google Home. Yup, low barrier of entry", + "Section": "Embedded python", + "Speaker Info": "I am Ved. I have a masters in Computer Science/Data Science from IIIT-Bangalore and I work on NLP/Linguistics at Slang Labs. My goal in life is to sit down and have a conversation with a computer at a bar coffee shop. Maybe we won't get there soon, but at least maybe I can make it reserve my seat for me", + "Speaker Links": " vedmathai.com https://github.com/vedmathai/ https://www.linkedin.com/in/vedmathai/", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Ved Mathai (~ved47)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/create-a-voice-conversational-agent-for-your-raspberry-pi-home-automation-system~eZgQa/", + "title": "Create a voice conversational agent for your raspberry pi home automation system" + }, + { + "Content URLs": "https://github.com/Laneone/askfm-pytho", + "Description": "Hey everybody! Ever tried to webscrape? Ever faced a \"No robots allowed! No web scraping allowed!\" message from a favorite site? This talk is for meant for you. Usually when you're done building a fancy web scraper and begin running the homebrew'd tool on your favorite site there's chances you'll face a block on your IP address preventing your computer from accessing more resources and therefore downloading the contents of the website. Your tool maybe fast, it might be scalable, it might be the best written scraper out there, but with just one IP address under your belt, it's easy for giants to block your ip address and prevent you from getting that precious data, especially if you've built a threadsafe and multi-node webscraper. Enter The Onion Router, The ToR project, allows you to use the the internet vis-a-vis a proxy and visit the same website under a different endpoint ip address, but that's just for one instance of ToR. What if you ran, say 200? at once? 200 ip addresses > 1 ip address. With 200 endpoints and the latest update to the requests library, you can now use your multi-threaded and resource hungry webscraper and it can(not) be stopped! Whatever your rate of data collection, you can 200x it! The stack is simple, you open a SOCKS5 proxy per ToR endpoint, connect it to a request with it's own port number and you're good for that one request, same for multiple requests. You can build a task scheduler to orchestrate the url to scrape and the port number the tor endpoint is on and have the entire application running on a cloud service provider to ensure you face no bandwidth issues. The demo centered around the talk will attempt to rapidly and quickly scrape users from the famous social network Ask.fm which is known to restrict users from retreiving from their site if you attempt to download more than 4 users in under a second, but with the hack in place, you'll be retrieving close to maximum efficiency on a DigitalOcean droplet , but this can be applied to virtually any website and any cloud provider. Never pay for webscraping again! Thanks and see you at PyCon! \n-Lokesh Poovaraga", + "Last Updated": "07 Jun, 2018", + "Prerequisites": "Basic concepts of web scraping, Regex, Task scheduler, ports and proxies", + "Section": "Developer tools and Automation", + "Speaker Info": "Hi I'm Loki! (Lokesh Poovaragan) A full-stack developer from Dayananda Sagar, Bangalore, and I love to code in python! In my free time I love to web scrape and gather good amounts of public data and encompass them into json format for data(sentiment) analysis. I also build prototypes of interesting combinations of technology to solve unique problem statements. I love exploring new and interesting areas of work and I love to play with code", + "Speaker Links": "Blog: http://laneoneblog.blogspot.in GitHub: http://github.com/Laneon", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Laneone (~Laneone)", + "created_on": "07 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-intermediates-guide-to-theoretically-unlimited-webscraping-with-python-using-requests-lxml-tor~e1MZe/", + "title": "A Intermediate's Guide to (theoretically unlimited) WebScraping with Python using Requests & lxml & ToR" + }, + { + "Content URLs": "Would update soon after feedback", + "Description": "Most machine learning algorithms require feature vectors as inputs. In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object (image, text, sound). Feature engineering, the practice of extraction of features from objects is a combination of art and science; it requires the experimentation of multiple possibilities and automated techniques with the intuition and knowledge of the domain expert. Automating this process is called \"feature learning,\" where a machine learns the features itself. One way to obtain features is to use the 'Bag-of-Features' model, the idea behind which is to simplify object representation as a collection of its subparts. Originally used for representing text data, the \"Bag-of-Words\" methodology can be extended to different types of objects resulting in models such as \"Bag-of-Visual-Words,\" \"Bag-of-Audio-Words.\" The significance of these models in the age of self-learning deep networks still holds because of their ability to work with limited data. The contents of the talk are: Introduction to Feature Engineering Working with Text Data Understanding 'Bag-of-Words' Example: Text Classification Working with Image Data Introduction to 'Bag-of-Visual-Words' Example: Image Classification Comparing the performance to CNN Overview of 'Bag-of-Audio-Words' Generalizing 'Bag-of-Features' This talk primarily discusses Bag-of-Words, Bag-of-Visual-Words through an example of text classification and image classification respectively. It also covers the concepts that generalize to models other than Bag-of-Features. The goal is to acquaint the audience who have previously worked on numeric data with some ideas to get started with text and multimedia data", + "Last Updated": "08 Jun, 2018", + "Prerequisites": " Intermediate knowledge of Python Familiarity with classification problems Familiarity with basic NLP/CV is helpful (but not necessary)", + "Section": "Data science", + "Speaker Info": "I'm a fresh graduate in Computer Science & Engineering. I am passionate about Data Science, and I spent most of my time learning about skills required to excel in the domain. Outside of my professional interests, I am fond of rock music and reading", + "Speaker Links": " Blog: https://pranavsuri.com GitHub: https://github.com/pranavsuri LinkedIn: https://linkedin.com/in/suripranav Twitter: https://twitter.com/pranav_suri", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Pranav Suri (~pranavsuri)", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bag-of-features-representing-text-image-data-as-numerical-vectors~b2XMe/", + "title": "Bag-of-Features: Representing Text & Image Data as Numerical Vectors" + }, + { + "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", + "Description": "In today's Era, the IT sector is moving more and more towards automation. Now every company is trying to provide its users with the facility to perform their task without the need for any human intervention.\nIn this talk, we are addressing a similar problem of automating the vehicle parking systems. Problem description: Automated license plate recognition(ALPR) is a well-known problem where we try to extract the license number from a cars number plate using machine learning algorithms. The scope of its real-world application ranges from highway toll plaza to automated parking and charging of future electric cars.\nThis problem has been targeted with a variety of algorithms like traditional template matching to advance deep learning algorithms like YOLO . Here we will be presenting a combination of little template matching clubbed with some deep learning to solve this problem in the most simplistic way", + "Last Updated": "08 Jun, 2018", + "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations", + "Section": "Developer tools and Automation", + "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", + "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Saqhas", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-license-number-recognition-in-python~e33Ae/", + "title": "Automated License number recognition in python" + }, + { + "Content URLs": "http://click.pocoo.org (Cool power-point and Github repo coming up", + "Description": "Who hasn't used Git in the terminal? An absolute beast of a tool. But did you ever have an idea to build your own cool Command Line tool for something you believed could simplify life for other devs but you didn't because you were too lazy to research? Worry not! I present to you Click! Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It\u2019s the \u201cCommand Line Interface Creation Kit\u201d . It\u2019s highly configurable but comes with sensible defaults out of the box. In this talk, I'll go through the process of designing a simple (or complex) Command Line Interface called thanos which tells you whether you survived the SNAP or not. I'll be taking you through the process of designing, building and publishing our thanos package. We'll then upload it to the Python Package index so that you can do pip install thanos from any system worldwide and find out if you perished or not. Outline What is a CLI ? Building our own CLI called Thanos , to find out whether you survived the snap or not. >>thanos snap\n You didn't make the snap. Creating complex commands using beautifully decorated code. Exploring arguments, flags and options within the CLI. What's PyPI, and why do we need it? Uploading your new Thanos package to Python Package Index. QA", + "Last Updated": "08 Jun, 2018", + "Prerequisites": " Should have seen or used a terminal before. (Mandatory) Basic Python knowledge preferred.", + "Section": "Developer tools and Automation", + "Speaker Info": " Adarsh is a visionary who strives to build amazing tools for people. He is currently pursuing bachelors in CSE. Currently he is Google Summer of Code Intern at CloudCV , an organisation which works on making reproducible AI research, where he is building a versatile CLI for EvalAI project. He was one of the youngest speakers at FOSSASIA International Summit 2018 in Singapore for his work on Python based NLP POSTagger. Worships Open Source software and have contributed to multiple organisations like FOSSASIA, Zulip where he was also a mentor for Google Code-In 2016 .", + "Speaker Links": "https://www.youtube.com/watch?v=TzIr9THCUJg https://2018.fossasia.org/event/schedule.html#s-4267 https://github.com/isht3/ https://www.linkedin.com/in/guyandtheworld", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "isht3", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-your-own-command-line-application-and-upload-it-to-pypi~b427e/", + "title": "Build your own Command Line Application and upload it to PyPI!" + }, + { + "Content URLs": "Part 1 Part 2 Github Rep", + "Description": "Websites and blogs have become a common trend amongst professionals to display not just their resumes but also their daily work items. Static blog generators have gained popularity over the last few years . People who have been using Wordpress, Blogspot or Blogger are now shifting to Pelican , Jekyll etc. One major annoyance was that Wordpress had a huge attack surface. Everytime someone found out a Wordpress exploit, your site was at risk. When comparing Blogger vs Pelican, the Slant community recommends Pelican for most people. In the question \u201cWhat are the best solutions for a personal blog?\u201d Pelican is ranked 10th while Blogger is ranked 14th. Python is becoming more and more popular amongst programmers and so is Pelican . \nPelican is a static blog generator and supports several formats like Markdown , ASCII etc . It turns Markdown and some Jinja templates into the Full Stack Python site. Its beauty lies in its simplicity and even a non programmer can get started with Pelican in just a few lines of code and plain text . Over the past few years people have shifted from Wordpress to Pelican .This is because a static site has basically no attack surface, and can be hosted on free or inexpensive hosts like Github Pages .\nThis talk is focused on introducing a simple static site generator to beginners and even avid bloggers who aren't coders . This talk will cover:- Basic installation of Pelican Writing a blog post with Pelican Changing themes of a blog/site Comparison between Jekyll and Pelican The main aim of this talk is to familiarize people with the concept of edifice . I have met a lot of non coders who have asked me about creating a basic website for personal use . This talk is also targeted to all those you are interested in blogging and everyone out there has something to say and something to blog ", + "Last Updated": "08 Jun, 2018", + "Prerequisites": "Absolutely nothing ", + "Section": "Web development", + "Speaker Info": "Anumeha Agrawal is a Pythonista and an open source enthusiast . She is in her third year of undergraduate program in Information Technology at NITK Surathkal . She is also a Google Summer of Code 2018 student at Systers . In her project at Systers , she has used python to write scripts to retrieve data from GitHub API and use it in her MEAN stack project . She uses python scripts to simplify most of her work like API data collection and web scraping . Python was the first language she was introduced to when she began programming and it is her weapon of choice . Owing to the simplicity of python syntax, she also used python to code her algorithms for her talks and workshops at college . Apart from being a full stack developer ,she is also a Data science enthusiast and employs python for designing most of her Deep Learning models and algorithms ", + "Speaker Links": "Link to Github Link to Linkedin Profile Link to Medium Blog Link to GSoC projec", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Anumeha Agrawal (~anumeha)", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pelican-magic-for-beginner-bloggers~e5MYe/", + "title": "Pelican - Magic for beginner bloggers" + }, + { + "Content URLs": "Will be sharing soon", + "Description": "Your introduction to concurrent programming in python. This talk is dedicated to a developer to enable him/her get started in asynchronous programming. The contents that will be covered in the discussion are as follows. What is asyncio? Why should we bother? Multi Threading vs Multiprocessing vs asyncio understanding the differences. All about what an event loop is with examples Futures Tasks and coroutines Streams Multiple Coroutines. Scheduling Calls Synchronization primitives Queues Working Example with a few notes on sockets and summary. The talk provides preliminary insight and a simple explanation to programmers who wish to explore asyncio and/or concurrent programming. ", + "Last Updated": "08 Jun, 2018", + "Prerequisites": " Basic understanding of python syntax. Some OS concepts like differences b/w multiprocessing and multithreading. Understanding UNIX (not mandatory).", + "Section": "Core python and Standard library", + "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", + "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Vishnu Kiran (~vishnu25)", + "created_on": "08 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-asyncio~b6MOa/", + "title": "Introduction to Asyncio" + }, + { + "Description": "This workshop is dedicated to discuss and extrapolate on the core of Object Oriented Programming its finer details and nuances. The objective of the talk is to introduce concepts that will ensure OOP becomes second nature to a programmer. What you will gain after this session Detailed overview of Object Oriented Programming Intuition on the finer nuances of Object Oriented Programming. Tips on keeping the OOP code clean and readable. Expanding your horizon by understanding some lesser known concepts in Python. The session will focus on the following aspects with examples Inheritance and everything about it. Method Resolution Order Method Types Custom Base Object, Collections, and Dict Objects Extending Built-in Types Data Models Meta Classes and where they help Decorator and Class Decorators. Factory Design pattern Singleton Things to remember while writing code Conclusion", + "Last Updated": "09 Jun, 2018", + "Prerequisites": " Basic Python syntax Some understanding of Object Oriented Programming", + "Section": "Core python and Standard library", + "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", + "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Vishnu Kiran (~vishnu25)", + "created_on": "09 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-object-oriented-programming~e7MQb/", + "title": "Advanced Object Oriented Programming" + }, + { + "Content URLs": "I will upload slides soon", + "Description": "Object-Relational Mapper (ORM) is one of the powerful feature of Django. It allows us to interact with database without writing long complex SQL queries. The contents that will be covered in the discussion are as follows. Introduction to ORM, How it works ? What is queryset ? how it works ? Explaining use of values, values_list, only and defer to run ORM query efficiently How to use select_related and prefetch_related to optimize queries Some examples to show, how to query very complex data using only ORM What not to do while using ORM to avoid slow performance", + "Last Updated": "09 Jun, 2018", + "Prerequisites": " Basic knowledge of Python and Python web framework (Django) Some experience in quering relational databases", + "Section": "Web development", + "Speaker Info": "My name is Hiren Patel. I am working at Aubergine solutions pvt ltd and I have been doing full stack web development there from last 2.5 years. While working on some web projects, I have always focused on learning django in more detail and try to optimize APIs to return response faster", + "Speaker Links": " Github: https://github.com/hirenalken LinkedIn: https://www.linkedin.com/in/hiren-patel-046672ab/ StackOverFlow: https://stackoverflow.com/users/3553279/hiren-patel?tab=profile Medium: https://medium.com/@hirenpatel_38103 I had presented a talk on this same topic in meetup organised by Ahmedabad based meetup group. here is the link to meetup: lin", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Hiren Patel (~hirenalken)", + "created_on": "09 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/efficient-use-of-django-orm~b8gja/", + "title": "Efficient use of Django ORM" + }, + { + "Content URLs": "Slides TBD Code repository TB", + "Description": "Abstract Today, massive systems are running on microservices communicating with each other using REST APIs. REST is easy to get started, loosely structured and does good job in exchanging messages. But it's convenience comes with a performance trade-off, which takes us back to other optimal alternative: gRPC Description In this talk we will see what gRPC is and how it is different from REST. We will get started with GRPC by generating stubs for python and \nbuild a simple gRPC API server. We will try to find out the advantages of gRPC over REST by doing a side by side comparison of our APIs. We then deploy our server in Kubernetes and discuss how we could scale our microservices. Outline Introduction to gRPC (3 min) gRPC concepts (5 min) Designing the APIs REST-fully (3 min) Going the gRPC way (5 min) Generating python stubs Duel: gRPC vs REST python servers (4 min) Demo (4 min) Deploying our gRPC apis in kubernetes Summary (3 min) Q & A (3 min) Key take aways to audience Audience will get a practical introduction to gRPC and protocol buffers. Now the audience will know an alternative to HTTP/REST. This allows them to design better microservices\nbased on their use cases. Bonus: Deploying and scaling python microservices in Kubernetes. Links Companies using gRPC in production Protocol buffers ", + "Last Updated": "09 Jun, 2018", + "Prerequisites": "This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners", + "Section": "Web development", + "Speaker Info": "Naren is a Product Engineer with specific focus on building robust backend systems. Past 5 years, he has built dozens of microservices and scalable systems using Python, Go and AWS cloud. He is an open source enthusiast who loves speaking at tech conferences and currently works as Senior Software Consultant at Tarka Labs. In his industry experience he\u2019s worn plenty of hats- like the one of a Trainer, Embedded Engineer, Product Engineer and Consultant and sometimes even helmets- while he\u2019s out cycling.\nWhen he\u2019s not stirring up code, you can find him whipping up a delicious gluten-free treat or training for cycling races.\nHe also blogs about software, productivity and goes by the handle DudeWhoCode across the internet", + "Speaker Links": "Past 5 years I have been architecting and building scalable backend systems using Python. I have built a dozen of microservices at scale. Recently I built a production infrastructure in Python that handles 20+ millions of API calls per day. At one point of time, I realised I should know some alternatives other than REST to communicate between the microservices. Out of curiosity I explored and used gRPC in few of my microservices. Since then, I wanted to share the knowledge so that developers will get to know other options while architecting their infrastructure. This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners. I have spoken in various conferences, my recent one was PyCon Singapore 2018. Below are some of my previous talks and speaker portfolio: Speaker Portfolio Featured talk 1 Featured talk 2 Featured talk 3 portfolio blog Github", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Narendran R (~narendran)", + "created_on": "09 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-better-python-microservices-using-grpc~e9jJa/", + "title": "Building better Python microservices using GRPC" + }, + { + "Content URLs": "Any related material will be shared soo", + "Description": "Natural language processing(NLP) is a branch of artificial intelligence concerned with automated interpretation and generation of human language. From keyword search to Virtual Assistants, from spell checkers to language translators and from sentiment analysers to Chat bots, NLP finds its applications in most of our day to day applications.\nThis workshop aims at delivering a basic Hands on tutorial to get started with NLP in Python. It commences with an introduction to NLP, discussion on various applications and a linguistic breakdown of Language (English). By the end of this workshop you will be able to : Install relevant packages such as nltk, gensim and pattern . Applying text processing techniques such as Tokenization, Stemming, Lemmatization and Chunking . Forming a Document Term Matrix using Bag of Words Model . Building a simple Spam/Ham classifier using Bag of Words Model . Generating Word Vectors using Gensim Word2Vec module. Building a Sentiment Analyzer . This workshop provides preliminary insight and a simple explanation to enthusiasts who wish to explore the field of Natural Language Processing.\nIt enables you to talk to your computer!", + "Last Updated": "10 Jun, 2018", + "Prerequisites": " Basic knowledge of Python. Any knowledge of Python modules such as Numpy, Pandas etc. is and add on.", + "Section": "Data science", + "Speaker Info": "Hello, I am Osheen Nayak, working as a Software Engineer at Texas Instruments Bangalore. I belong to Delhi Technological University batch of 2017.\nI am a Machine learning and Data Science enthusiast and I have been actively driving various Machine Learning activities. I have delivered few talks on Machine Learning in the past one of them including \"A primer on Machine Learning and Artificial Intelligence\" in the IEEE forum to and audience of 50 people. I am an avid football fan and also an amateur player.Also, I like to play video games, cricket and chess", + "Speaker Links": "Connect on LinkedIn : https://www.linkedin.com/in/osheen-nayak-31022a10b", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "osheen nayak (~osheen)", + "created_on": "10 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-talk-to-your-computer-a-101-on-natural-language-processing-with-python~e0M5a/", + "title": "How to talk to your computer - A 101 on Natural Language Processing with Python" + }, + { + "Content URLs": " http://github.com/vaideesg/omsdk http://github.com/dell/omsdk", + "Description": "Abstract Ever wonder creating your own super-type-manager leveraging the python's own type constructs? Ever explored alternatives to APIs for integration? In this talk, we will cover our experience in building a new type manager (as part of developing open source OpenManage(tm) Software Development Kit) leveraging pythons own type constructs and explore how this new type manager provides a credible alternative to APIs, especially in those information-heavy environments like Device Management. Description Devices (like Servers, Switches, Telecom Switches) are data-intensive systems. Their information model is so intensive, that practically all operations (health, inventory, metrics, configuration) on the device ends up in primarily as CRUD operations on the information model they expose. Only a paltry few operations are exposed as APIs. When building an API for managing these devices, we realized that providing classic function-style APIs only degraded the user experience. What we realized was there was significant information available on the Servers, and providing an API for exposing traditional CRUD (Create, Retrieve, Update and Delete) for all information nuggets was just exploding the API sets. It was not necessarily covering all the scenarios that could be possible for management and did not seem to scale. Our approach was to take this information model within the devices and expose them as a huge navigable data structure representing the entire spectrum of the device and provide a language native experience. We created a new type manager leveraging the python class special operators ( getattr (), setattr (), le () etc.) to create a whole new type manager that provides additional controls and safeguards. Some of the safeguards include: Not allowing edits to read-only components Allowing only applicable changes only (ranges, enumerations) Providing native python experience for special types (IP Address Types etc.) Providing mechanisms to validate cross-attribute validations Providing custom indices for arrays (like Virtual Disks, Users) Providing mechanism for tracking changes to configuration Apply changes to the device optimally Provide mechanisms for identifying configuration drifts Outline : Outline of the presentation: Introduction Device Configuration - Aspects & Peculiarities Pitfalls of API approach for Device Configuration Type Manager - introduction Super Types - Enumerations, Fields, Classes and Arrays Bringing in Native Type Experience Data as API - Enriched user experience Demo Q&A Key takeways to audience Audience will get an exposure: How to create your own type manager by overloading python type constructs Exposure to alternative approach to creating APIs for data-heavy systems & explore benefits Learn how type manager simplifies your life as well as the life of your consumers. Secrets of the python inbuilt __ operators - and how you can leverage them to provide native type experience even for your own custom classes How you can create a better user experience for customers in a simple way How you can incorporate Object Oriented SOLID principles", + "Last Updated": "10 Jun, 2018", + "Prerequisites": " General familiarity with type concepts (fields, arrays, classes, enums) is needed Exposure to in-built operators like ( getattr etc. will help) Exposure to Systems Management would be useful.", + "Section": "Core python and Standard library", + "Speaker Info": "Vaideeswaran Ganesan, Senior Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and data center products. His passion is compiler design, analytics, systems management, networking protocols and automation. Ajaya Senapati, Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and storage products", + "Speaker Links": "Vaideeswaran Ganesan\n 1. My Github Repository 2. My Linkedin Article which I wrote while implementing this Fun with Python Code Generation Ajaya Senapati\n1. Lin", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Vaideeswaran Ganesan (~vaideeswaran)", + "created_on": "10 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-as-api-building-a-type-manager-with-python~egyrb/", + "title": "Data as API: Building a Type Manager with Python" + }, + { + "Description": "Fog and haze (referred to as the atmospheric light) are the main cause of distortions, degradation in the quality of images clicked during foggy situations. But with the advancement in technology, thanks to Python and OpenCV libraries and brilliant minds of people out here in this small world, recovering almost a fog-free image has been made possible in recent times. And now we are moving towards making this algorithm more optimized so that it can work in real time for videos and live camera feed. Different mathematical models have been presented over the time for this algorithm but there are very few real-life implementations in any particular programming language, so here the Python implementation of this algorithm will be discussed. Basic steps and the ideas implemented will be discussed in a brief and different implementation will also be shown in the session", + "Last Updated": "10 Jun, 2018", + "Prerequisites": " Basic knowledge of the numpy functions. An idea about the OpenCV computer vision libraries and the different filters implemented there. Love for Python", + "Section": "Developer tools and Automation", + "Speaker Info": "Speaker: Vivek Modi Final Year undergrad at NIT Durgapur Tech Head at GNU/LINUX USERS' GROUP NIT Durgapur Summer Intern at DRDO (Integrated Test Range) Contributor in the project: Soumam Banerjee Final Year undergrad at NIT Durgapur", + "Speaker Links": "modiher", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Vivek Modi (~modihere)", + "created_on": "10 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-and-opencv-for-removing-fog-and-haze-from-an-image~ejBye/", + "title": "Using Python and OpenCV for removing Fog and Haze from an Image" + }, + { + "Content URLs": " Will have own slides. Link will be shared with all This GitHub Repo contains some of the content that will be delivered during the course of the talk. A lot of other websites from where I pick a point or 2", + "Description": "Everyday we listen to this word \"DATA\".\nBut after listening to that word, some questions might pop up in your mind. WHAT IS DATA? WHY DOES ANYONE NEED TO WORK WITH DATA? HOW TO UTILISE AND WORK WITH THIS DATA? Data is now one of the most important things for any business to run. From small startups to large companies, everyone looks at data to improve their business.\nEveryone looks at data to increase their profits. Everyone looks at data to understand why they failed and where they failed. Everyone looks at data to understand how a product gained success in the market. Basically Data is everything today for companies. Data is available everywhere now and it's become more important than ever to actually work with data and luckily we have great modules to work with data in Python. I'll be focusing on these modules and the power that data possesses. My primary focus here would be about the power of data. I surely will be talking about how to use this data in Python to make the most out of it, but before that I'd like the entire crowd to know what the power of data is. This would be a good talk for beginners honestly. Even if you have no idea about how data could be used or what is data, after this talk, you'll get a decent idea about it. Through this talk the 3 questions mentioned above in bold will be answered. The talk would progress in the following manner : Self introduction (3 minutes) Introduction about the topic (2 minutes) What is data? (3 minutes) Where is this data? (2 minutes) How to make the most out of data? (3 minutes) How Python helps in this process? (2 mins) Name and explain about different Python modules like Pandas, Numpy, Matplotlib and Seaborn in brief (10 mins)", + "Last Updated": "11 Jun, 2018", + "Prerequisites": "No prerequisites required. This talk will deal about everything from scratch and will give you a basic understanding of what modules could be used in Python. So you could research on those modules after the talk, but for the talk, no prerequisites required", + "Section": "Data science", + "Speaker Info": "Hey everyone, I'm Rahul Arulkumaran, a B.Tech 3rd year Student pursuing my major in Computer Science Engineering from Mahindra \u00c9cole Centrale, Hyderabad. I'm an open source and data science enthusiast. Coding is one thing I love doing all day and all night. Never feel like quitting.\nPython is my go to language. Anything I think of developing comes to life using Python. I have a very strong connection with Python as it was the first programming language I learnt. I'm also a full stack developer and perform data science on various datasets. I'm a Contributing and Managing Member in the PSF. I also am the President of the Computer Science Club in my college. Apart from that, I head the website development team for TEDxMahindra\u00c9coleCentrale and the Marketing and Promotions team for Aether (the techno cultural fest of MEC). I'm the Co-Founder and CEO of a startup which goes by the name FreeFlo. It is a product based company that looks at developing products related to Machine Learning, Blockchain and other related fields. I'm also currently interning in IIIT-Hyderabad in the Machine Translations and NLP Lab in the field of sentiment analysis. It might seem although I'm not interested in the non tech aspects of businesses, but I actually love working in teams related to business development and marketing. So that's mostly about it. Looking forward to interact with all of you out there ", + "Speaker Links": " GitHub My Blog Facebook LinkedIn Twitter Telegram Gmail ", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Rahul Arulkumaran (~rahulkumaran)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/power-of-data-and-working-with-it-using-python~bkgJb/", + "title": "Power of Data and Working with it using Python" + }, + { + "Content URLs": "-> How does a web framework work -> WSGI basics -> Getting hands dirty with coding More information will be uploaded soo", + "Description": "Build your own web framework using python .\nLets unleash the power of python by building a web framework from scratch . \nIt will help you understand what actually happens under the hood in most famous web framework", + "Last Updated": "11 Jun, 2018", + "Prerequisites": "Web development basics\nCuriosity\nTrust in python :", + "Section": "Web development", + "Speaker Info": "Not so useful BTech ( biotechnology ) from Thapar University\n2 years of experience working in pytho", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Pankesh (~PankeshGupta)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-our-own-web-framework-like-flask-in-python-from-scratch~el0je/", + "title": "Building our own web framework like flask in python from scratch" + }, + { + "Content URLs": "Will be uploading soon !", + "Description": "My philosophy has been : If you haven't build it you don't know it. So lets build a hadoop clone and see how it works . This workshop is basically about building your distributed processing system . It will take you through some basics of distributed system and we will try and build our very own distributed system in python ", + "Last Updated": "11 Jun, 2018", + "Prerequisites": "Google \"what is hadoop\" Google \"what is a distributed system", + "Section": "Networking and Security", + "Speaker Info": "class Pankesh (human)", + "Speaker Links": "class Pankesh (Human): def __init__ ( python=\"Python3\" ) :\n\n super.name = \"Pankesh gupta\"\n\n super.age = 25\n\n curiosity = True\n\n experience = 2\n\n education = \"Thapar University , Patiala", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Pankesh (~PankeshGupta)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lets-build-a-hadoop-clone-in-python~bm6Rd/", + "title": "Lets Build a Hadoop clone in python !!" + }, + { + "Content URLs": "Any related material will be shared soo", + "Description": "Financial data is difficult. It is sensitive to many unknown factors. So we need a good strategy for trading with deep learning. That's where reinforcement leaning comes in. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over.\nBy the end of the talk, you will learn:- What trading is? Why it's hard? How Can Deep Learning solve the trading problem? Why is reinforcement learning an effective solution?", + "Last Updated": "11 Jun, 2018", + "Prerequisites": " Willingness to learn Basic python", + "Section": "Data science", + "Speaker Info": "I have always been amazed by computers and how much you can do with soo little. Curiosity lead to passion. Passion lead me to work on some amazing things. AI is the buzzword around and I have been working on AI for quite some time and it's been a really great journey, challenging but rewarding. Recently, I started working with some startups. Currently, I'm working for a Silicon Valley startup, who has been working on making serious predictions on small data. I have also been interested in Fintech data. I started with simple fraud detection models and now I'm working on solving the trading problem with reinforcement learning", + "Speaker Links": "Connect on Twitte", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Himanshu Singh (~himanshu61)", + "created_on": "11 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-trade-with-reinforcement-learning~enX5b/", + "title": "Learning to Trade with Reinforcement Learning" + }, + { + "Content URLs": "https://www.tensorflow.org/ https://github.com/aymericdamien/TensorFlow-Example", + "Description": "Hey everybody!\nIf you have ever heard of this thing called as neural network , than this workshop is definitely for you .Neural networks are not new they been there for a long time . but they have become quite famous recently\ntensorflow is consisdered one of the best frameworks for getting started with neural networks and deep learning . About TensorFlow TensorFlow\u2122 is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google\u2019s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. We will also try and build an image recognition model using deep learning from scratch . Tensorlfow helps getting started with deep leaning and building neural networks ", + "Last Updated": "12 Jun, 2018", + "Prerequisites": "Basics of python and an open mind to learn new things ", + "Section": "Data science", + "Speaker Info": "Python lover . Machine learning enthusiast . Currently working on BIG ML ( training machine learning models on big data ) and efficient deployment of machine learning models on production ", + "Speaker Links": "Contributor at https://github.com/polyaxon/polyaxo", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Pankesh (~PankeshGupta)", + "created_on": "12 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-build-neural-networks-from-scratch-using-tensorflow~boKYb/", + "title": "Learning to build Neural networks from scratch using tensorflow" + }, + { + "Content URLs": "Will be updated on github before the conference", + "Description": " It is always essential to understand the genesis of evolution or the roots of revolution. Keeping in mind the above saying, in this workshop, I will provide a hands-on understanding of Blockchain technology using Python. There are multiple resources to get a firm understanding about this domain, but the best way to understand it is by using the concept of \"Learning-By-Doing\" . Following are few reasons why I want to willingly contribute to this domain: Blockchain is the underlying technology behind most of the\n cryptocurrencies and it has a potential of changing the way we work\n and communicate, making it more secure, efficient, and trustworthy. There is a immense amount of speculation going around in this domain\n with the rise of Bitcoin. What\u2019s happening with blockchain\n technology, I would say, is similar to the great American gold rush\n that happened in the mid 1800s. Innovators, investors, entrepreneurs, technologists all are hovering\n over the same underlying idea on how these cryptocurrencies work and\n how could blockchain be leveraged to create use-cases beyond\n crypto-systems. Also, I would love to mention few quotes to support the escalating phenomenon of Blockchain : The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping\neverything along its way by the force of its progression. -- William\nMougayar Over the next decade, there will be disruption as significant as the Internet was for publishing, where blockchain is going to disrupt\ndozens of industries, one being capital markets and Wall Street. -- Patrick M. Byrne I will help people in understanding the bits and bytes of this domain, including the basic cryptography concepts, algorithms and how to utilize the power of Python language to build their own blockchain. As we progress, we would engage into more advanced concepts pertaining to scalability and deployment once we build a minimalist prototype of aforementioned. Using on-the-go learning while developing will serve as a pivotal entry point for all the people who are willing to enter into this space and planning to build smart-contracts or invest in cryptocurrencies. Agenda for workshop : Introduction to Blockchain: Existing problems, what is Blockchain, why it matters, gist of few use-cases, related concepts. Python revisited: Functions, libraries, object-oriented programming terminologies, basic data structures, basics of zen of python. Blockchain under the hood: Cryptography 101, underlying data structure and algorithms, conceptual terminologies. Python and Blockchain amalgamated: Create blockchain using python. User-friendly front-end: Integrating the scripts in previous section with a basic front-end. Discussion regarding scalability methods and resources. Generating self-help focused Pypi library called pymyblockchain . (optional) Q&A session. Note: The above agenda is subject to change. It is tentative for now. Any changes will be updated here itself", + "Last Updated": "12 Jun, 2018", + "Prerequisites": "Basic python: Functions , Classes and Objects , Use of Libraries *No prerequisites apart from aforementioned. Even a person who is new to python will be able to grasp everything in workshop", + "Section": "Core python and Standard library", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "12 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchain-by-implementing-it-from-scratch-in-python~bq57b/", + "title": "Understanding blockchain by implementing it from scratch in Python" + }, + { + "Content URLs": "My python script", + "Description": "Information is being generated at an exponential rate everyday. There are multiple sources generating information. It becomes really tedious for a person to go and visit all the sources to obtain information. It could be of great help to the person if there can be a single source which cumulatively providing all the links of news generated by different newspapers. This is where web scraping and automation comes into picture. In this talk I want to explain how to scrape webpages hassle free , gather information and represent the gathered content in a easy to visualize format. By executing just a single Python file we can get all the data what we want from the web. Its not just about collecting the data, it is to reduce the repetitive work which a person does again and again to achieve the same goal. We can put repetitive work into a module and leave it upon the computer to do the same. This in turn will help us channelize our time more on the information rather than gathering that information. Agenda of Talk: Introduction: Web scraping, automation tools, parsing and scraping python libraries. How it helps in learning python extensively: My experience with web scraping and various use-cases on which I utilized. Q&A session.", + "Last Updated": "12 Jun, 2018", + "Prerequisites": "None", + "Section": "Developer tools and Automation", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "12 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping-and-automation-for-novice-users~er52d/", + "title": "Webscraping and automation for novice users." + }, + { + "Content URLs": "https://www.slideshare.net/mobile/karx01/micro-python-pycon-india-2018-proposal-kartik-aror", + "Description": "This session will aim to achieve 2 objectives Introduce you to (in a fun and practical way), what is microPython. equip you to be up and running to build your own systems!", + "Last Updated": "13 Jun, 2018", + "Prerequisites": "Must know a guy who owns a raspberry Pi", + "Section": "Embedded python", + "Speaker Info": "Hello World. I am Kartik Arora, founder at Akriya Technologies . Before starting my journey in the wild, I worked for Rivigo for a few months, and in Bing Team during my 2 years at Microsoft", + "Speaker Links": "https://twitter.com/karx_brb https://www.facebook.com/karx01 https://www.linkedin.com/in/karx01 https://github.com/kar", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kartik Arora (~kartik53)", + "created_on": "13 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/micropython-time-to-get-building~av58e/", + "title": "MicroPython : time to get building" + }, + { + "Content URLs": "GitHub More content will be updated soon", + "Description": "What is Transfer Learning? Transfer Learning is the method of reusing our existing knowledge developed for one task to solve a similar task. Say, you want to detect cars on night-time images and instead of learning from scratch we could reuse our existing knowledge from a model which has been trained on day-time images. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. I believe Transfer Learning is a major achievement in our quest for Artificial General Intelligence (AGI) as Transfer Learning allows us to generalize our knowledge which is something we humans excel at. Andrew Ng, ex-chief scientist at Baidu, co-founder of Coursera and professor at Stanford, said during his widely popular NIPS 2016 tutorial, \u201cTransfer Learning will be the next driver of ML success.\u201d Training Deep Neural Networks from scratch is an expensive process. Not only does it require a lot of compute resources and time, deep Learning models require a huge amount of data and it is a major bottleneck when it comes to start-ups and niche areas of research like health care. What you will learn :- How to build an image classifier in a few minutes using Transfer Learning When and how to fine-tune pretrained models Freezing layers of a pretrained model depending upon the scenario Using ConvNet as a feature extractor Using differential learning rates Constraints of using pretrained models Transfer Learning : Beyond Computer Vision Cross-Lingual Domain Adaptation : Using the knowledge we have learnt from one language and applying our knowledge to another language is another application of transfer learning with huge potential. Cross-lingual adaptation methods would allow us to leverage the vast amounts of labeled data we have in English and apply them to any language, particularly languages with very less labeled data such as Indian languages. Reinforcement Learning and Learning from Simulations : Training an agent (in Reinforcement Learning) to achieve general artificial intelligence directly in the real world is too costly and hinders learning initially through unnecessary complexity. It is better to train an agent in a simulated environment such as the OpenAI Gym before deploying it in the real world. Eg: Self-driving cars Agenda 1.Introduction to Computer Vision (3 min) 2.Introduction to Transfer Learning (3 min) 3.Why should you use Transfer Learning? (2 min) 4.When to use Transfer Learning? (2 min) 5.Build an image classifier in minutes using Transfer Learning (2 min) 6.Effective Transfer Learning techniques (6 min) 7.Feature Extraction using pretrained models (3 min) 8.Constraints of using pretrained models (1 min) 9.Transfer Learning beyond Computer Vision (3 min) 10.Transfer Learning : A right step towards Artificial General Intelligence (AGI) (2 min) 11.Q&A session (3 min", + "Last Updated": "14 Jun, 2018", + "Prerequisites": "Basic knowledge of deep learning Love for Pytho", + "Section": "Data science", + "Speaker Info": "Hi! I\u2019m fascinated by AI and it\u2019s applications particularly in art and culture - generating art, fashion styles, music, literature, etc. I\u2019m a 3rd year student at SRM Institute of Science and Technology, Chennai studying Computer Science Engineering. I\u2019m also part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in AI, Blockchain, Computational Biology, Electrical Systems, Internet of Things, and Mixed Reality. I'm also a part of a club which organizes PyData KTR . I will be talking about \"Abstract Art using Compositional Pattern Producing Networks\" in the next meet-up which is scheduled on 14th July, 2018. I\u2019m currently working as a Computer Vision intern at Cogknit Semantics, Bangalore. I'm working on a fashion recommender system which analyses images of clothes and suggests matching clothes to go along with it. Eg: Suggests matching pants and shoes if the input image is a shirt. I love Python because of it\u2019s simplistic philosophy and lucid coding style which allows me to think more about model architectures rather than fixing bugs in my code", + "Speaker Links": "Connect with me on LinkedIn Find me on GitHub Follow me on Twitter E-mail me at : niladrishekhardutt@gmail.co", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "niladri99", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-subtle-art-of-effective-transfer-learning~dw5ra/", + "title": "The Subtle Art of Effective Transfer Learning" + }, + { + "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", + "Description": "Problem description : Deep learning algorithms have shown great results in speech recognition domain, So here we have used deep learning techniques to enable the machines to read the lips from a video without sound better than humans. By analysing the movement of lips of a person we are trying to predict what that person is trying to speak.\nAutomated Lip reading can be helpful in many ways. Some of them are: Silent dictation in public spaces. Covert conversation. Helping the people with speaking ade in talking to other people. Improved hearing aids. Speech recognition in a noisy environment. The talk will be focused on : How the problem should be tackled. Discussion of different phases Algorithms and python libraries used for implementation.", + "Last Updated": "14 Jun, 2018", + "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations Basic understanding of Recurrent Neural Networks : An excellent resource to understand this is Understanding LSTM Networks . Similar to CNN the motive should be to understand the basic working of Recurrent Neural Networks. The coding part will be discussed in the talk.", + "Section": "Developer tools and Automation", + "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", + "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Saqhas", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-lip-reading-using-convolutional-neural-networks-in-python~ejMvd/", + "title": "Automated Lip reading using convolutional Neural Networks in python" + }, + { + "Content URLs": " Research Paper Github repository of project with over 100 stars: pyCAIR Beta release on PyPI: pyCAIR Docs: pycair.readthedocs.io", + "Description": "In this talk, I will speak about a simple yet very powerful image manipulation mechanism. The naive user utilizes the services of any standard toolkit, be it a web service or a remote application for image manipulation. The black box approach to this process is: A user provides an image and other parameters as input to the toolkit which in turn produces the results and returns it back to the user. Often these results are not up to the mark. The image sometimes gets distorted, misaligned or blurred. Deviating from the standard mechanisms, I would like to talk about a technique called as Content aware image resizing . The primary factor in this technique is the content . It is the content which drives the entire technique. The image is cropped, enlarged or modified keeping in mind the primary factor. I will talk about an algorithm called as Seam Carving which is used under the hood to achieve the aforementioned technique. It is this algorithm and the power of Python libraries , that makes this technique perform better than the standard mechanisms. Agenda of Talk: Introduction: Basics of seam carving, how the algorithm works Understanding energy concepts, basics of computer vision and dynamic programming Walk over the pseudo-code and dry run of algorithm Comparative analysis of this technique with standard mechanisms Q&A Session Conclusion", + "Last Updated": "14 Jun, 2018", + "Prerequisites": " Basics of Python", + "Section": "Developer tools and Automation", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pycair-understanding-content-aware-image-resizing-using-python~bkK6b/", + "title": "pyCAIR: Understanding Content-Aware Image Resizing using Python" + }, + { + "Content URLs": "Will be provided soo", + "Description": "Everyone need not to know everything to build something great. If you are a student and wants to build a major/minor or a professional level project without worrying about the DevOps/Servers and its cost. If you are a Data Scientist and works with files/data and want to make your analytical tool public but you don't want to get in Server handling and learning some web framework . If you are a Frontend developer or work in a fast paced organisation where shipping out fast, better, robust and always running services are required. If you want to prepare a POC or a working model API fast without the requirement of server engineer. Then, this Talk is the place which your are looking for. This talk will be focused on How one can build really scalable and robust web APIs without learning any web framework that too in a very very easy manner. We will be talking about a python package I have made called Lamlight which makes the process of building web APIs as simple as a Git push . This package provides a CLI tool and answers the limitations imposed by the services like AWS lambdas . Lamlight enables Developer to: Make web APIs without learning any web framework or DevOps. Just focus on the core business logic because everything else it will provide you. (Eg: full python boilerplate, CLI automation tool ) Live code Changes. Put large dependencies on your Serverless web api like Numpy, Scipy, Pandas. Save 80% of time by making the process as simple as Git push. Objective of the Talk: Problems faced in a Servered Architecture. Introduction to Serverless Web APIs. Why Shift to Serverless Web Architecture. Platforms providing these Services and their limitations. Get Faster and beat these Limitations. Problems solved by Lamlight. Explanation of its working. Live demo. Q & A The talk would be extremely beneficial for students, Algorithm developer, Frontend Developer, Data scientists and others who are not familiar with server side development and server technologies or want to save time of server handling but still want their work to be done", + "Last Updated": "14 Jun, 2018", + "Prerequisites": " Love for Python Linux AWS(Optional)", + "Section": "Developer tools and Automation", + "Speaker Info": "Hello I am Rohit Negi. I am a developer with 1 year of professional experience and +2 years of freelancing experience. I have a Bachelor's degree and I am currently working as a developer in Elucidata Corporation, where I work on making technical architectures for the system to get connected and work robustly , designing Server APIs, Working with Frontend technologies like Angular to make the robust Frontend apps. I am very passionate about creating new and better stuff", + "Speaker Links": " https://www.linkedin.com/in/rohit25negi/ Email: rohit25.negi@gmail.com", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Rohit Negi (~rohit17)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lamlight-develop-webmobile-apps-without-learning-django-flask-and-any-other-web-framework~egKke/", + "title": "Lamlight: Develop web/mobile apps without learning Django, Flask and any other web framework" + }, + { + "Content URLs": "GitHub Repo: https://github.com/sleebapaul/gospel_of_rnn.git Google Colab Notebook: https://drive.google.com/file/d/1qh94MdQr9SeTLxGkMJc6kZGguRID8LqW/view?usp=sharing Blog: https://sleebapaul.github.io/rnn-tutorial", + "Description": "Language modeling was a complex task of previous days. But advancements in Deep Learning has solved this problem very effectively. Using Recurrent Neural Networks architecture, I've built a language model which can effectively generate the fifth gospel of bible by learning from four existing gospels. This model is also able to divide verses and chapters along with meaningful passages", + "Last Updated": "14 Jun, 2018", + "Prerequisites": " Recurrent Neural Networks basics Deep learning basics Language modeling basics Familiarization with PyTorch", + "Section": "Data science", + "Speaker Info": "Sleeba Paul is a Power System graduate and published researcher who loves intelligent machines. He currently works as a Machine Learning Engineer at Refly; an AI startup in India where he works on content enhancement and video analytics", + "Speaker Links": "Personal website: http://sleebapaul.github.io/ LinkedIn: https://www.linkedin.com/in/sleebapaul/ Github: https://github.com/sleebapau", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Sleeba Paul (~sleeba)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gospel-of-lstm-how-i-wrote-5th-gospel-of-bible-using-lstms~elLMe/", + "title": "Gospel of LSTM : How I wrote 5th Gospel of Bible using LSTMs" + }, + { + "Content URLs": " Hello world of chatbots world - wordbot An Experiment with Opensource chatbot engine - RASA NLU ", + "Description": "Google Assistant and Siris\u2019 of the world have tickled our curiosity enough to deep dive and understand under the hood technologies that make a chatbot. Though we don\u2019t have Google level of data to create a generalized chatbot, we can use the existing NLP engines and create chatbots that produce valuable results in a specific domain. For eg., anything that goes in your FAQ page can be converted into content for a chatbot. In this talk, I\u2019ll share my 2-year journey with chatbots. Existing bot platforms and how to leverage it to build your own chatbots. I'll also share the internals of an opensource chatbot engine - Rasa NLU. Key Takeaways Chatbot\u2019s architecture (3 mins) Natural language Processing, Understanding, and Generation what and how it plays an important role in building chatbots(3 min) How to use existing chatbot engines to build a chatbot(6 min) Internals of a chatbot engine - Demystifying RasaNLU (15 mins)", + "Last Updated": "14 Jun, 2018", + "Prerequisites": "Basic knowledge of Pytho", + "Section": "Data science", + "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape - Tech Enthusiast - Django & Chatbot specialist - Mentor/Speaker Build2learn , Chennai Geeks. Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", + "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavan", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Bhavani Ravi (~bhavaniravi)", + "created_on": "14 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatbots-101-by-demistifying-rasanlu~bm6Gd/", + "title": "Chatbots 101 - By Demistifying RasaNLU" + }, + { + "Content URLs": "Source code available on Github: https://github.com/Cheukting/Style-mimicking-text-generator Example slides: https://slides.com/cheukting_ho/pylondinium1", + "Description": "Computers are getting closer to speak like humans. But can we even make them speak in particular ways, like as Trump or Shakespeare? In this hands on talk we will see how this is possible with the latest deep learning techniques combined with word embeddings and other advanced NLP technique. In this talk, first we would introduce two neural network and machine learning mechanisms which in popular and widely used in NLP (natural language processing): Word Embeddings and Recurrent Neural Network. Word Embeddings is a way to extract the context of a word by \u201clearning\u201d its presence in a paragraph; while Recurrent Neural Network, including LSTM (long short-term-memory), enable us to \u201ctrain\u201d sequential data. After that, we will showcase how to implement these mechanisms in a neutral network. With that, we can \u201cbuild\u201d a machine to generate articles, plays or speeches in the style of the training corpus and have lots of fun. In the first half of the talk, concepts of how Word Embeddings and LSTM works will be explained. Audiences will understand why this is essential in the field of NLP and why we are using it. In the second half, a code demo will be used to showcase how to implement these mechanisms. Through an example, audiences will learn how Keras is used together with Tensorflow and Python to build a sequential neutral network. We will showcase generating a paragraph using Shakespeare\u2019s play and another one using Trump\u2019s speech. This talk is for people who have some experience with data science and understand the concept of how a neural network works, but would like to go deeper into the details of how does it applied to NLP to solve more complex AI problems. We used very simple code but did a complex task like text generation, that opens the door for a lot of people who wants to experiment with deep learning", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "Basic concepts of Neural Network like Stochastic Gradient Descent and back propagation, as it will not be covered in the talk due to time limit", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-keras-building-an-ai-that-talks-like-shakespeare-or-trump~enX7b/", + "title": "Deep Learning with Keras : Building an AI that Talks like Shakespeare or Trump" + }, + { + "Content URLs": "Project source code on Github: https://github.com/Cheukting/GCP-GPU-Jupyter Demo code: https://github.com/Cheukting/jupyter-cloud-demo Example slides: https://www.slideshare.net/CheukTingHo/pycon-israel-launch-jupyter-to-the-clou", + "Description": "There are lots of reasons using a cloud service is favorable, but how to make sure consistency between development and deployment? With Docker and Terraform, we can create the same environment on cloud easily. For example, we will deploy a Jupyter notebook on Google Cloud Platform using both tools. In this talk, we will use a task: hiring a GPU on Google Cloud Platform to train neural network, as an example to show how an application can be deployed on a cloud platform with Docker and Terraform. The goal is to have Jupyter Notebook running in an environment with Tensorflow (GPU version) and other libraries installed on a Google Compute Engine. First we will briefly explain what is Docker and what is Terraform for audiences who has no experience in either or both of them. Some basic concepts of both tools will also be covered. After that, we will walk-through each steps of the work flow, which includes designing and building a Docker image, setting up a pipeline on Github and Docker Hub, writing the Terrafrom code and the start up script, launching an instance. From that, audiences will have an idea of how both tools can be use together to deploy an app onto a cloud platform and what advantages each tool can bring in the process. This talk is for people with no experience in application deployment on cloud service but would benefit form computational reproducibility and cloud service, potentially data scientists/ analysts or tech practitioners who didn\u2019t have a software developing background. We will use an example that is simple but useful in data science to demonstrate basic usage of Docker and Terraform which would be beneficial to beginners who would like to simplify their work flow with those tools", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Developer tools and Automation", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/launch-jupyter-to-the-cloud-an-example-of-using-docker-and-terraform~boKXb/", + "title": "Launch Jupyter to the Cloud: an example of using Docker and Terraform" + }, + { + "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/seatgeek/fuzzywuzzy Source code available on Github: https://github.com/Cheukting/fuzzy-match-company-name Slides (not finalized): http://slides.com/cheukting_ho/fuzzy-matchin", + "Description": "Ever encounter a tricky situation of knowing there\u2019s names that are the same, but matching strings straight away leads you no where? All you need is FuzzyWuzzy, a simple but powerful open-source Python library and some wit. This talk will demonstrate how to efficiently fuzzy match company names. Matching strings should be one of the first natural language processing problem that human encounter since we start use computer to handle data. Unlike numerical value which has an exact logic to compare them, it is very hard to say how alike two strings are for a computer. One may compare them character by character and have an idea of how many characters in the pair of stings are the same. Unfortunately in most application we need computer to perceive strings like we do and therefore we have to use fuzzy matching. Fuzzy matching on names is never straight forward though, the definition of how \u201cdifference\u201d of two names are really depends case by case. For example with restaurant names, matching of words like \u201ccafe\u201d \u201cbar\u201d and \u201crestaurant\u201d are consider less valuable then matching of some other less common words. Also, do we consider company names that matches partly (like \u201cHappy Unicorn company\u201d and Happy Unicorn co.\u201d) are the same? In the first half of the talk Levenshtein Distance, a measure of the similarity between two strings, will be explained. Different functions in FuzzyWuzzy like \u201cpartial_ratio\u201d and \u201ctoken_sort_ratio\u201d will also be explored and compared for difference. It is very important to understand our tool and choose the right one for our task. Then in the second half, we will start tackling the example problem: matching company names, we will show that besides using FuzzyWuzzy, we have to also handle problem like finding and avoid matching of common words and speeding up the matching process by grouping the names. By combining all tricks and techniques that we demonstrate, we will also evaluate how efficient this method is and the advantage of using this method. This talk is for people in all level of Python experience who would like to learn a trick or two and would like to be able to solve similar problems in the future. Theory of how the library works will be explained and It is easy to be pick up even for beginners", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fuzzy-matching-smart-way-of-finding-similar-names-using-fuzzywuzzy~epKVd/", + "title": "Fuzzy Matching - Smart Way of Finding Similar Names Using FuzzyWuzzy" + }, + { + "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/networkx/networkx Slides (not finalized): https://docs.google.com/presentation/d/1y_Wmuv_hqs8OZTI8XLJ5ajvjEpllK7Xeifa52yTpw-k/edit?usp=sharin", + "Description": "When you make a search for a hotel room, do you know how many travel agents are searching for you at the same time? In this talk, we demonstrate how to use the millions of searches a sourcing company received to build a network of travel agents and finding the main hubs among them using NetworkX. Network analysis is getting more and more attention in Business Intelligence, people hope to get information out of the structure of an organization or a communication network. In this talk, we use the hotel room search requests from travel agents, including online public website, B2C, B2B and B2B2C, to build a relational network among them. By using this network as an example, we demonstrate how insights can be extract by studying network properties. In the first half of the talk, we will explain how the network is built using NetworkX, an open-source python library that is designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. When 2 agents are making the same search at the same time , a link ( or an \u201cedge\u201d in network analysts terms) is made pointing form the initial searcher to the subsequent searcher. Using a list of these searches, a directed graph is built. We will also demonstrate how to pick the biggest connected component out form the graph. In the second half, with the graphs created, we show how different functions of NetworkX can be used to study the graphs. By compare the graph properties of our graph to the other popular network graphs, we can get the insight of how the network was created. Also by studying the graphs, we can understand the behavior of the agents and can even figure out which agents are acting as main hubs in the network. This talk is for people who are interested in network analysis and would like to see how it can be used in a business case. Audiences with any level of python experience can learn some basic concept of network analysis work and how it can be applied to provide business insights", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-understanding-agent-connections-using-networkx~bq5pb/", + "title": "Case Study in Travel Business - Understanding agent connections using NetworkX" + }, + { + "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/welch/seasonal Example Slides: https://www.slideshare.net/CheukTingHo/pydata-amsterdam-2018-time-series-analysis-with-seasonal-data-9909335", + "Description": "For time series analysis, everyone\u2019s talking about ARIMA or Holt-Winters. But there\u2019s other models which could also break down a seasonal series into trend, seasonality and noise. We will use an open source Python library called Seasonal to analyse B2B worldwide travel data. Times series analysis is an important part of data analysis for lots of businesses. It is very often for stakeholders to be interested in the performance of the business by analyzing measurements of profit, cost, number of sale, number of searches etc over time. In this talk, we will do a case study of showing how we estimate the impact public holidays made on the travel business. The method of analyzing the time series by seasonal breakdown will be explored and the work flow of solving the problem will be explained. In the first half of the talk, an introduction about time series and its characteristic will be explained for audiences who is new to analysis on time series. The data we use will be from a business to business travel company. It has seasonality thought out the year, a weekly cycle and also a growing trend in business. As the company have clients around the world, data from different countries will shows different behaviors as well. Therefore, before we show the analysis, the complexity of the data will be explored. In the second half, we will introduce a open source Python library called Seasonal. Using this package, we will demonstrate how to break down the travel data and extract the fluctuation of the sale in different countries. By comparing the fluctuation and Google calendar, public holidays in different countries can be spotted and their impact on the business can be estimated. This talk is for people who are interested in time series analysis and its application in business. Audiences with or without experience would also found this talk useful in giving them insights in how a business could benefit in making use of the data and doing a proper time series analysis", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "None, it's a beginner friendly talk", + "Section": "Data science", + "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", + "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Cheuk Ting Ho (~Cheukting)", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-time-series-analysis-with-seasonal-data~er5pd/", + "title": "Case Study in Travel Business - Time Series Analysis with Seasonal Data" + }, + { + "Content URLs": " Code will be updated on github very soon.", + "Description": "There are many framework available in the market for free and with a lot\u2019s of feature like Django , Flask , Tornado . These framework help us to build web application and serving the files over the network without worrying about the low level details like how it works , how the files are being severed to the clients , web browser and how it handles the clients to be connected and serving the data to the lot\u2019s of clients with minimum amount of time with managed thread. So in this talk I\u2019ll share my knowledge how does the web server work and how we can build our own framework like other available framework and further enhance it , to make it big, and to handle the clients with multiple processes and threads. In this talk I will be talking about : What is a WebFramework and How does a web framework work? How we can make a simple web sever to serve the \u201chello world\u201d webpage to the browser How we can make the HTTP custom request header to tell the browser about the current status of request on the different situation like 200 , 404 , 500. how to server files like html, css to generate the advance webpages using socket to the browser. Getting the requested URL Params and serving the files over the network. Making a Download link and let the user to download the files over socket. Improvement of request and response time of the web server and optimising it so that the web server can handle more and more clients over the network. ", + "Last Updated": "15 Jun, 2018", + "Prerequisites": "1. Basic python understanding. 2. Python installed on your system. 3 .Socket library (you can install it using the pip installer", + "Section": "Core python and Standard library", + "Speaker Info": "I am Nawneet Kumar, CTO at Elezire Technologies Pvt. Ltd. I have worked in Different Projects and in Different Languages in my past year. I have worked in era like IOT Development , Android Application Development , IOS Development and Web Development", + "Speaker Links": "Linkedin : https://www.linkedin.com/in/nawneet-kumar-77b64814b/ github : https://github.com/navSharma4", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "nav.sharma47", + "created_on": "15 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-own-webframework-like-django-flask-tornado-to-serve-web-application-using-core-socket-programming~av55e/", + "title": "Building Own WebFramework like Django , Flask , Tornado to serve Web Application using Core Socket Programming" + }, + { + "Content URLs": "Apache_Build_Monitor Jenkins' REST API & Pytho", + "Description": "As a build and release engineer, have you felt how good it would be to know the status of scheduled nightly builds before you reached office ? As a developer, have you wondered, while you were away from the desk, what's the status of quality gate builds that should be passed before the changes can be integrated to the mainline ? Intent of this talk is to outline what's offered via Jenkins's REST API and showcase some of the possibilities by consuming the API using Python", + "Last Updated": "16 Jun, 2018", + "Prerequisites": " Read-up docs on Python libraries XML, JSON Capability to follow and assimilate code snippets", + "Section": "Developer tools and Automation", + "Speaker Info": " Speaker works for a CyberSecurity firm in Bengaluru, India Likes being outdoors and reading books.", + "Speaker Links": "Linkedi", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Ramanathan Muthaiah (~ramanathan)", + "created_on": "16 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/consuming-jenkinss-rest-apis-in-python~dw58a/", + "title": "Consuming Jenkins's REST APIs in Python" + }, + { + "Content URLs": "http://github.com/gnsrikanth/simplelinuxbackdoor/ https://medium.com/@gnsrikanth/creating-a-tcp-backdoor-using-python-9edafc213f9", + "Description": "In this talk, we discuss how python scripts can be used in the world hacking. Python can be used to automate many tasks and we see network protocols using python. Programming isn't just codes, but it's a way of communication. This talk is more of an awareness about the possibilities of python can be used and hacking is one of them. We break down steps to hack a system and automate tasks using python. Topics covered: Sockets in python Using TCP, UDP protocols and creating a Server/Client A basic backdoor for windows Using HTTP protocol to steal users data Using encryption to obfuscate network traffic Subprocess module Pyinstaller to make binaries of malware Bypassing antivirus (we will test it by uploading .exe to virustotal) Using Sqlite3 to retrieve chrome passwords Emailing subprocess outputs with python Send data to google forms as POST Simple Ransomware code Other Python tools for hacking", + "Last Updated": "16 Jun, 2018", + "Prerequisites": "Basics in python, Operating system fundamentals, Networking basics", + "Section": "Networking and Security", + "Speaker Info": "I am Grandhi Srikanth, and truly passionate in cyber security. I hold C|EH, CCNA in Routing and Switching, Cyber Ops certification and interested in creating malware codes and as python makes it simple, I use python", + "Speaker Links": "Twitter: @gn_srikanth LinkedIn: https://www.linkedin.com/in/grandhi-naga-srikanth/ Github: https://github.com/gnsrikant", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Naga Srikanth Grandhi (~naga_srikanth)", + "created_on": "16 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/backdooring-windows-with-python~ax5Bb/", + "title": "Backdooring windows with python" + }, + { + "Description": "We have a word for it now - Domotics . The fun started a year back when I laid hands on this beautiful device from Amazon, which could not only manage your music, reminders, lists but also make calls and send messages. Basically, a smart phone in the cloud to be used without hands. But a developer sees endless possibilities with this powerful tool. Although speech recognition technology itself is nothing new, Amazon Echo has made its way to the homes of regular consumers. This talk is specially focused on giving a head start to the attendees about building and using powerful applications in python using an Alexa device. Being a python developer for the past 10 years and working on alexa skills for the past year, I intend to share my experience with the python community and enthusiasts. Broadly, this talk will be covering the following topics: How the echo framework and Alexa skills work An introduction to creating alexa skills in python with flask-ask Handling requests , responses , contexts and sessions . Testing applications with ngrok and deploying to the cloud. A sneek peek into other home automation possibilities like micropython embedding with popular microprocessors. The talk would be illustration and example driven and will include demos of cool app(s) I have been working on", + "Last Updated": "17 Jun, 2018", + "Prerequisites": "This talk is intended for developers who have a decent grasp on the basics of the python framework and trends, although you do not need knowledge of any specific packages or libraries. Just an enthusiastic mind is enough! The primary takeaway of this talk would be learning how to get started ideating and building applications for an alexa enabled smart home device and discuss some cool developer tips", + "Section": "Developer tools and Automation", + "Speaker Info": "Sonal Raj ( @_sonalraj ) has been an avid pythonista for 10 years. He has been working as an integral part of the financial technology industry for the past 4 years. Sonal holds a masters in Information Technology and has been a research fellow at the Indian Institute of Science, Bangalore. His domains of interest include distributed systems and graph databases, and he loves to explore new gadgets and develop new technology. He is also the author of the best selling book 'Neo4j High Performance' ", + "Speaker Links": " Talk at PyCon India 2014 Talk at PyCon India 2013 Real Time Computation with Apache Storm - IISc Bangalore Human Computer Interaction Systems : Slides Website Github Reasearch Profile", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Sonal Raj (~sonal)", + "created_on": "17 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/alexa-enabled-smart-home-programming-with-python~dy5nd/", + "title": "Alexa enabled smart home programming with Python" + }, + { + "Content URLs": "A library for ANTLR that is being built by me is available here: https://gitlab.com/virresh/coala-antlr ANTLR's official page: http://www.antlr.org/ My blogs related to ANTLR in Python: https://virresh.wordpress.com/tag/antlr/ An example calculator: https://github.com/virresh/ANTLR4-Exampl", + "Description": "This talk aims at introducing ANTLR for python 3, and talk about Abstract Syntax Trees. It will present an overview of the process, the intricacies and will end with a concrete example to show the utility. ANTLRv4 is a tool that can generate parse trees for any compatible grammar, and provide tools to walk through that tree, so I will illustrate how to use that rather than dwelling more on the theory aspect of the parse trees and boost up the development of language tools. There is a speciality with ANTLRv4, we can separate context from the grammar (so we can get very close to the expectation that grammars are context free). I expect the session to be beginner friendly so no pre-requisites save some basic python expected. Also I will cover some basic examples, and also a demo of an actual language grammar to create a meta-program if time permits. The session is expected to have the following things: What is a grammar ? What are Parse trees and how do they compare to ASTs ? What is ANTLR ? (The parser generator and the runtime provided) How do we use a parse tree ? (dwelling on setting up the environment for ANTLR based development and a short, basic calculator building example) Visitors and Listeners A short real world example on detecting technical constricts in actual programming languages (probably Python itself)", + "Last Updated": "17 Jun, 2018", + "Prerequisites": "A working knowledge of python basics and some familiarity with some sort of command line interface is ideal (best suited if you are familiar with any unix/linux based systems, simple script invocation etc", + "Section": "Developer tools and Automation", + "Speaker Info": "I'm a student presently pursuing BTech in CSE at IIIT-Delhi, and am a GSoC student this year at coala.io and have been programming various stuff using python for around two years. I am developing a library to facilitate easy usage of ANTLR for building linting tools. I've worked on a large array of technologies in any area that I get to know about, ranging from Full stack development, to Systems programming to Language tools. I do my best to pick up and experiment with whatever technologies I can, and I love to learn ", + "Speaker Links": "GitHub: https://github.com/virresh Website: https://virresh.github.io/ Blogs: https://virresh.wordpress.com/ LinkedIn: https://www.linkedin.com/in/virresh", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Viresh Gupta (~virresh)", + "created_on": "17 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-antlr-with-python~az5ye/", + "title": "Using ANTLR with python" + }, + { + "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. \nThe website for the workshop is here . \nYou can find the introduction slides here , the sphinx tutorial here and the exercises in form of IPython notebooks. Note: The notebooks are hosted statically, you can download from here and run locally to have an interactive session. See Also: Workshop content for PyCon conference in 2015 , SciPy conference in 2016 , 2014 and 2013 ", + "Description": "In this tutorial we will introduce attendees to SymPy, a computer algebra system (CAS) written in Python. We will show basics of constructing and manipulating mathematical expressions in SymPy, the most common issues and differences from other computer algebra systems, and how to deal with them. In the last part of this tutorial, we will show how to solve practical problems with SymPy. This will include showing how to interface SymPy with popular numeric libraries like NumPy. Attendees will take home an introductory level understanding of SymPy. This knowledge should be enough for attendees to start using SymPy for solving mathematical problems and hacking SymPy's internals (though hacking core modules may require additional expertise). SymPy is a pure Python library for symbolic computation. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. The tutorial will cover the following topics and more. Introduction What is Symbolic Computation? A More Interesting Example The Power of Symbolic Computation Why SymPy? Gotchas Symbols Equals signs Two Final Notes: ^ and / Basic Operations Substitution Converting Strings to SymPy Expressions evalf lambdify Printing Printers Setting up Pretty Printing Printing Functions Simplification simplify Polynomial/Rational Function Simplification Trigonometric Simplification Powers Exponentials and logarithms Special Functions Calculus Derivatives Integrals Limits Series Expansion Finite differences Solvers A Note about Equations Solving Equations Algebraically Solving Differential Equations Matrices Basic Operations Basic Methods Matrix Constructors Advanced Methods Advanced Expression Manipulation Understanding Expression Trees Recursing through an Expression Tree ", + "Last Updated": "18 Jun, 2018", + "Prerequisites": "The tutorial will only assume a basic knowledge of Python. No prior knowledge of SymPy or other Python libraries is required, although it is suggested that attendees be familiar with the IPython notebook. A mathematical knowledge of calculus is recommended. We recommend that the attendees install the Anaconda Python distribution which includes SymPy, NumPy, and IPython. Once Anaconda is installed simply type the following in a terminal to install the necessary packages: $ conda install numpy ipython-notebook sympy Other alternative installation instructions can be found here: http://docs.sympy.org/dev/install.htm", + "Section": "Data science", + "Speaker Info": "SymPy India developers will be conducting the workshop: Shekhar Prasad Rajak : GSoC 2016 | Solvers Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers Module Ravicharan : IIIT Allahabad | Core Developer at SymPy, GSoC 2018 | Combinatorics module Jashanpreet Singh : TIET Patiala | Core Developer at SymPy, GSoC 2018 | Beam Bending module", + "Speaker Links": " Resource repository: https://git.io/sympy-pycon-india-18 SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://youtu.be/5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://youtu.be/nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://youtu.be/AqnpuGbM6-Q SymPy, SciPy 2014: https://youtu.be/Lgp442bibDM Symbolic Computing with SymPy, SciPy 2013: https://youtu.be/dAgShwIx72c", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Yathartha Joshi (~Yathartha22)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-python-using-sympy~aAold/", + "title": "Symbolic Computation with Python using SymPy" + }, + { + "Content URLs": " Hydra Draft Book of Hydrus Hydra Ecosystem Wiki Hydrus Hydra Flock Demo Hydra CG homepage I'll be sharing my slides after the talk", + "Description": "Introduction 3rd generation Web APIs enables creation of truly RESTful services with all its benefits in terms of scalability, maintainability, and evolvability. This allows to create Generic Consoles and loosely coupled clients. The main objective of this talk is to provide an overview of Hydra and Hydrus and how we can create such APIs using Hydrus. Hydra Building Web APIs seems still more an art than a science. How can we build APIs such that generic clients can easily use them? And how do we build those clients? Current APIs heavily rely on out-of-band information such as human-readable documentation and API-specific SDKs. However, this only allows for very simple and brittle clients that are hardcoded against specific APIs. Hydra, in contrast, is a set of technologies that allow us to design APIs in a different manner, in a way that enables smarter clients. Hydrus Hydrus is a Flask server meant to build and deploy Hydra-based Web APIs in a straightforward and effective way. Hydrus utilises the power of Linked Data to create a powerful REST APIs to serve data. Hydrus uses the Hydra draft standard for creation and documentation of it's APIs. The flow of the talk will be as follows: My Introduction What is Hydra Draft? A detailed introduction to Hydrus How can Hydrus be used to create Semantic Web APIs easily? Some Use Cases A short demo Q/A session", + "Last Updated": "18 Jun, 2018", + "Prerequisites": " Python Basic knowledge of Web APIs", + "Section": "Web development", + "Speaker Info": "My name is Akshay Dahiya. I'm a Mentor and Organization Admin for Python Hydra in Google Summer of Code 2018 and I love working on Semantic Web and Artificial Intelligence-related projects. I also mentor a couple of students across various Udacity Nanodegree programs (FullStack Nanodegree, React Nanodegree and Deep Learning Nanodegree) in my free time", + "Speaker Links": " http://www.xadahiya.me/ https://github.com/xadahiya/ https://www.linkedin.com/in/xadahiya/ http://www.typingeek.com/", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Akshay Dahiya (~xadahiya)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3rd-generation-web-apis-using-hydra-and-hydrus~dBpYa/", + "title": "Creating 3rd generation Web APIs using Hydra and Hydrus" + }, + { + "Content URLs": "https://docs.google.com/presentation/d/1_hyRLHdITpIMzhAbpxuaTQkm6qop4ZWQt6ERGW4MFag/edit?usp=drivesdk&ouid=10471550379351873801", + "Description": "This is a simple talk about web scraping using python.In this lecture we going to have a clear picture of webscraping. \nBy the end of the lecture audience are going to have a clear picture of \nWhat is web scraping? \nWhat is the use of it? \nWhat are the useful libraries in python for web scraping? \nPros and cons of the libraries\nAnd mainly how to parse the Websites with practical examples", + "Last Updated": "18 Jun, 2018", + "Prerequisites": "A little amount of python knowledge is useful but not mandatory. I'm going to explain right from the very beginnin", + "Section": "Others", + "Speaker Info": "I am a student of Vishnu Institute of technology, Bhimavaram. I am studying 2nd IT. I was fallen in love with coding when I listened to the 1st lecture of my academic about C programming. That day changed my life. I have been working on python from January 2018.\nI am a quick learner, self disciplined, self motivated guy. \nMy hobbies are coding and learning new thing", + "Speaker Links": "https://www.sololearn.com/Profile/495149", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Deepak Puppala (~deepak12)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping~bDrKe/", + "title": "WebScraping" + }, + { + "Content URLs": "Will share the Slides post my Talk through a proper channel", + "Description": "Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. Note: In this workshop all the implementation will be done using PYTHON Session Takeaways: How to use different features of AWS to create your Serverless Application. What is Serverless Computing and how \"Functions as a Service\" is a revolutionary way to develop applications. Understand AWS Lambda Functions, the FaaS offering on Amazon Web Services. Understanding of the AWS services - Lambda, S3, EC2, CloudWatch, API Gateway, RDS, IAM How to access the AWS services using Python libraries in the Lambda Function. Hands On Cloud Native Web Applications Development using AWS Lambda and other offering. Practical examples of how you can combine multiple services and events in AWS and develop applications rapidly using AWS Lambda Functions", + "Last Updated": "18 Jun, 2018", + "Prerequisites": "Python: Basic of Python Programming Basics of Python Libraries Usages (Imports) AWS Free Tier account - https://portal.aws.amazon.com/billing/signup?redirect_url=https%3A%2F%2Faws.amazon.com%2Fregistration-confirmation#/start", + "Section": "Web development", + "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", + "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Ritu Mehra (~ritu86)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/serverless-application-development-using-aws-and-python~eEvga/", + "title": "Serverless Application Development using AWS and Python" + }, + { + "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. You can find the introduction slides here ", + "Description": "SymPy is a Python library for symbolic mathematics. It aims to be an alternative to systems such as Mathematica or Maple while keeping the code as simple as possible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.\nThe talk will highlight the following: SymPy, what it is and how it is different from others. What is symbolic computation and how SymPy achieves it. Power of SymPy: Symbolic manipulations Equation solving Calculus Linear Algebra ", + "Last Updated": "18 Jun, 2018", + "Prerequisites": "Basic mathematics, just enough to appreciate the manipulation done by the computer algebra system and Python. No prior knowledge of SymPy or other Python libraries is required", + "Section": "Data science", + "Speaker Info": "SymPy India developers will be conducting the talk: Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers module", + "Speaker Links": " Resource repository: https://git.io/sympy-pycon-india-18 SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://youtu.be/5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://youtu.be/nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://youtu.be/AqnpuGbM6-Q SymPy, SciPy 2014: https://youtu.be/Lgp442bibDM Symbolic Computing with SymPy, SciPy 2013: https://youtu.be/dAgShwIx72c", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Yathartha Joshi (~Yathartha22)", + "created_on": "18 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-sympy~dGxJe/", + "title": "Symbolic Computation with SymPy" + }, + { + "Content URLs": "Coming Soo", + "Description": "It's really hard to escape the 3D buzzword. You find it used in all sorts of places, right from the movies you watch, Games you play, 3D printing , webgl graphics in the browser and VR , AR applications. In this workshop we are going to cover the basics of 3D and do a hands on session on creating 3D Art using a professional open source application called Blender . Of course, python is a major part of blender and we will put your python skills to some good use. What is this workshop NOT about : This is not one of your boring programming workshops. We are not going to try improve your python knowledge ten folds in a matter of 2 hours. What is this workshop about : Come to this workshop if you want to be a kid again and have fun creating art in 3D using Blender and Python !!! Who am I : Hello, Sreenivas here! I am a 3D artist turned programmer. I work in the animation and VFX Industry and battle production issues with the power of python. I love art, technology and excited about combining both. I support open source by evangelizing Blender and Krita . Who are you : You are a person with an open mind, bitten by the curiosity bug and intrigued by how 3D Art is made. You have at least basic knowledge of python and ready to use your super powers to create 3D Art. Takeaway : By the end of the session\u2026 You will know a broad overview of 3D Art . Have a working knowledge of the professional open source 3D application, Blender . Get a deeper understanding of the workflow for creating 3D art. Use your python skills in the process of creating 3D Art.", + "Last Updated": "19 Jun, 2018", + "Prerequisites": " Laptop with a decent GPU (any modern laptop) A mouse with a middle click button (scroll which is clickable) Download and install Blender from https://www.blender.org/download/", + "Section": "Others", + "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", + "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "sreenivas alapati (~cg-cnu)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3d-art-using-blender-and-python~aKBxe/", + "title": "Creating 3D Art using Blender and Python" + }, + { + "Content URLs": "Coming soon", + "Description": "Do you know, your favorite superheroes in Avengers , cute characters of Kung Fu Panda and the epic wars of Baahubali were brought to screen with the help of python ? If you are into gaming , you need to thank python for the characters you have played and the world you have explored. Even the next generation technologies like AR and VR use python to deliver their magic to you in new formats. It won't be a overstatement if we say python is the backbone of the animation Industry In this talk we go behind the scenes and see how our favorite programming language is used in the animation industry, why it plays a huge role and the kind of applications built with it", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "A bit of curiosity and interest in learning about usage of python in various industries, usually less represented in the python community", + "Section": "Others", + "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", + "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "sreenivas alapati (~cg-cnu)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/amazing-world-of-animation-powered-by-python~dLDrd/", + "title": "Amazing world of animation - powered by python" + }, + { + "Content URLs": "https://docs.openstack.org/infra/jenkins-job-builder", + "Description": "Jenkins job builder is an openstack project used for automation and reusing of templates in yaml and json to make jobs and subscribe them to Jenkins. People who like to save time on tedious details can use this open source software and live there life a little better", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "Jenkins( a little bit )\nPython\nPip\nRelated libraries like PyYAML, Jinja etc", + "Section": "Developer tools and Automation", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Himanshu Chhabra (~himanshu87)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jenkins-job-builder-automating-jobs~aMgGd/", + "title": "Jenkins job builder - automating jobs" + }, + { + "Description": "Abstract: Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. The Big Question: \"Is everything Perfect in AWS Lambda?\" .... Well it depends on how you use it and this is what I will cover in my Talk. Note: This Talk will have some code references using PYTHON Outline: What will you learn from this session/talk: What are Lambda Functions . What are the different features of Lambda Functions. The famous Lambda Timeout . The Deployment and Resource Limits . The Cold Start issue and its workarounds. The Cost Factor Why do you need to know this: Helps develop decision making in the project design architecture The Case Study: Case Study in which you should/should not use Lambda Functions. Real Life project experience: The hidden learning with an on job project on the limitations to Lambda Function. Q&A ", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "Python: Basics of Serverless Computing Basic of Python Programming Basics of Python Libraries Usages (Imports)", + "Section": "Others", + "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", + "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Ritu Mehra (~ritu86)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-lambda-with-python-dos-and-donts~dNjvd/", + "title": "AWS Lambda with Python : Do's and Dont's" + }, + { + "Description": "With examples build the concept of creating a language model using text data", + "Last Updated": "19 Jun, 2018", + "Section": "Data science", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "divya chowdhary (~divya69)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~aOkra/", + "title": "Language Model (Text Analysis) using Python from scratch" + }, + { + "Content URLs": "Will be updated soon", + "Description": "Note: This talk is co-presented by Koushik (me) and Shubham Rao Talk Summary: Bitcoin has become so mainstream these days. It unveiled the importance of decentralization. But how does Bitcoin work? It\u2019s because of its core technology called Blockchain. After the Internet, Blockchain technology is regarded as the next big revolution. This talk gives a hands-on demonstration of how Blockchain technology works by building a toy version from scratch. Outcomes: After this talk the audience should be able to understand the basic working principles of bitcoin. They will be able to leverage their knowledge as a starting point of open-source contributions to projects like Ethereum. This demonstration will consider three important features of Blockchain Technology. All these features are essential to blockchain technology and we will be building a minimal version in Python. Agenda: 0 - 5 mins:\n Blockchains are secure because they use SHA256 or SHA512 algorithm for cryptography. I will describe the logic behind these hashing algorithms and give some computational facts about them. 5 - 10 mins: \n I will use the Python library called \u2018hashlib\u2019 to implement the SHA256 algorithm in Python. This makes us to convert data into SHA256 hashes. 10 - 15 mins:\n The SHA256 algorithm is used to convert all the transactions and their details into a single hash. Once the everything is converted into a hash, this hash must be stored for future usage. After a new transaction is approved, this new transaction and its details are again converted into a new hash along with the previous hash. I will demonstrate the process of storing the hash and using it again for a new transaction. 15 - 20 mins:\n Here I will explain a basic working principle of blockchains and how linking the previous transactions with the new one helps in the their security. The hashes stored are called blocks and the process of liking the previous hash the new hash makes a chain like connection thus forming a Hyperledger. 20 - 25 mins:\n Later in the process of mining will be explained using the variable quantity called Nonce. This explains why bitcoin miners need high computation power to do Proof-of-Work. \nI will also cover a variety of essential terms and concepts through the course of the talk which haven\u2019t been detailed in the agenda. Also, I will use python module called 'TkInter' to build a basic GUI for our blockchain. Last 5 mins:\n Questions and further reading + code sharin", + "Last Updated": "19 Jun, 2018", + "Prerequisites": "Love for Python and acquaintance with its libraries", + "Section": "Core python and Standard library", + "Speaker Info": "Hi, we are Koushik and Shubham , two Computer Science sophomores with research interests in Decentralisation and Blockchains, also occasionally working in Artificial Intelligence and Machine Learning. As members of Next Tech Lab, QS Reimagine Award-winning, student-run lab from our University, we work in Satoshi Lab, which focuses on Blockchains. We regularly participate and give talks in paper-reading groups and meetups like PyData", + "Speaker Links": "Visit my profile on LinkedI", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "KOUSHIK BHARGAV M M Srinivas (~koushik_bhargav_m)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchains-from-scratch~dPl4d/", + "title": "Understanding blockchains from scratch" + }, + { + "Content URLs": "Github repository links will be updated soon", + "Description": "In this talk, I am going to talk about advanced concepts of Python related to Caching. A cache can be easily understood as a saved answer to a question. Caching can speed up an application if a computationally complex question is asked frequently. Instead of the computing the answer over and over, we can use the previously cached answer. Caching is an important component while scaling applications which are to be used by many users. It solves various problems related to cost and latency. Usually it takes more time to retrieve data from DB rather than cache. Using a cache to avoid recomputing data or accessing a slow database provides us with a great performance boost. I will describe in depth the different methods of Caching, their pros and cons. This talk will help developers focus on their code before scaling their applications. It will provide immense performance improvements with this simple concept. Outcomes: The novice audience will be able to understand basic Caching Mechanisms. They will be able to utiilize their knowledge which will serve pivotal while scaling applications Contents to be covered in talk: Local Caching: What is it, how to do it, example, built-in Python libraries: (using cachetools ), advantages, dis-advantages Memoization: What is it, pseudo-code algorithm, implementation using example, built-in Python libraries: (using lru_cache ), advantages, dis-advantages Distributed Caching: What is it, techniques: (using memcached , using pymemcache ) Agenda: Initial 10 minutes: Introduction to Caching and its various techniques. 10 - 20 minutes: Examples and code walk through for various techniques. 20 - 25 minutes: Comparative analysis of how caching is better than non-scaled applications. 25 - 30 minutes: Q&A session", + "Last Updated": "19 Jun, 2018", + "Prerequisites": " Basics of Python", + "Section": "Core python and Standard library", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "19 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-caching-in-python~aQm9a/", + "title": "Understanding Caching in Python" + }, + { + "Content URLs": "Docker Docker Swarm https://docs.docker.com/engine/api/v1.37/ https://www.elastic.co/products/elasticsearch https://www.elastic.co/products/kibana https://www.elastic.co/products/beats https://jmeter.apache.org", + "Description": "Summary: Knowing how Enterprise Server perform under load (% CPU, % Memory, Network, % Disk time) is extremely valuable and critical. This may limit the server performance and lead to enhancements or fixing before you go for production. Now any Load testing tools available comes with below problems Preparing the environment / infrastructure (installing various software dependencies) on multiple host systems to perform load test at times very tedious task. It requires maintenance and manual interventions to scale up and scale down load test. You have to write your own test codes, need some development effort. Most of the stress tools comes with their own format of reporting, very difficult to customize if it\u2019s really needed. Also it\u2019s difficult to view, analyze and compare test results real time across systems. Here in today\u2019s talk we are going to demonstrate how JAAS (JMeter As A Service) can be a one stop solution for all these problems. And how python is playing a crucial role in Delivering JAAS Solution. Tech Stack: Tech Stack behind JAAS Python: Python is at the core of JAAS. It is responsible for communicating across all individual components using Rest API. Python is also responsible for slicing and dicing the data for processing. Docker: For auto deploying of JMeter Apps, we use Docker containers (pre-packaged with all dependencies). This reduces manual interventions for maintaining the Load test environment / infrastructure. ELKB Stack: ELKB is the backend for JAAS. We store all logs, beats, JMeter results in Elastic Search. Logstash for data processing pipeline and Kibana for visualization. JMeter : JMeter is the load test tool for generating load. It\u2019s an open source software, Ease of Use, Platform independent and Robust Reporting. JAAS comes with a single window User interface where user will provide the Load test details like: System details Load Generation type Number of concurrent users Number of threads Using RESTFul API implemented in Python this info (including dynamic Test plan .jmx file for JMeter) will be stored in ES Backend and a new Docker service will be created. We use Docker container (prepackaged with all dependencies as a single app) for generating load on System. Usually a Docker container ships JMeter software and Beats (Data shippers for Elasticsearch ). Every time for a new load test request, we deploy a new instance of our app on the Docker Swarm cluster (a new Docker container).We maintain Docker swarm cluster (group of machines that are running Docker) for scalability and load balancing while performing load test. Each of this machines in cluster (both manager and worker) will communicate with each other and execute Docker command using Python Rest call only. Swarm managers can use several strategies to run Docker containers, such as \u201cemptiest node\u201d -- which fills the least utilized machines with containers. Or \u201cglobal\u201d, which ensures that each machine gets exactly one instance of the specified container. Swarm managers authorize workers to execute\\run the Docker container. Each Docker service will have specific input from user (stored in ES backend) for generating particular type of load on specific host system. Similarly user can scale up or scale down the load (number of users or threads) using the same UI form on the fly. This is the biggest advantage of JAAS over any other Load test tool available. In normal scenario there is no option but stop and start the tool, if you want to scale up or down. \nEach Docker container with its JMeter instance will keep generating the Load on specific host system and Beats will be responsible for pushing back the data/results into Elasticsearch. This entire implementation of data reading and writing to Elasticsearch is happening through Python. Once the load test specific data pushed to Elasticsearch , kibana will prepare the Visualization for you. This is real time, aggregated (in case of concurrent users are generating the Load) and available in a single dashboard which makes it very easy to compare and analyze", + "Last Updated": "20 Jun, 2018", + "Prerequisites": "Familiarity to Python, Docker, JMeter and Elastic Stack.\nPython and Modules(XML, JSON and Request) experience", + "Section": "Developer tools and Automation", + "Speaker Info": "Vishnu Murty K A Senior Principal Engineer at DellEMC Infrastructure Solutions Group, is an MS (Software systems) with a total experience of 13 years in Leading Product Qualification and Automation Development efforts. The domains Vishnu has worked on include Storage and System Management Software. Responsible of Delivering Zeno - Continues Test Automation framework, JAAS, ICEMAN and Automation Tools. Presented automation papers in Pycon (Python developer forum)\u00a0and STeP-IN Forum. Dibyendu Dutta A professional with over 7 years of experience in Core Java, PHP, Node.js, Python.\nHe is currently working as a Senior Engineer in Dell R&D Bangalore. He has designed, developed web applications for various MNCs across multiple domains.\nHe loves to be keep updated with all latest tech trends , cutting edge technologies", + "Speaker Links": "Vishnu Murty K https://www.linkedin.com/in/vishnu-murty/ Dibyendu Dutta https://www.linkedin.com/in/dibyendu-dutta-3b65581b", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Vishnu Murty (~vishnu79)", + "created_on": "20 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/distributed-load-testing-using-python-jmeter-and-docker~dRnEd/", + "title": "Distributed Load Testing using Python, Jmeter and Docker" + }, + { + "Content URLs": "Will be updated soon", + "Description": "Talk Summary :- Recently, there is a boom in concept of face recognition system with the introduction of Face ID by Apple in their iPhone X mobile phones. This was also incorporated by OnePlus for their mobile phones too. The most notable use of this technology is at Baidu, an internet company, are using face recognition instead of ID cards to allow their employees to enter their offices. Another place where this technology is prominently seen is in auto photo and video tagging feature of Facebook. In this talk we will build a Facial Recognition program using python library \u201cface_recognition\u201d and then we will dive deep in the behind the scenes action of this library and will try to build a One Shot Learning face recognition model using PyTorch. We will be implementing a Siamese neural network on AT&T Laboratories Cambridge dataset. We will also cover the basics of this neural network, triple loss function and and will discuss the reason for choosing this architecture. I will explain how the network models a relation between two images and relates them. Outcome of this Talk :- Attendees will be able to possess the power to implement state of the art Facial Recognition program in a few minutes. They will also get to know how facial recognition works when we have very small dataset. They will be able to make a state of the art One Shot Learning face recognition based on Siamese Network (the working force of face_recognition and implementation of Google\u2019s FaceNet). Agenda :- Introduction to Face Recognition [2 mins] Introduction of python library \u201cface_recognition\u201d [1 min] Building a face recognition program using \u201cface_recognition\u201d library\n (possible live demo of the output) [6 min] How \u201cface_recognition\u201d encodes faces [2 min] Introduction of Triplet Loss and Siamese Network and reason to choose one shot learning (which is used to\n encode faces) [5 min] Implementation of Siamese Network using PyTorch on AT&T Laboratories\n Cambridge dataset and its results [10 min] Q&A Session [3 min]", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Basic Knowledge of Machine Learning and Neural Networks Love for Pytho", + "Section": "Data science", + "Speaker Info": "Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", + "Speaker Links": "Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Saurabh Ghanekar (~saurabh29)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-state-of-the-art-facial-recognition~eVrXe/", + "title": "Understanding State of the Art Facial Recognition" + }, + { + "Description": "for students,\nunderstanding data analysis with pandas, using ipython shell or terminal and jupyter notebooks", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "understanding of python scripts", + "Section": "Data science", + "Speaker Info": "I'm a 3rd year B.tech(information science) student from Bangalore, Karnataka", + "Speaker Links": "https://github.com/pandyamaru", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Marut Pandya (~pandyamarut)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-with-pandas~bWvxa/", + "title": "Data analysis with Pandas" + }, + { + "Content URLs": "Speaker will focus on when and how to use design patterns, rather than what are the design patterns available. Github repository for the talk", + "Description": "Having less time to design software and solving the design problems correctly, to create robust , modular and highly maintainable code is current challenge.\nMight be, you are aware of some of the design patterns but it will never solve your problems until you have deep understanding on the problem and right place to use design pattern. If you think, you need to design a very unique architecture, then may be you are missing powerful available design pattern that can provide you generic solution template. Let's learn ( and become expert), to speed up development process; guessing issues that can come up later development stages and selecting the right design pattern in the right stage of the software development in Python", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Coders and programmers who want to learn about software design and architecture", + "Section": "Others", + "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", + "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Shekhar Prasad Rajak (~Shekharrajak)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/i-would-have-known-this-software-design-techniques-before~eXwgd/", + "title": "I would have known, this software design techniques before.." + }, + { + "Description": "Data proliferation is putting pressures on business leaders to become data-driven. Although, leaders have to rely on data analysts to run those queries and get insights out from data warehouses. Its a common principle-agent problem wherein data analysts only ask questions from data which they are directed to ask, but its never a one-way street. One has to flirt with data for a long time to get to know it and leaders get stuck in the loop of data analyst direction as leaders are not equipped with or don't have time to write SQL queries. This calls for a natural language query wherein a business leader can ask a question in simple plain English and data is spitting out either in a table or graph. This session is guided towards how Innovaccer has solved this problem and provides an architecture, knowledge base building, and natural language processing guidance to build one on your own. The session will also emphasize on the fact that accuracy of such a software will be very poor if it is industry agnostic as SalesForce and ThoughtSpot have tried in the past. Thus, one has to tame it to their own business context or vertical", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Basics knowledge on natural language processing, not even how to code it, but what are its basic components. https://www.nltk.org", + "Section": "Data science", + "Speaker Info": "Kanav Hasija is Co-Founder and Chief Product Officer at Innovaccer. He has developed a healthcare data platform with his team which helps connect to various healthcare IT systems to get a longitudinal view of the patient record and turn it into analytical insights on risk, cost, and utilization behaviour of patient to act on them and treat them before they get sick to reduce the cost of healthcare. The platform today has more than 10 million lives on the platform and an estimated $1 Billion has been saved till date in US healthcare costs while keeping people healthy with a quality of care bump of 15%. He is a coder and mathematics enthusiast since the age of 10, completed his bachelor in engineering from IIT Kharagpur and pursued higher studies in Intellectual Property Law from UNH Law in the US. He is recipient of various awards like Samsung-Stanford Patent Prize, Honorable Mention for Excellence in Technology, Best Graduate Student Award, and is also an author in a few publications like IEEE. Harshil Rastogi is a software development engineer at Innovaccer. He has worked on various enterprise-grade software components in the fields of data management, data transformation, and natural language processing", + "Speaker Links": "https://www.linkedin.com/in/kanavhasija/ https://www.linkedin.com/in/harshil-rastogi-3a754b65", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Kanav Hasija (~kanav)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bringing-analytics-in-hands-of-leaders-natural-language-query-in-python~bYx2a/", + "title": "Bringing analytics in hands of leaders: Natural Language Query in Python" + }, + { + "Content URLs": "Slides Celery Documentatio", + "Description": "Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. Although it is most popular in the web development ecosystem, it has a wide area of usage from system management to IoT devices. With Celery, transforming a function into a task is quite easy and can add great performance & usability to the applications that we build. This talk aims to give attendants a general overview of Celery and its uses. We will walk through the core Celery architecture by introducing key components with the help of various real-world examples. This will also lead to an understanding of the task queue systems in general. Attendants will also gain knowledge about Celerybeat; a tool that focuses on scheduling tasks", + "Last Updated": "21 Jun, 2018", + "Prerequisites": " Basic knowledge of Python. Ready to learn", + "Section": "Others", + "Speaker Info": "Software Engineer at Essentia SoftSer", + "Speaker Links": "Linkedin Githu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "abhyudaypratap@outlook.com", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-celery~eZy5d/", + "title": "Understanding Celery" + }, + { + "Content URLs": "https://github.com/someshchaturvedi/customizable-django-profiler Will be updating slides soon", + "Description": "Django, as we all know, is an excellent framework for building high stable, scalable, extensible web apps. Django framework operates around middlewares. Do we really understand how a middleware works? What happens when the request comes in and response goes out? Which middleware is used for what purposes? Why is the order of middleware stack important? How can we implement a custom middleware? Benefits and complications of implementing custom middlewares My talk will cover all the above questions along with a live demo of a profiling middleware ( customizable-django-profiler ) which is used to track down the function calls associated with an API call taking more time for execution. Contents of the talk: Introduction : Introduction to middleware. Middleware architecture : I will talk about the middleware architectural design. It\u2019s basics and various use cases Implementation of middleware in Django : Explain how the request-response cycle works along with targeting above mentioned questions on the go. Live demo : I will demo the development of a simple custom middleware which can be used for profiling requests. Conclusion : Possible use cases for Django middlewares. Q & A session : Questions and answers session. In the end, the audience will have an understanding of Django middleware stack, middleware architecture, request-response cycle in Django and will be able to develop their own middleware for Django from scratch", + "Last Updated": "21 Jun, 2018", + "Prerequisites": "Basics of Python and Djang", + "Section": "Web development", + "Speaker Info": "I am recently graduated from IIT Roorkee. I have been working on web applications (especially Django for more than 3 years now). Selected for Google Summer of Code this year and working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API . My areas of interest are Web Applications, Artificial Intelligence and Computational Biology", + "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "hulksmash (~someshchaturvedi)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-django-middleware-stack-with-a-live-demo~e1qme/", + "title": "Understanding Django middleware stack with a live demo" + }, + { + "Content URLs": "Git Hub Repository : click here Demo: click her", + "Description": "The workshop will be escalating from a very beginner level and so I only require you to know the basics of python and if possible a glance of the OpenCV library. The workshop will be proceeding accordingly : Basics of Image processing. Image classification using Deep Learning ( CNN ). Deploying your own Emotion recognizer. ", + "Last Updated": "21 Jun, 2018", + "Prerequisites": " Basics of Python Please download and install the following libraries in beforehand : Pytorch OpenCV Fastai numpy matplotlib dlib imutilis We will be using all of the mentioned libraries to make the goings of the workshop easy to understand and implement. Additional Files : Please download from her", + "Section": "Data science", + "Speaker Info": "I am shaaran and my main aim is to take technology to everyone and spread my knowledge as far as I can, in a journey to fulfill my dreams I have went to many institutions and have conducted workshops and talks in Robotics and AI, I am currently a second-year student at VIT University and also a part of many organizations like Google Developers Group, RoboVITics and more , I have interned at Toshiba recently and have made a new AHU control system using IOT and AI", + "Speaker Links": "Github: click here Linkedin: click her", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "shaaran Lakshminarayanan (~devshaaran)", + "created_on": "21 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-your-own-emotion-recognizer-from-scratch~b2rzb/", + "title": "Building your own Emotion recognizer from Scratch !" + }, + { + "Content URLs": "A similar version of this talk was recently delivered at Pycon APAC2018 (Singapore). Video An attendee's review", + "Description": "Offensive / abusive content is a major issue for social-media and digital interaction platforms. In some jurisdictions (Eg: Europe), platform providers are required by law to remove such content within 24 hours of posting or risk hefty fines (upto \u20ac50M in Germany). In order to meet the governance mandate, we need to have systems in place that can automatically detect abusive content at scale. This talk is based on my practical experience of building an automated solution to solve this problem. This talk begins with discussing some of the approaches currently being employed for offensive content detection at scale: word filtering, rule-based systems and actual human annotation. The former two are restricted by the following: Offensive content is context specific. A given word (f*ck) can be used in both positive (that\u2019s f*cking awesome) and negative (that\u2019s f*cking terrible) contexts. Robustness to spelling variations (The word \u2018shit\u2019 can be spelt as \u2018sh*t\u2019, \u2018sh!t\u2019, etc) Failure to detect content that is offensive in idea but uses non-offensive words. (Eg: your mom is a fat cow, X people are inferior, etc) Manual human annotation is notoriously hard and expensive to scale. The talk presents a Deep neural network based approach to overcome the previously mentioned limitations. It introduces and discusses the building blocks of model architecture (deep convolutional networks, word embeddings, etc). The second half of the talk focuses on implementing the model to solve the problem at scale as a RESTful micro-service using python, Django, Tensorflow and Docker. This architecture can also be used to implement other text classification systems (eg: sentiment detection, user intent detection systems, topic-of-discussion classifiers, etc.), making the talk relevant for a wider user base. Attendees will: Gain insights into building deep learning based text-classification systems that can scale Learn the nitty gritties of the offensive content detection and text classification Learn about the basic concepts of Deep Learning and NLP (convolutional neural nets, multi-layer perceptron, word embeddings, etc.) Understand the scientific and software challenges involved in text classification and learn to overcome them Be able to apply the learnings from here to other text classification problems as well", + "Last Updated": "22 Jun, 2018", + "Prerequisites": " Elementary knowledge of Python Basic understanding of machine learning (nice to have, not mandatory) An open mind ;)", + "Section": "Data science", + "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. He is currently employed as a Machine Learning Engineer. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", + "Speaker Links": "https://www.linkedin.com/in/alizishaan-khatri-32a2063", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Alizishaan Khatri (~alizishaan)", + "created_on": "22 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/detecting-offensive-messages-using-deep-learning-a-micro-service-based-approach~e30Ra/", + "title": "Detecting offensive messages using Deep Learning: A micro-service based approach" + }, + { + "Content URLs": " Apache Beam : https://beam.apache.org/ Apache Beam Python SDK : https://beam.apache.org/documentation/sdks/pydoc/2.4.0", + "Description": "Data together with 3Vs characteristic, volume, variety and velocity is labelled as Big Data. Big Data and parallel processing have been hot topics since Google\u2019s paper on MapReduce and till today the era of different runners like Apache Spark, Google Cloud Dataflow etc. Apache Beam is a unified big data processing paradigm which enables the user to run batch and streaming data processing jobs on multiple execution engines like Apache Spark, Apache Flink, Google Cloud Dataflow etc. *Objective of the talk* : Overview of Apache Beam Python SDK Core SDK constructs like Pipeline , PTransform , PCollection etc. Creating custom DoFns and composite Transforms Creating a Pipeline with customizable options Running a pipeline on different runners like DirectRunner , DataflowRunner etc Unit testing a Pipeline with asserts Demo: StreamingWordCount example using Google Cloud Dataflow Q&A", + "Last Updated": "22 Jun, 2018", + "Prerequisites": " A little knowledge about Python 2.7 Enthusiasm for Parallel Data Processing Motivation to play with lots of Data", + "Section": "Others", + "Speaker Info": "I am Mukul Arora, working as a Software Engineer in Schlumberger India Technology Centre. I graduated from Delhi Technology University in May 2017. I am a Data Science and Big Data practitioner and have been highly involved in solving Computer Vision and Medical Imaging problems using Deep Learning Techniques. Currently, I am exploring efficient ways to solve Big Data problems on Cloud.\nI am an avid cricket fan and love to write poems", + "Speaker Links": "LinkedIn : https://www.linkedin.com/in/mukularoradce/ Github : https://github.com/codemukul95 YourQuote : https://www.yourquote.in/mukul-arora-ffds/quotes", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "mukul arora (~mukul11)", + "created_on": "22 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unified-and-portable-parallel-data-processing-using-apache-beam~b4Dxb/", + "title": "Unified and Portable Parallel Data Processing using Apache Beam" + }, + { + "Content URLs": "The code is in this repo :\nhttps://github.com/KaustabhGanguly/Smile-Detector :", + "Description": "In this era of deep learning and machine learning , the beginners may get lost sometimes , as there is a steep learning curve involved with the process .\nWhen I was starting out on machine learning , I always wanted to get my hands dirty in the advanced stuffs but It was hard for me and there was no guidance .\nSo , in this talk and coding session I will guide you through how you can build your own facial recognition system and implement a smile detection very quickly and easily with the power of openCV and python . It will take 10 mins and any beginner with basic knowledge of python can grasp the concepts easily .\nI will not use convNet or anything ,but a model called HaarCascades . It's an old mathematical model which was/is mainly used where deep learning is not an option . I will guide you through the basics and tell you some quick things and facts and we will enjoy a lot . See you on pyCon 2018 ! kindly upvote if you want some quality 10 mins learning something new ", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "Basic Python knowledg", + "Section": "Data science", + "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India .\nI'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 .\nI'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", + "Speaker Links": "Follow me on github :\ngithub.com/kaustabhganguly\nConnect with me on linkedin :\nlinkedin.com/in/kaustab", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kaustabh Ganguly (~KaustabhGanguly)", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quick-and-easy-implementation-of-smile-detector-on-your-webcam-using-python-and-opencv-from-scratch-without-any-neural-network-and-for-beginners~e5E8e/", + "title": "Quick and easy implementation of Smile Detector on your Webcam using python and openCV from Scratch without any Neural Network and for beginners ." + }, + { + "Content URLs": "A sample code can be found here :\nhttps://github.com/KaustabhGanguly/Recurrent-Neural-Networks-to-predict-Google-Stock-Pric", + "Description": "I will show you how to predict google stock price with the help of Deep Learning and Data Science .\nThe predictions are not realistic as stock prices are very stochastic in nature and it's not possible till now to accurately predict it .\nAs I'll only have 30 mins to talk , I can't train the data and show you as it'll take several hours for the model to train on google collab . So , I will show you : Basics of Recurrent Neural Networks and LSTM Basics of pytorch Coding line by line with describing every words Then starting to train the model and prematurely closing it and move forward to show you the results that I'll bring with me after training .", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "You should have basic pyTorch understanding but I'll guide you anyways through the basics .\nBasic understanding of LSTM or RNN is preferred but not required ", + "Section": "Data science", + "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India . I'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 . I'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", + "Speaker Links": "Follow me on github : github.com/kaustabhganguly Connect with me on linkedin : linkedin.com/in/kaustab", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Kaustabh Ganguly (~KaustabhGanguly)", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-stock-price-time-series-prediction-with-rnnlstm-using-pytorch-from-scratch~b67Rd/", + "title": "Google Stock Price Time Series Prediction with RNN(LSTM) using pytorch from Scratch" + }, + { + "Content URLs": "Will be updated soon", + "Description": "Dash is a Python framework for building analytical web applications, built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs to your analytical Python code. The workshop will include building interactive dashboard with Dash framework. How to visualise the data purely in python will be the key take away", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "Python 3 Pip3", + "Section": "Web development", + "Speaker Info": "I am software engineer working at Juxt Smartmandate, who believes in creating products using open source technology", + "Speaker Links": "https://github.com/kapoorabhish https://www.linkedin.com/in/abhishek-kapoor-4b7b9295", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "kapoorabhish", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-interactive-dashboard-using-plotly-dash~e771e/", + "title": "Building interactive dashboard using Plotly Dash." + }, + { + "Description": "Automation is something we all desire, may it be the twitter feed of a celebrity, or perhaps the latest price of bitcoin. For students, it can range from tracking assignment deadlines or message updates. For developers, it can be the tracking of an important issue or auto merging of pull requests. For management, deadlines for a work assignment or a due presentation. With Python, everything listed above is possible. The talk will feature how to start automating the small things that can prove highly productive. We will use simple libraries first, and this will be followed by using fully headless browsers like selenium and understanding the concepts of web crawling. Integration of API services like Google Calendar and Google keep, to sync all the data collected will be demonstrated. Finally, we will deep dive into an interesting open-source project I made, and how I have automated most of my college work.\nA simple breakdown of the talk is described as follows. REST API Introduction ( Totally 3 minutes ) Libraries we will use ( Totally 6 minutes ) The Requests library The BeautifulSoup library Web Scraping example for IMDb ( Totally 4 minutes ) Code and Logic walkthrough Running Example Automation Example ( Totally 10 minutes ) What we will be doing The Code Google API linking Cron/Scheduling The base logic Running Example Selenium ( Totally 5 minutes ) Introduction Example Conclusion and My work ( Totally 2 minutes )", + "Last Updated": "23 Jun, 2018", + "Prerequisites": "Basic understanding of REST APIs and Frameworks, and Beginner-Intermediate Level of Python Programmin", + "Section": "Developer tools and Automation", + "Speaker Info": "CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms.\nTechnical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", + "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Priyansh Jain (~Presto412)", + "created_on": "23 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-your-life-with-python~b873a/", + "title": "Automating your life with Python" + }, + { + "Content URLs": "https://docs.google.com/presentation/d/1d061xK27vMdJ8Xjta8K3kuvA4-dbX8MrywzXQmZ1Ln4/edit?usp=sharin", + "Description": "Have you ever been amazed how efficiently and effectively tech giants are processing their data ? Do you want to build an analytics system that is capable of processing billions of records in a day ? For those of you who are wondering how to build a scalable, low latency system for running arbitrary SQL queries in Python, this talk is for you! This system is distinguished by being schema-independent, and processing queries with minimal latency I will describe how to architect this system using the powerful Lambda Architecture (an often used design pattern in big data) and Apache Kafka, how to process and format the raw schema-independent data, and introduce different online analytical processing (OLAP) systems and their respective tradeoffs. The end product will be an analytics engine capable of running arbitrary queries on billions of records. Finally, I will also discuss some exciting extensions of this pipeline, including applying machine learning algorithms and adding a monitoring system. The talks ends with benchmarks of queries made on billions of records followed by a Q&A session. This talk is intended for folks belonging to any of these fields: Involved in the process of revamping their data warehousing systems\n for arbitrary queries with minimal latency Those who want to build their own analytics layer from scratch Analytics enthusiasts", + "Last Updated": "24 Jun, 2018", + "Prerequisites": " General Python knowledge Basic SQL queries Great Enthusiasm Little Familiarity with Databases", + "Section": "Data science", + "Speaker Info": "Shaik Asifullah is currently working as Senior Data Engineer at MoEngage, open source developer who previously worked at WalmartLabs and graduated from BITS Pilani, Goa. He got interested in learning more about Big Data technologies after he learnt about Columnar databases. He was also associated with faculty of University of Zurich & ETH Zurich in building a Sentiment Analyser and worked on predicting results of US 2016 Presidential elections with the model. His recent open source contribution is regarding building a distributed Python environment for building, simulating, and analysing models of biochemical networks, including gene regulatory networks and metabolic networks. He is also a great admirer of Freud Psychoanalysis & Andre Breton Surrealism", + "Speaker Links": "https://www.linkedin.com/in/shaikasifullah https://github.com/ShaikAsifullah/distributed-telluriu", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Shaik Asifullah (~shaik2)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/processing-billions-of-records-per-day-with-python~e97Db/", + "title": "Processing Billions of Records Per day with Python" + }, + { + "Content URLs": "Will come soo", + "Description": "Blockchain Technology is the talk of the town. Almost all articles published have some relation to Blockchain concepts.\nWhile Public Networks usually pertain to Cryptocurrency, Private networks pertain to business-level implementations. In order to develop with this technology as our base, it is important to understand the key features, as well as make implementations using the existing skillset, which happens to be the Python Programming Language. The talk will feature Complete in-depth explanation of Blockchain technology, and the working of Bitcoin as an example. Developing your personal Cryptocurrency with Python Introduction to Hyperledger Sawtooth, and understanding how and why to use Python with it. Best practices to consider in mind while developing for a blockchain. By the end of the talk, you will be able to Explain the concepts of Cryptocurrency and Blockchain technically. Understand Python's role in one of the most popular frameworks created by Intel, and implement your own ideas with the same.", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "General Pytho", + "Section": "Others", + "Speaker Info": "Hi, I'm Priyansh! Here's a quick bio. CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms. Technical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", + "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Priyansh Jain (~Presto412)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-with-python~e0yLa/", + "title": "Blockchain with Python!" + }, + { + "Content URLs": "Will be updated soon", + "Description": "Your machine learning models might be intelligent enough to make predictions but may lack the wisdom to prevent bias. They may be as vulnerable as a child getting influenced by inappropriate sources encouraging racism, sexism or any unintended prejudice. Models learn exactly what they are taught. The more biased your data is, the more biased is your model. For instance, a text model by Google says how \u201cEngineer is to a Man\u201d is the same as \u201cHousewife to a Woman\u201d. This shows how incidental data can lead to unintended bias. Machines are given the power to judge so there is a need for us to ensure we prevent biased/unfair judgments. In this talk, we are going to discuss how to arrive at \"Engineer is the same for both man and woman\" [debiasing gender] by following the steps below : Intro to Machine Learning bias and word vectors? [10 min] Analyse bias from word vectors and it's problems [10 min] Debiasing algorithm [10 - 15 min] Questions [5-10 min] One Famous example of bias:", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "Knowledge of python Knowledge of building machine learning models / Interest in building on", + "Section": "Others", + "Speaker Info": "I am a software developer, speaker, opensource contributor and a wannabe developer evangelist. I love everything python and NLP(Natural Language Processing) research. I have been volunteering with various local startup and tech communities to promote entrepreneurship and technology. I work at mroads and help them develop better a.i", + "Speaker Links": "Links: Linkedin: https://www.linkedin.com/in/poornagurram/ Github: https://github.com/poornagurram StackOverflow: https://stackoverflow.com/users/5443381/poorna-prudhv", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "G POORNA PRUDHVI (~poornagurram)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-fair-machine-learning-systems~egVkd/", + "title": "Building fair machine learning systems" + }, + { + "Content URLs": "Errbot's Website: http://errbot.io Errbot's GitHub Repository: https://github.com/errbotio/errbot corobo's GitHub Repository: https://github.com/coala/corobo The slides will be shared to the audience as a GitHub repo after the talk", + "Description": "Abstract The aim of this talk is to introduce you to Errbot, which is a chatbot that can be used to automate software development and operation tasks to facilitate faster development of code. Errbot is a chat bot which connects to your favorite chat service(Gitter, Slack, Telegram, Zulip, IRC, etc) and brings your tools into the conversation. It provides you with a rich and user friendly API, through which you can write your own plugins so you can make it do whatever you want: retrieving some information online, trigger a tool via an API, troll a chat room member, etc. The talk will include: Introduction to DevOps and ChatOps What is Errbot Guide to setting up you own bot Writing your first plugin Fun with the bot Automating GitHub/GitLab tasks right from the chat room - Introduction to corobo", + "Last Updated": "24 Jun, 2018", + "Prerequisites": " Basic knowledge of Python and APIs Will to learn", + "Section": "Developer tools and Automation", + "Speaker Info": "Nitanshu Vashistha is a 3rd Year Engineering Undergraduate in India studying Information Technology. He started learning how to code in his first year of engineering but little did he know that he was just playing with the syntax, which he realized in his second year and his journey as a developer began. His first working application was in Python and that got him interested to develop more using Python. Nitanshu is a Python developer and an open source enthusiast . He has mentored Google Code-In 2017 and is currently a Google Summer of Code 2018 student working on a project based on Errbot for coala . He likes writing about himself as third-person :", + "Speaker Links": "GitHub: https://www.github.com/nvzard LinkedIn: https://www.linkedin.com/in/nitanshu Blog: https://medium.com/@nitanshu.vzar", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Nitanshu (~nvzard)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-automate-development-tasks-an-introduction-to-errbot~ejVve/", + "title": "How to automate development tasks? - An Introduction to Errbot" + }, + { + "Content URLs": "Content will be updated soon", + "Description": "You all would have often faced the issue of not being able to recognize handwriting, either it is a Doctor's prescription or sometimes, even your friend's assignment. This problem might have caused some harm, maybe due to the delay in submitting the assignment or seeking chemists' that can recognize that particular handwriting.\nTherefore, in this talk, we will be focusing on how Python and Data Science can be used to recognize handwritten digits and character which will ease out the pain of recognizing haphazard writings. Topics to be covered: What is Handwritten Digit and Character Recognition? Why we need it and uses of it? How Python can help in achieving this? How NLP and Neural networks can be used to increase accuracy? Future Scope", + "Last Updated": "24 Jun, 2018", + "Prerequisites": " Basics of Python Basics of Data Science", + "Section": "Data science", + "Speaker Info": "I'm Prashant Pandey. I've deep interest in Data Science, especially in Python. I've been working in the domain of Data Science since one year now, and have completed several projects. Presently, I'm working on Handwritten Digit and Character Recognition", + "Speaker Links": "https://github.com/Prashantpandey2398", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Prashantpandey2398", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handwritten-digit-and-character-recognition-using-python~bkV6a/", + "title": "Handwritten Digit and Character Recognition using Python" + }, + { + "Description": "A framework which will give a drag and drop web development option using Django as the backend", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "Python and basics of Djang", + "Section": "Web development", + "Speaker Info": "Sanket Sarkar [ Microsoft Technology Associate {Introduction to Python Programming}]\nA final Year Student of B.Tech", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Sanket Sarkar (~sanket78)", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/drag-and-drop-framework-for-django~elVMb/", + "title": "Drag and Drop Framework for DJANGO" + }, + { + "Content URLs": "Will be updated soon", + "Description": "Get to know Flask and how to create beautiful REST APIs in no time. Fall in love with Flask and learn the best practices for building APis in a hurry. Flask is a lightweight micro-framework for Python. Its simplicity and elasticity make it the best choice for building APIs in no time. In my talk, I will cover the basics concepts of Flask and Requests. I will show the tools that can automate the most common tasks in API development and will share the design patterns to avoid common pitfalls. Some of the specific tools and topics that I'll cover: Flask-Restplus, SQLAlchemy, request lifecycles, REST + CRUD API patterns, Flask architecture", + "Last Updated": "24 Jun, 2018", + "Prerequisites": "No previous experience in Flask is needed", + "Section": "Web development", + "Speaker Info": "Sara is a seasoned software engineer and the Co-Founder of Gradient.gt, a data science and machine learning consulting company based in Guatemala, where she works crafting web applications and solutions to companies in need. When she is not coding, she spends her free time baking sweet treats and watching Rick and Morty", + "Speaker Links": "www.sara-codes.com Linkedin.com/in/sarairisgarcia Gradient G", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "montjoile", + "created_on": "24 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-apis-in-no-time-using-flask~bmVGd/", + "title": "Designing APIs in no time using Flask" + }, + { + "Content URLs": "https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology I will update slides and code soo", + "Description": "Central dogma of life or of molecular biology is the core molecular process which keeps us alive! It's the machinery which converts DNA to mRNA to protein to active protein which eventually gets distributed in the body. DNA -> mRNA -> Protein Through this talk, I'll give a live demonstration of the processes by which this mechanism takes place and unravel its mysteries using Python! I'll explain how python is helping us simulating biological processes in the most elegant manner. How is DNA transcripted to mRNA? How is mRNA translated to protein? These are some of the questions I\u2019ll answer by simulating the actual processes using Python. By solving small challenges involved with this mechanism, I\u2019ll tell the audience, why Python is the best computer language for a bioinformatician and how great python libraries can make the life even easier especially BioPython. The challenges I am talking about are real bioinformatics problem, although basic, including translation, transcription and reverse complement. In the end, I\u2019ll brief some huge accomplishments of bioinformatics and computational biology and how we can contribute to this sector which has a promising future as well. Contents of the talk: Introduction : Introduction to gene and how we (computer scientists)\n recognize a gene Central Dogma of Life : a Live action of how a gene\n is converted to RNA and then to protein using Python. Why Python is best for biology? : Bioinformatics can be best studied using Python Impact of this sector : Accomplishments of Computational Biology and\n bioinformatics Conclusion : Possible ways in which we can contribute. Q & A session : Questions and answers session. Outcome: After the talk, the audience will have an understanding of how we function at a cellular level, how proteins are formed in our body and how can we simulate other biological processes using Python and will recognize the power of Python which can be harnessed in biology as well as other sciences. They will also have a basic introduction of BioPython", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Curiosity to learn :", + "Section": "Others", + "Speaker Info": "I have completed my B.Tech in Biotechnology this year from IIT Roorkee. I have interests in Web applications, Artificial Intelligence and Computational Biology. I have worked a couple of years in Computational Biology and Translational Bioinformatics Lab at my Institute and currently a Google Summer of Code student working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API ", + "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "hulksmash (~someshchaturvedi)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/simulating-central-dogma-of-life-using-python~enV7e/", + "title": "Simulating central dogma of life using Python" + }, + { + "Content URLs": "Content of my talk: Computer Vision with Pytho", + "Description": "We all(probably) love facial recognition feature isn't it?. We all edit our images before posting it to social media to give a flamboyant touch and its done in too simple steps. Open the editing software, select what you want to configure(filters, Sharpness, etc.) and you're done. Quite easy, right? But what if you know how the back-end of how these softwares run? what if you know the what kind of codes make your camera detect objects? Well with OpenCV and python its simpler than you can imagine! My talk will be about OpenCV with Python. OpenCV is an acronym for Open Source Computer Vision Library . Its a library used for image processing. The code can be written in C++, Java or Python but since we all love Python, we'll use that. We will be using ' cv2 ' library for all the image processing and detection. My talk will feature: How images are stored in computer and how each pixels store image. Different types of Colour Bands and the role of Colour Bands in forming an image. Editing images with cv2 library in python. Blurring, Sharpening, Greyscaling, and other uses of image kernels. Object and Face Detection and live object Tracking using python and OpenCV.", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Basic knowledge of Python and basic mathematics(Class 10th)", + "Section": "Others", + "Speaker Info": "I am an undergraduate final year student, CSE branch from REVA University. I am a passionate programmer. I am an IEEE Volunteer. I was the Chair of IEEE Computer Society Chapter REVA University. Right now i am Student Branch Coordinator at IEEE Region 10(Asia/Pacific).\nCurrently I am interning at Valtech India as a Java Developer.\nI have taught python to more than 150 students in my college by taking sessions. I have taught OpenCV to more than 80 students.\nI started loving python since 2016 when I read the book 'learn python the hard way by Zed Shaw'. My almost all the undergraduate projects are based on python", + "Speaker Links": "Read my Blog! My Github Connect with me on LinkedIn", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Rohan Vijay (~rohan96)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/computer-vision-with-python~bo9Xe/", + "title": "Computer Vision with Python." + }, + { + "Content URLs": "https://github.com/vibrantabhi19/PyConIndia2018 (A Github Link to the slides and the Jupyter Notebooks) https://docs.google.com/presentation/d/1UmT3PbazC6sO_owIeiLNj5G1EdTwrdpS84JWenO-3eE/edit?usp=sharing (Introduction Slide for CNN and PyTorch) Some more slides and notebooks as and when we come up with more ideas to make the workshop interacting and interesting", + "Description": "Just like in our everyday lives, AI and robotics are increasingly a part of our healthcare ecosystem. Currently healthcare is broken; there\u2019s shortage of doctors; poor quality of care. There is a dire need to provide assistance to the whole medical industry to improve healthcare. PyTorch, which is a very popular modular deep learning framework for fast, flexible experimentation is an invaluable resource for such problems. It supports seamless conversion of Numpy arrays into GPU tensors and vice versa. The dynamic computational graph allows to change the network behavior on the fly unlike static graphs and due to Its highly modular nature helps in fast debugging. Unlike other production grade tools, Pytorch helps with lots of Research and Experimentation with novel architectures and is very useful to test ideas a bit more quickly and prototyping. With Medical Imaging being the field most impacted by AI, our goal in this workshop is to give a good head start covering the heuristics of Medical Imaging, the concepts involved in it and how to code your way out. This workshop would be divided into two halfs. First Half: Pytorch Introduction\nDuration: 1 hour 20 minutes\nThe first half would be a gentle introduction to PyTorch framework. We will introduce the audience with the basics of PyTorch. This workshop will cover topics like: What is PyTorch? (Use cases and war stories) Tensor 101 Ndarray/Tensor library Numpy Bridge, Fast CPU to GPU conversion of tensors The automatic differentiation engine or autograd Difference between Static and Dynamic computational graphs Advantages of dynamic computational graph with examples The optimization package Scope of debugging Ecosystem Linear Code flow in Pytorch (One of the core philosophy of PyTorch) Saving and loading models* Deep Learning workflows* Tutorial on Transfer Learning.* Workflows which involve writing custom data-loaders will also be introduced in brief.* A 10 minute coffee/kit-kat break. :-) Second Half: Let\u2019s dive in. Duration: 1 hour 15 minutes. Introduction to Radiology: What is radiology? What do the images look like? How is AI used here? How will AI help improve radiology practice? Liver, Tumor and Vessel Segmentation - setting the context of why it is needed. Challenges faced in solving liver segmentation. How we solved the challenges - edge maps, data imbalance and overall architecture and data used. Hands on with live Liver Segmentation using PyTorch. Challenges faced in vessel segmentation and classification. How we solved the challenges - vesselness filters, overall architecture and data used. Hands on with live Vessel Segmentation using PyTorch. Putting it all together A 15 minutes Q & A session", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Zeal to learn new things would be enough but basic knowledge of Python would be good to go but the following are always encouraged: Basic Knowledge of algebra. Python Libraries such as Numpy. Basic knowledge of working with Neural Network (not a strict requirement as we will be covering most of it). We also encourage the participants to have a look into the following linked talks/videos/literature to get a head start into the topic. The related materials from web for ideas: https://github.com/soumith/talks/blob/master/2017-NIPS/Coding-papers-in-pytorch.pdf https://github.com/soumith/talks/blob/master/2017-GATech-Atlanta/PyTorch-frameworks_overview_deepdive.pdf https://www.youtube.com/watch?v=LEkyvEZoDZg https://www.youtube.com/watch?v=VMcRWYEKmhw https://www.youtube.com/watch?v=Rv9naeLXolY&index=3&list=PLrzfRWNHZPa0gKBEXTJ0gbDu8NsR07KEH https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/01-basics/pytorch_basics/main.p", + "Section": "Data science", + "Speaker Info": "Abhishek Kumar: Deep Learning Engineer, Predible Health, Bangalore. I am presently working as Deep Learning Scientist at Predible Health, here,I work on the the research and development of Predible's core Imaging platform wherein we have build state of the art segmentation algorithms/models in Computer Vision. I have previously taken workshop at IIT-Bombay Techfest, I have spoken at Shri Mata Vaishno Devi University at their SFD celebrations and at MuPy (Manipal Institute of Technology's annual Python Conference), Kongu University and a few other colleges/Universities. I have been a constant contributor in the open source world and have been attending PyCon and other conferences every year. An athlete, a Real Madrid F.C follower and a part time stand-up comedian (good enough to make you laugh). Aditya Bagari: Final year Undergrad, Indian Institute of Technology, Madras I am a final year Undergraduate student at IIT-Madras doing my Dual-Degree in Engineering Design with specialisation in Bio Medical Sciences. I have been working on Medical Imaging and PyTorch for almost a year and I have been a constant admirer of Open Source Technologies and frameworks. Feel free to drop any suggestions or modifications that you want in this workshop. See you at PyCon", + "Speaker Links": "Abhishek Kumar: Website (A very outdated one), LinkedIn , Medium , Github . Aditya Bagari: LinkedI", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Abhishek Kumar (~vibrantabhi19)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploring-pytorch-for-ai-assistance-in-medical-imaging~bqXpa/", + "title": "Exploring PyTorch for AI assistance in Medical Imaging" + }, + { + "Content URLs": "Session Content: Introduction to main units of Deep learning Feature engineering techniques for audio data DeepSpeech Architecture Live demo of DeepSpeech Project Common Voice initiative (why and its need) Community Support details Applications of speech recognition Key Takeaways: Unravel the mystery behind the AI which powers speech recognition for services such as Siri, Google Assistance etc Learn about various by which one can contribute to Project DeepSpeech & Common voice project Get introduced to major units of deep learning and state of art DL architectures powering speech to text applications Tags: AI, speech recognition, speech to text, machine learning, Python, tensorflow, deep learning, Voice search Projects links: DeepSpeech : https://github.com/mozilla/DeepSpeech https://arxiv.org/abs/1412.5567 Common voice: https://voice.mozilla.org/ https://voice.mozilla.org/en/data", + "Description": "Pitch: Our voices are no longer a mystery to speech recognition (SR) software, the technology powering these services has amazed the humanity with its ability to understand us. This talk aims to cover the intrinsic details of advanced state of art SR algorithms with live demos of Project DeepSpeech. A research says that \"50% of all searches will be voice searches by 2020\". World\u2019s technology giants have placed big bets with their investments in services providing voice search, personal digital assistant, IoT devices etc. Solving the problem of speech recognition is a herculean task, given the complexity involved with data like the human voice. The talk will cover a brief history of speech recognition algorithms, the challenges associated with building these systems and then explain how one can build advanced speech recognition system using the power of deep learning and for illustration, we will deep dive into Project DeepSpeech. Project DeepSpeech is an open source Speech-To-Text engine developed by Mozilla Research based on Baidu's Deep Speech research paper and implemented using Google's TensorFlow library. Speech recognition is not all about the technology, there's a lot more concerns, challenges around how these AI models are being part of our day to day life , it's biases etc. The bigger question revolves around centralization of these AI services, projects like Common Voice addresses these problems by enabling all to be part of this revolution, a part of the talk will focus on how people need to approach these type of research keeping in mind the community and humanitarian benefits as first priority", + "Last Updated": "25 Jun, 2018", + "Prerequisites": " Basic Python Feel enthusiastic about ML & AI services Interest to learn about speech recognition systems", + "Section": "Data science", + "Speaker Info": "Vigneshwer is an innovative machine learning researcher with an artistic perception of technology and business, having several years of experience in developing robust machine learning solutions for video and text analytical problem statements and have played key roles in analyzing problems, creating hypothesis matrix and delivering novel algorithms and data-driven solutions for many fortune 500 companies. An open Source aficionado, Official Mozilla TechSpeaker and the author of Rust cookbook", + "Speaker Links": "Github | Website | Facebook | Twitter | LinkedIn | Talk", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Vigneshwer Dhinakaran (~dvigneshwer)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-speech-recognition-with-project-deepspeech~erNpe/", + "title": "Demystifying speech recognition with Project DeepSpeech" + }, + { + "Content URLs": "TB", + "Description": "The focus is more on teaching core concepts to programmers rather than using libraries. More than one neural network will be implemented. An Easy way to learn Machine Learning An interactive way to learn ML. With ML being a leading platform in the market, the workshop introduces to one of the most important fields of Machine Learning that is Deep Neural Networks. Only basic introduction to Mathematics required. Why Python? Python for Machine Learning Machine Learning What is Machine Learning? Why learn Machine Learning? Types of Machine Learning Regression and Classification Supervised and Unsupervised Neural Networks Deep Neural Networks Feed forward Neural Networks Convolutional Neural Networks CNN Recurrent Neural Networks Layers in Neural Networks Neuron Models Perceptron Sigmoid Neuron Binary Threshold Rectifier Stochastic Binary Cost Functions (A Loss or Objective function) Gradient Descent Gradient Boosting Backpropagation Stochastic Gradient Descent Implementing the classic MNIST dataset problem A Neural Network for handwritten digit recognition Classification using individual pixels Image Classification A simple implementation using deeper networks TensorFlow Expanding the Neural Network using Google's Library for Machine Learning Might change to Caffe - nVIDIA's library for Machine Learning Deep Learning A brief introduction to Deep Learning practices Auto Encoders Other areas of Deep Learning (A qualitative study) ", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "User Prerequisites Core Python - lists, dict, string including functions and classes NumPy, SciPy - not necessary but preferred Elementary Calculus - Differentiation and Integration (Understanding qualitatively is enough) Linear Algebra System Requirements 32/64-bit Windows/Linux architecture with at least 2GB RAM Python3 compiler with NumPy, SciPy and TensorFlow library PDF reader Other Requirements but not necessarily needed Anaconda3 (or support for ipynb files, Jupyter preferred) A graphic card", + "Section": "Core python and Standard library", + "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", + "Speaker Links": "GitHub Instagram Emai", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Aniket Chowdhury (~aniket43)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-advent-of-deep-neural-networks-neural-network-implementation-without-ml-libraries-and-extending-them-with-tensorflow~av75b/", + "title": "The Advent of Deep Neural Networks. Neural Network implementation without ML libraries and extending them with Tensorflow." + }, + { + "Content URLs": "will update soo", + "Description": "Get to Know Tkinter , pyqt5 and pyqtgraph and how to create a data visualization and control interface for your geeky arduino project in no time. Tkinter is a is the standard Python interface to the Tk GUI toolkit pyqt5 is Python bindings for the Qt cross platform UI and application toolkit pyqtgraph is Scientific Graphics and GUI Library for Python I will show you how to send the commands to Arduino using Python GUI and how parse and create a real-time graphs from Arduino dat", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "You should know how to write mighty Hello World program in Python and Arduin", + "Section": "Embedded python", + "Speaker Info": "I'm just a Tinkerer. Been playing with Python , Arduino and Raspberry Pi from few year", + "Speaker Links": "Blog - My Tinkering with Arduino GitHub linkden simple dem", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Kunchala Anil (~anilkunchalaece)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-python-gui-for-arduino-project~dw88e/", + "title": "Building Python GUI for Arduino Project" + }, + { + "Content URLs": "Will be updated soo", + "Description": "The ELK stack consists of Elasticsearch, Logstash, and Kibana. Although they've all been built to work exceptionally well together, each one is a separate project that is driven by the open-source vendor Elastic\u2014which itself began as an enterprise search platform vendor. It has now become a full-service analytics software company, mainly because of the success of the ELK stack. The session will cover basics of ELK stack for a kickstart", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Passion to Lear", + "Section": "Others", + "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International University", + "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Chhavnish Mittal (~chhavnish)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-wih-elk-stack~axNBd/", + "title": "Getting Started wih ELK Stack" + }, + { + "Content URLs": "Will be updated soo", + "Description": "Ever thought of Building a brilliant website but don't want to waste time in setting up or do the boring server setup for it or it's too hard for you to make your website secure from attackers. Well, Django is here to solve these problems for you. Django is a rich MVC-MVT Python web Framework for the website which will do all these tasks for you. After this workshop, you will be able to create dynamic high-security web applications and perform CRUD operations by interacting with the database of your choice. We will be creating a blog website where users can log in, create blogs, rate them, etc", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Laptop with Python3 installed and Pycharm (or any of your favourite IDE)", + "Section": "Web development", + "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International Universi", + "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Chhavnish Mittal (~chhavnish)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/first-steps-into-web-development-using-django-framework~dyOna/", + "title": "First Steps into Web Development using Django Framework" + }, + { + "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research\nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", + "Description": "The Python ecosystem is growing and may become the dominant platform for machine learning. The primary rationale for adopting Python for machine learning is because it is a general purpose programming language that we can use both for R&D and in production. In this talk I will discuss 1. Python and its rising use for machine learning, 2. SciPy and the functionality it provides with NumPy, Matplotlib and Pandas.\n3. scikit-learn for machine learning algorithms, TensorFlow and Keras for Deep learning and PyTorch for Natural Language Processing, 4. How to setup your Python ecosystem for machine learning and what versions to use. At the end I will also give case studies on using this Python ecosystem for biomedical applications", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", + "Section": "Data science", + "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", + "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban\nhttp://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban\nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Parthi", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mastering-machine-learning-with-python~azNya/", + "title": "Mastering Machine Learning with Python" }, - "89": { - "Content URLs": "This one is the essence of it but closed source and in java: https://lifehacker.com/how-to-build-your-own-amazon-echo-with-a-raspberry-pi-1787726931", - "Description": "Voice is the new touch. It's not going to be too long before the likes of Alexa or Google Home take over our day to day life like the Internet and the mobile phones have. There are countless tutorials on how to hook up a home automation system using a Raspberry Pi like here and here . Pair that up with voice capabilities and you can basically tell your lights to turn themselves off or the TV to change the channel. In this talk I'll cover the following: Hook up a microphone to a raspberry pi and be able to capture wav files on python. Use an online API like Google's Speech API to convert the wav to text. Give a background on what intents and entities (slots) are. Installing open source software like Snips Encoding our intents and example sentences and training the open sources software Calling a functions to do particular activities At the end there'll be a cool demo", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of what a Raspberry Pi and Python is. And maybe played with an Alexa, Siri or Google Home. Yup, low barrier of entry", - "Section": "Embedded python", - "Speaker Info": "I am Ved. I have a masters in Computer Science/Data Science from IIIT-Bangalore and I work on NLP/Linguistics at Slang Labs. My goal in life is to sit down and have a conversation with a computer at a bar coffee shop. Maybe we won't get there soon, but at least maybe I can make it reserve my seat for me", - "Speaker Links": " vedmathai.com https://github.com/vedmathai/ https://www.linkedin.com/in/vedmathai/", - "Target Audience": "Intermediate", + { + "Content URLs": " Open Library Website Open Library Github Repository Open Library Client Github Repository Open Library Bots Github Repository", + "Description": "This Workshop is designed to guide developers who are interested in learning more about the basics of open source software and contributing to their first open source project. We'll look at Open Library, a mature open source project, and see how 20 open source contributors are able to make contributions which impact over a million international users. You\u2019ll learn what tools, best practices, and processes help make an open source project successful and what beginning steps you can take to enter the open source world. What is Open Library? Open Library is a non-profit online library created by Aaron Swartz and Brewster Kahle in 2006 with the mission of \u201cOne Web Page for every book ever published\u201d. Open Library is written in Python using the web.py micro-framework, and is open source on Github. Open Library uses Infobase, its own database framework based on PostgreSQL and Infogami which is its own Wiki Engine using Python. Why Open Library? Open Library has an active, supportive community, newcomer-friendly issues, and mature documentation , which makes it a good candidate for engineers who are looking to contribute to their first open source project . Some of the advantages of having Open Library as your entry to the world of Open Source Software are as follows: Open Library is very easy to install and has simple and straight-forward instructions. Issues for Beginners are labelled as first-timer-issues on the repository to help beginners get over their fear of contributing to Open Source and making it a simple process for them. Open Library has a community call every week in order to catch up the progress that each contributor is making. There is a Slack channel where anyone can be invited to and GitHub issues for communication. There is an updated Wiki which keeps getting updated as contributors contribute to the project. All coding procedures followed by Open Library are documented in a CONTRIBUTING / Getting Started guide. Some of the opportunities for new developers looking to get started to contributing to Open Library are as follows: Open Library does poorly as compared to global standards (like a modern js build system) and this is a huge opportunity for people who want to contribute to Open Library. it relies on a lot of custom code like Infogami and Infobase which are not well maintained anymore and are mostly in Python 2. So there is huge opportunity here in building a complete system while migrating to Python 3 while making sure you do retain the ease of the old code. Session Plan Creating a Github account and finding us on Github. Comment on the Slack Invite Issue to be added to the Open Library Slack Org. Understand how communication works on Open Library and getting familiar with using Github Issues and Slack for communication. Introducing yourself to the Open Library Community on Slack and initiating to become an 'Open Library Librarian'. This stage also involves talking with the Open Library community and finding Issues that match your interest. A simple and brief introduction to Git(clone, add, commit, push, pull) and Github (Fork, PRs, Issues). Setting up the project on your local dev environment. Reading Documentation as this is an important part of learning to contribute to Open Source Software. Using the Github Bug Tracker to find First Timer Issues to resolve and work on them. Making your first commit as a Open Library Librarian and submitting a Pull Request. Getting your Pull Request Merged after following community guidelines. Understanding the review process followed at Open Library and making sure to use that effectively to contribute to further Issues!", + "Last Updated": "25 Jun, 2018", + "Prerequisites": " Basic understanding of Python Ability to read documentation to understand the codebase Basic understanding of git and scm", + "Section": "Web development", + "Speaker Info": "Salman Shah is a Final Year Undergraduate Student at NITK Surathkal and a GSoC Student at Open Library, Internet Archive. Salman is a night owl whose primary interests include reading novels, participating in Hackathons and discussing technology. His language of choice is Python which he\u2019s used to add thousands of books to openlibrary", + "Speaker Links": " Personal Website Github Profile LinkedIn Profile", + "Target Audience": "Beginner", "Type": "Workshops", - "author": "Ved Mathai (~ved47)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/create-a-voice-conversational-agent-for-your-raspberry-pi-home-automation-system~eZgQa/", - "title": "Create a voice conversational agent for your raspberry pi home automation system" + "author": "Salman Shah (~salman96)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/open-library-one-web-page-for-every-book-ever-published~aA7ld/", + "title": "Open Library - One Web Page for every book ever Published" }, - "90": { - "Content URLs": "Shall be updated soon", - "Description": "Here, We will talk about how you can make a bot to help you automate your life and make your very personal Assistant, and maybe you will end up making something better than Google Assistant or Siri. We will be using modules to perform a task, so you can keep making them as you go and your assistance will keep becoming more powerful and yes all this will be done in python. In this talk: - We will start with setting up project creating simple python GUI. - Making some modules to perform a simple task. ~ Composing email with speach ~ Some other cool modules - Explaining what else we can achieve with this. ~ Let's make, its personality using tensorflow for talking stuff - Showing my work and explaining how it works Here, Is in early development phase Then we will end with some questions and how they can continue with this project", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic Understanding of Python", - "Section": "Developer tools and Automation", - "Speaker Info": "He is a student, a self-taught programmer loves to dig deep and know more about the computers. Fell in love with python and now loves to Automated things with python. He is GSoC aspirant. He is an active volunteer at PyDelhi and ALiAS . When he is not automating things he loves to contribute to open-source and closing issues", - "Speaker Links": "Website: omkar.site Github: @omi1085", + { + "Content URLs": "TB", + "Description": "This tutorial is meant to familiarize participants with Tensorflow, generally as a tensor library and particularly as a tool for doing day-to-day machine learning tasks. The ultimate goal of the tutorial is to be able to make participants comfortable enough with it so that they can use tensorflow as a scalable substitute for other ML libraries like sklearn. Why Learn Tensorflow? For the same reason that you should learn NumPy. Tensorflow is to Keras (and many other deep learning libraries) what NumPy is to sklearn (and many other machine learning libraries). It is the underlying data model of many deep learning applications. There are always nooks and crannies in any deep learning application that high level wrapper libraries cannot reach. The tutorial is aimed at making these accessible and debuggable with tensorflow. What will I learn? The focus of the tutorial would be on loss functions - ensuring their fundamental correctness with respect to the machine learning problem at hand, ensuring their differentiability and convergence are critical to solving a deep learning problem. There are many ready-made loss functions in tensorflow, and using these as building blocks, we will see how to make arbitrarily complex loss functions. FAQs: Q. Will I need a GPU? A. No. The beauty of tensorflow is that it can seamlessly deploy code to GPUs, without you needing a GPU to develop that code. Q. What is the format of the tutorial? A. Being a tutorial, this session is meant to be highly interactive in nature. It will be a sequence of units where concepts are first explained and then the audience will have to solve exercises in a Jupyter notebook. Q. I don't know anything about neural networks or deep learning. Should I attend this tutorial? A. Absolutely. The focus is on tensors, which are the domain of tensorflow, and not on network layers, which are domain of keras", + "Last Updated": "25 Jun, 2018", + "Prerequisites": " Basic knowledge of Python data structures and NumPy arrays Basic knowledge of linear algebra Elementary vector calculus", + "Section": "Data science", + "Speaker Info": "Jaidev is a data scientist based in New Delhi, India. He specializes in building data-driven products and the tooling around them for a living. His research interests are in signal processing and computational harmonic analysis. He is obsessed with applications of machine learning in personal productivity and recommendation systems. He blogs about these here ", + "Speaker Links": "Twitter GitHub Blo", "Target Audience": "Intermediate", "Type": "Workshops", - "author": "omkar yadav (~omkar10)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/superpybot-your-personal-assistant~bYZAd/", - "title": "SuperPyBot: Your Personal Assistant" + "author": "Jaidev Deshpande (~jaidev)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tensorflow-101~dB7Ye/", + "title": "Tensorflow 101" }, - "91": { - "Content URLs": "https://www.artima.com/weblogs/viewpost.jsp?thread=214235 http://www.dabeaz.com/python/GIL.pdf -slides tb", - "Description": "Python is an amazing language, known for its vast standard library and use in rapid prototyping. When we were trying to build a robotics system that is primarily modular and upgradeable, we ended up using Python to power the brain of the project. In this talk, we'll discuss how we designed the event loop, responsible for controlling the mechanical actions and state of a robot snake. Animating multiple motors concurrently at different speeds to different positions. Foreground and background tasks. Interrupting ongoing tasks. We will discuss best practices when performing asynchronous actions in Python, and how to ensure actions are completed within a bounded time.\nFinally we touch one of the lesser known 'features' of Python, the Global Interpreter Lock. GIL is a mutex that protects access to Python objects, preventing multiple threads from executing at once. Two threads calling a function may take twice as much time as a single thread calling the function twice. We'll discuss some of the real world implications of the GIL, along with some considerations that must be taken while writing highly synchronous Python code", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Knowledge of common Python syntax would be great", - "Section": "Core python and Standard library", - "Speaker Info": "Hi, I'm Pranith, a final year undergrad student at NMIT, Bangalore. I'm a robotics enthusiast with a passion for cypherpunk, virtual reality, and generally, the future. Apart from the usual frameworks, I've used Python across the field, ranging from web technologies implemented on raw CGI to microPython on the ESP8266. I try to apply Python in odd ways to bridge various layers of the stack, and as a result have a fair amount of experience breaking it", + { + "Content URLs": "Weather API: Open Weather Map (OWM) Public Posts: Twitter API", + "Description": "This talk focuses on demonstrating the power of Python's Statistical and Data Science Libraries. I have been working on a project to classify average human sentiments as positive or negative. Classification is completely based on the prediction made by the ML models, which incorporates the weather of the location. I will try to prove that weather is \"one of the factor\" contributing to the moods/emotions of humans and ultimately affects the decision making ability. I have achieved the accuracy of 60%, which is good enough, with the existing and publically available data. The accuracy will certainly grow along with the data", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Basic knowledge of Python Basic understanding of Statistics Pinch of common sense", + "Section": "Data science", + "Speaker Info": "I am a Python enthusiast, always a keen explorer of the power of python. I have been passionate about Python since my early college days, and then I went on developing many Web Apps, APIs based on Django and Flask, later on, my journey with Python turned towards exploring the magic of Data Science. It has been quite an interesting time spent exploring this field, and I must say that the depth cannot be determined. The more you experience, the more moments of awe occur", + "Speaker Links": " https://omkar-dsd.github.io/ https://towardsdatascience.com/a-simple-word-sense-disambiguation-application-3ca645c56357 https://medium.com/@omkar_dsd/when-killing-humans-becomes-the-right-choice-e3964419e78c https://stackoverflow.com/users/5130528/omkar-deshpande https://www.github.com/omkar-dsd", "Target Audience": "Beginner", "Type": "Talks", - "author": "Pranith Hengavalli (~prnthh)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/robot-snakes-and-the-global-interpreter-lock~eXPve/", - "title": "Robot Snakes and the Global Interpreter Lock" + "author": "Omkar Deshpande (~omkar08)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/analyzing-the-impact-of-weather-on-human-sentiments~bD7Ka/", + "title": "Analyzing the impact of weather on human sentiments" }, - "92": { - "Content URLs": "Slides : Coming soo", - "Description": "Large Python codebases can be hard to maintain. If we make it easier to understand our code bases, we make everyone more productive and help each other write fewer bugs. Static typing is one of remedies that can improve readability and maintainability of the code. That's why Python now features optional static typing as described in PEP-484 , implemented as Mypy . Mypy is an experimental variant of Python that let's you add optional type annotations to type check your Python code. And it works great on both Python 2.7 and 3.3+. Adopting static typing is easier that you think, you can start on a small set of code and move on to bigger pieces. In this talk I'll share about, PEP-484 and Introduction of type annotations in Python 3.5 Use cases of Mypy and how to use it with Python 2 and 3 Project typeshed and how to leverage it Lessons I learned by type hinting the project Twine We\u2019ll also discuss how to make it a seamless part of your project; what order to approach things in; and some powerful new packages that make it even easier today to add static types to your Python codebase than ever before", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of Python Difference between dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Wasim is a Senior Software Engineer at Zemoso Labs, Hyderabad. He's an open source fanatic who loves to create meaningful software and contribute to open source projects. Some of his contributions are included in projects like Sendgrid, Warehouse, Twine and Hazelcast. Apart from programming he also tweets . You can find him interesting on his GitHub profile ", - "Speaker Links": "Article on Medium about Mypy Open source contributions can be found at my GitHub profile ", - "Target Audience": "Intermediate", + { + "Content URLs": "TB", + "Description": "\"Data is the new Oil!\" But, what is the benefit of this oil if you cannot refine (analyse) and sell/use (derive value) it. Big Data has pushed the frontier of analytical processing to gather more actionable insights in the past decade from having separate analytical servers to performing analytics close to the Data Lake/Cloud. A new paradigm of FOG computing has recently emerged which enables analyzing data at the Edge (close to the data capture device). This talk will focus on Edge Analytics enabled by Python & Raspberry Pi. Why attend this session? This session will provide a first hand look into the paradigm of FOG computing and Edge analytics. Model deployment is a critical part of the analytics life-cycle and this talk will provide insights and best practices to ensure seamless and robust model deployment. Also, the audience will get a flavor of python in embedded devices through the live and interactive demonstration using Raspberry Pi. Content The talk will cover the following sections: Evolution of analytics (Dedicated Machines -> Cloud -> Edge) The need of Edge analytics Analytics Life-cycle (ALC): Introduction, Importance of Model Deployment, Adapting ALC for Edge Analytics Model Exchange Formats (PFA, ONNX) for Deployment: Introduction & Need for Democratizing model development process Edge Device Introduction - Raspberry Pi Introduction to Portable Format for Analytics (PFA) Model Deployment on Edge Device (Raspberry Pi) using open source PFA engine implemented in Python Hands-on Application Use Cases - Deployment of Clustering, Regression, Decision Tree, Neural Network/ Deep Learning Models", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Python 2.7.x titus python package (pip install titus)", + "Section": "Embedded python", + "Speaker Info": "A die hard Pythonista, Ankit is a full time open source contributor and a former Google Summer of Code 2013 scholar under Python Software Foundation. Currently, he is developing the open source Portable Format for Analytics (PFA) implementation - Titus on Python 3. Ankit has 4 years of industrial experience in machine learning, quantitative modelling, data analytics and visualization. Over the years, he has developed an expertise in handling the entire data analytics pipeline comprising \u2013 ingestion, exploration, transformation, modeling and deployment. He is a polyglot programmer with an extensive knowledge of algorithms, statistics and parallel programming. He has shipped multiple releases of DB Lytix, a comprehensive library of over 800 mathematical and statistical functions used widely in data mining, machine learning and analytics applications, including \u201cbig data analytics\u201d. An IIT Kanpur alumnus, Ankit is also an active researcher with publications in international journal and conferences. He is actively working in the domain of IoT Analytics and has recently presented his work: \"Discovering Knowledge from Smart Meter Data using Competitive Learning Methods\" in the Data Science Congress 2018. \u201cIn-database Analytics in the Age of Smart Meters\u201d in the 5th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, 2017. \u201cSmart Meter Data Analytics using Orange\u201d in Scipy India 2017, Mumbai. Ankit is an active contributor to the Indian Python Community and has conducted the following workshops in PyCon India and Scipy India: Scientific Computing using Orange in SciPy India 2017, Mumbai. Making Machine Learning Fruitful and Fun using Orange in PyCon India 2017, New Delhi.", + "Speaker Links": "LinkedIn Youtube channel Githu", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Wasim Thabraze (~waseem18)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mypy-optional-static-typing-for-python~bW1Ee/", - "title": "Mypy: Optional Static Typing for Python" + "author": "Ankit Mahato (~ankit60)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fog-analytics-using-raspberry-pi-and-python~eE7gb/", + "title": "Fog Analytics using Raspberry Pi and Python" }, - "93": { - "Description": "In Data Science, Garbage In = Garbage Out. Feature engineering is one of most of the important yet most neglected step in life cycle of Machine learning projects. Kaggle competitions have showed us that top Kagglers spend more than half of their time in feature engineering. Through various experiments, its also proved again & again that better features with simple model triumphs even advance models. In this talk I am planning to discuss basic as well advance feature engineering techniques which can be used by everyone in their projects Outline What is Feature Engineering ? Techniques for Numerical Variables Techniques for Categorical Variables Techniques for Textual data Advance techniques Feature Selection & Dimensionality reduction QA", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic knowledge of Python & Machine learning", + { + "Content URLs": "http://www.calmdownkarm.com/2018/clustering (Blog Post)\nhttps://github.com/CalmDownKarm/360classificatio", + "Description": "Quick walkthrough of how word2vec combined with more traditional clustering mechanisms can be used for topic modelling and document classificatio", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "Some familiarity with clustering (Kmeans) is helpful, but not required", "Section": "Data science", - "Speaker Info": " Sudarshan Gadhave is a Data Science ,Data Engineering & Data\n Integration professional with over 8 years of experience working on\n Machine Learning , Data Engineering , Data Visualization and Data\n Warehousing Projects. Currently he is working as a Specialist Data Scientist in Analytics R&D team of\n Nice Actimize ( Nice Systems) working on developing Anomaly & Fraud detection models. Earlier experience of working in Advance Analytics & Data Warehousing\n teams of NEC, Japan & John Deere (Deere & Company). Pythonista & expert in Python Machine learning stack (Numpy,Pandas,\n Scikit-Learn, Matplotlib) Active & Core member of Python Pune meetup group.Presented several\n talks on Python & machine learning in meetups, conferences and\n colleges all over Pune.", - "Speaker Links": " Github:- https://github.com/sudarshan1413 Linkedin:- https://www.linkedin.com/in/sudarshan-gadhave-73567b23/", + "Speaker Info": "Recently graduated from BML Munjal University, Developer at Gramener", + "Speaker Links": "calmdownkarm.co", "Target Audience": "Intermediate", "Type": "Talks", - "author": "sudarshan1413", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/art-of-feature-engineering-for-machine-learning~eVWza/", - "title": "Art of Feature Engineering for Machine Learning" + "author": "Karmanya Aggarwal (~CalmDownKarm)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/document-clustering-with-word2vec-and-hierarchial-clusters~dG7Jd/", + "title": "Document Clustering with Word2vec and Hierarchial Clusters" }, - "94": { - "Content URLs": "A few topics I will be covering, I would not be covering everything in detail, but hope to highlight important aspects from these links over the talk session: http://openmusictheory.com/ https://in-thread.sonic-pi.net/ https://github.com/gkvoelkl/python-sonic http://www.daveconservatoire.org/course/introduction-to-sonic-pi By the end of this talk, I aim to instil a much better idea about Live Coding and Programming Musi", - "Description": "Sonic Pi: An open-source live coding platform developed by Dr Sam Aaron aims to explore and teach programming concepts based primarily on the process of creating new sound.\nWe will venture deeper into the live coding platform and produced different genres/styles on music while coding live and dwell further into performing algorithmic music on a wider scale. I have tinkered with different styles of tones and sounds in sonic-pi and Python and re-created a rendition of popular 21st century music, only through algorithmic-generation, and seek to promote appreciation about open-source software such as sonic-pi and aim to demonstrate it's applications, along with the use of Python over the course of a thirty minute-talk and demo, in the rendition of producing Algorithmic-Music Live , during the course of the talk. By the end of the session, I aim to establish a better understanding of Live-coding, Programming Music and Intelligent-dance music Artists such as Aphex Twin. The flow of the talk will be as follows: Self Introduction Introduction to Music-theory and Sound Generation Introduction to Live Coding and Python-sonic Understanding the algorithmic workflow Diving beyond: Guitars, drums and Piano Produce an algorithmic-track! End of talk Q&A Session We shall also fiddle with a physical midi-controller if we find time, and demonstrate various interesting forms and styles of music; \nWe will also be producing a popular 21st century track from scratch ", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " A curiosity for algorithmically-produced music, Python and open-source software. Basic Music theory knowledge is appreciated, but anything relevant will be covered during the talk.", + { + "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research \nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", + "Description": "We survey progress in recent years toward developing a theory of deep learning. Works have started addressing issues such as: (a) the effect of architecture choices on the optimization landscape, training speed, and expressiveness (b) quantifying the true \"capacity\" of the net, as a step towards understanding why nets with hugely more parameters than training examples nevertheless do not overfit (c) understanding inherent power and limitations of deep generative models, especially (various flavors of) generative adversarial nets (GANs) (d) understanding properties of simple RNN-style language models and some of their solutions (word embeddings and sentence embeddings", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", "Section": "Others", - "Speaker Info": "My name is Sushen Kumar. I am a currently pursuing a Bachelor of Engineering in Computer Science at Sir M Visvesvaraya Institute Of Technology, Bangalore. Over the course of my academia I have dabbled into a few open-source projects, as well as contributed to open-source organisations on GitHub: Attended several hackathons around India: (Winner-ValuePitch Hack, Runners' up- IESA Makeathon) Given talks and held beginner sessions on Creative Coding in Python and sonic-pi. Completed three grades in hindustani-classical music-theory, with 8+ years of experience in playing the Guitar and Harmonium. Received 3 Honours and Awards (National level). I absolutely love Music and Coding, and aim to merge this passion and demonstrate the applications of Python and open-source frameworks in Music Production by means of this talk :)", - "Speaker Links": " https://github.com/nehsus https://www.linkedin.com/in/sushenk/", - "Target Audience": "Beginner", + "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", + "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban http://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban \nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Nehsus (~nehsus)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-algorithmic-music-and-melodies-with-python-sonic~dRXVa/", - "title": "Generating Algorithmic Music and Melodies with Python-sonic" - }, - "95": { - "Description": "Data Wrangling involves detection, correction, removal, or otherwise dealing with inaccurate and corrupted data. The most common file formats in which data can be stored are CSV, JSON, and XML. However, many times, the data is not available in the desired format and rather is available in some unconventional file formats like PDF or PPT. Parsing PDFs may seem like a daunting task to many as it is quite an unpredictable format. Simply stated, PDF is a hard-to-parse format. This workshop will help you understand the concept of Wrangling PDFs in an easy and fun way. Following will be the flow of this workshop: Self Introduction Brief Introduction to Data Wrangling Why prefer CSV, JSON, or XML? Why avoid using PDFs? Basics of RegEx based Pattern Matching Parsing PDFs Programmatically using \"slate\" and \"pdfminer\": Getting hands-on Inefficient Parsing? Consider Data Cleaning Exploring PDF Wrangling with \"pdftables\" Where to go from here? Question and Answers Session The End :) Key Takeaways: Gain confidence in Data Wrangling using Python. Get familiar with the daunting PDF Parsing task. Get hands-on with popular PDF Wrangling libraries in Python: \"slate\", \"pdfminer\", and \"pdftables\". Understand the concept and importance of Data Cleaning.", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Basic knowledge of programming in Python language. Familiarity with wrangling CSV, JSON, or XML files will be good but is not necessary.", - "Section": "Core python and Standard library", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/wrangling-unconventional-file-formats-with-python-playing-with-pdfs~aQXGe/", - "title": "Wrangling Unconventional File Formats with Python: Playing with PDFs" + "author": "Parthi", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/toward-theoretical-understanding-of-deep-learning~dJjgd/", + "title": "Toward Theoretical Understanding of Deep Learning" }, - "96": { - "Content URLs": "I delivered a talk on Recurrent Neural Networks at GeoPython 2018, Switzerland. The proposed talk will be enhanced version of my previous talk. This time, I will be covering more topics to make it a more detailed talk.\nLink to my previous talk: https://github.com/greatdevaks/GeoPython_Basel_201", - "Description": "Recurrent Neural Networks (RNNs) have become famous over time due to their property of retaining internal memory. These neural nets are widely used in recognizing patterns in sequences of data, like numerical timer series data, images, handwritten text, spoken words, genome sequences, and much more. Since these nets possess memory, there is a certain analogy that we can make to the human brain in order to learn how RNNs work. RNNs can be thought of as a network of neurons with feedback connections, unlike feedforward connections which exist in other types of Artificial Neural Networks. The flow of the talk will be as follows: Self Introduction Introduction to Deep Learning Artificial Neural Networks (ANNs) Diving DEEP into Recurrent Neural Networks (RNNs) Comparing Feedforward Networks with Feedback Networks Quick walkthrough: Implementing RNNs using Python (Keras) Understanding Backpropagation Through Time (BPTT) and Vanishing Gradient Problem Towards more sophisticated RNNs: Gated Recurrent Units (GRUs)/Long Short-Term Memory (LSTMs) End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras or TensorFlow will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", + { + "Content URLs": "https://en.wikipedia.org/wiki/Decentralized_autonomous_organization\nhttps://blockchaindevs.github.io/MeetupDA", + "Description": "Open Source Communities and their management. How things work currently A case study of different open source organizations: Advantages and disadvantages of current systems. The issues with Open Source organizations are nothing new, what are the possible solutions available? DAO and automation of majority of the tasks of a \"Open by default organizations\" What part of the organization can be automated, what can't. Important Aspects that usually breed trust among members::\n - Transparency\n - Consistency & Automation\n - Inclusion & support Our Proposal We will be posting codebase and complete websites and mobile apps that offer these solutions: Automated and transparent membership procedure. Transparent Public Elections on Blockchain for a board with automated publication of votes and results. Automate votes based on proposals Automated Procedure to apply for grants: with voting members and results being put up on Blockchain Automated meetings with MOM being recorded and put up on blockchain. Testing Proposal from the ground up: Start Small and test if these methods work locally in meetup groups \n- Automation of Tasks around meetups:\n...\nWe will keep updating here as and when we have deployed solutions on blockchain Tools used for these automation: Blockchain Dapps using : Solidity & Vyper\nPython: Kivy Framework for mobile apps and Web3.js & other such frameworks. Repos:\n They will be made online shortly, currently the experimentation is going on the following repos: https://blockchaindevs.github.io/MeetupDAO please excuse for the alpha quality of the software as they are just experiments as of now. This is a open source initiative based on the needs we feel we have seen arise in open source communities around us. Ultimate Goal Use this proposal as a catalyst and create small Organizations in local communities testing this theory. If things work in local communities, create a National Level Organization for managing the tasks around PyCon India This is just one of the hopefully multiple proposed solutions for moving on post PSSI", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "A willing ness to contribute, ability to learn. \nOpen Mind to experiment even if it leads to failure", + "Section": "Developer tools and Automation", + "Speaker Info": "http://github.com/akshayaurora Akkshay is huge open source enthusiast, he has helped bootstrap different communities around Kivy, PyDelhi, ILUGD, BlockchainDevs , HyperLedger Delhi/NCR & chaired conferences like PyDelhiConf, Pycon-India, Global Blockchain Conference. He has been involved and working on blockchain based projects from 2011 onwards, he is one of the core developers of Kivy python framework & Electrum bitcoin wallet that has been built on top of it", + "Speaker Links": "http://github.com/akshayauror", + "Target Audience": "Advanced", "Type": "Talks", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-recurrent-neural-networks-using-python~dPGAb/", - "title": "Understanding and Implementing Recurrent Neural Networks using Python" + "author": "Akshay Arora (~akshayaurora)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-open-source-communities-on-blockchain-a-transparent-way-to-manage-organizations~aKkxa/", + "title": "Automating Open Source communities on Blockchain: A transparent way to manage Organizations" }, - "97": { - "Description": "Considering the fact that businesses these days make a lot of money by recommending customers the things that match their likes, knowing how to build a Recommendation System would be of great use to many aspiring Deep Learning enthusiasts. This workshop is all about understanding and implementing Auto-Encoders. Auto-Encoders are the Unsupervised Deep Learning Models which are widely used for Dimensionality Reduction and Feature Discovery. New types of Auto-Encoders have enabled us to build very nice Recommendation Systems. The talk will focus on understanding Auto-Encoders, their types, and building a Recommender System that Predicts Rating (1 - 5) using PyTorch. The flow of the workshop will be as follows: Self Introduction Introduction to Unsupervised Deep Learning Diving DEEP into Auto-Encoders (Theory, Architecture, and Working) Introduction to Sparse Auto-Encoders Introduction to Denoising Auto-Encoders Introduction to Contractive Auto-Encoders Introduction to Stacked Auto-Encoders Understanding the Deep Auto-Encoders Training Auto-Encoders Building a Recommender System that Predicts Ratings (1 - 5) Understanding the Problem of Overcomplete Hidden Layers End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras, TensorFlow, or PyTorch will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", + { + "Content URLs": "Slides will be uploaded soon", + "Description": "Python - Turing Complete and easy at the same time. Given its simplicity, one may be tempted to use it to solve a problem of any magnitude. But as the codebase scales, so does the difficulty in managing it. And as the applicability scales up, so does the difficulty in maintaining performance. In this workshop, we will walk through how these problems crop up in the first place, and how to tackle them. This workshop will NOT cover scalability from the perspective of distributing data loading and computation across multiple compute units (horizontal scalability). We will focus more on how to write code from the very start that is both efficient in performance and makes a larger codebase manageable. The topics we will go through are: 1.Performance - How should one write \"fast\" code Finding the bottleneck - Profiling Compiling Python to C - JIT vs AOT / Cython vs Numba vs Pythran vs PyPy - How they differ and choosing which one is for you Concurrency - To parallelize or not to parallelize, to sync or not to sync Choosing the right data structures Hacks and bits that can get us the extra performance 2.Design Principles - How should one write \"good\" code, because we have all written code that we have difficulty in understanding ourselves in no time Logging - Keeping track of what happened when and where Type Checking - The why and the how Unit Tests and beyond", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Cython, numba, and pythran installed. All of them are available on pip/conda Working knowledge of Python", + "Section": "Others", + "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", + "Speaker Links": "R S Nikhil Krishna Personal Website Github Linkedin StackOverflow Lokesh Kumar T Github Linkedin StackOverflow", "Target Audience": "Intermediate", "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-auto-encoders-using-python~aOGRa/", - "title": "Understanding and Implementing Auto-Encoders Using Python" + "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-code-that-you-need-not-look-back-at-fast-and-good-python-at-scale~dLlrd/", + "title": "Writing code that you need not look back at - Fast and \"good\" python at scale" }, - "98": { - "Content URLs": "Will share the code, slides, and resources as a GitHub repository after the talk", - "Description": "Automatic Visual Speech Recognition comes very handily in scenarios that have noisy audio signals. A video image of a person talking is analyzed and shapes made by the lips are examined which are then turned into sounds by comparing to a dictionary to create matches to the words being spoken. In this talk, we will use a VGG+GRU network which is based on CNN+LSTM layers to predict the text spoken by the speaker and classify it into 20 classes from audio-less videos, consisting of 10 words and 10 phrases. This will be done on the audiovisual MIRACL-VC1 dataset. The talk will cover how a CNN+LSTM can be used to recognize a sequence of shapes formed by the mouth and then match it to a specific word or sequence of words spoken from Visual Feed. It will include data-preprocessing, creation of CNN and LSTM layers using Python and applying them on the dataset", - "Last Updated": "06 Jun, 2018", - "Prerequisites": "Basics of Python Syntax, Tensorflow, Keras, Neural Network", + { + "Content URLs": "So, Slides can be seen here: https://slides.com/tanayagrawal/efficient-hyperparameter-optimization#/ Full content is available here: https://github.com/tanayag/pycon_18_hyperopt You can also have a look at my article: https://blog.goodaudience.com/on-using-hyperopt-advanced-machine-learning-a2dde2ccece7 In the Repo iris.csv is the dataset that we'll work on. docker folder contains the scripts to setup Environment \"Introduction to Hyperopt.ipynb\" is iPython Notebook which contains the implementation which we'll work on during workshop and understand the concept \"link_to_slides.txt\" contains the link to our presentation", + "Description": "Hands on Experience with Advanced Hyper-parameter Optimization Techniques, using Hyperopt We'll go step by step, starting with the Hyper-parameter optimization with SkLearn's Grid Search, we'll compare it with the more effective Hyper-Parameter Optimization TPE Algorithm implemented in Hyperopt.\nWe'll also go through on how to parallelize the evaluations using MongoDB making the optimization even more effective. A Docker Image will be provided, so that participants won't have to waste time in setting up the environment. The Workflow of the Workshop would be: We will start with a slide presentation so that participants get some insight on what they are going to do. After that we'll shift on to a Juypter Notebook(pre-installed in the docker environment, so you can just focus on the implementation part), here they will implement the code, and see the best algorithms of hyperparameter optimization working. After that we'll show a working demo of a problem that we were working on and solved using Hyperopt during our Summer Intern at MateLabs. After attending this workshop you will be able to apply Hyper-parameter optimization using better algorithms which decides the hyper-parameters based on information. In short much much efficient model training", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "Basic Python Coding and a little familiarity with Machine Learning/Data Science", "Section": "Data science", - "Speaker Info": "Kanika Modi holds a Bachelor's in Computer Engineering from Netaji Subhas Institute of Technology, University of Delhi. Having finished her coursework, she will join Amazon as a Software Development Engineer(SDE). She is an open source enthusiast and has contributed to organizations such as Systers, Fossasia, etc. She is also a Google Summer of Code'18 mentor at Systers, a GirlScript Summer of Code'18 mentor and mentor at RightApprise. Her interests also extend to the fields of artificial intelligence and machine learning. She prefers Python as her weapon of choice", - "Speaker Links": "Link to LinkedIn Link to GitHub Link to Twitte", + "Speaker Info": "Tanay Agrawal Working on Machine Learning/Deep Learning and also an Open Source Enthusiast. Currently in Final Year of his Engineering. He is working as Deep Learning Intern at Matelabs. He along with team at MateLabs is creating Meta Algorithms, so that user even with minimum or no knowledge of Machine Learning would be able to use it. Also he is a contributor at SymPy. He has previously worked on state of the art Classification and Object detection Models as well. He has previously conducted Python workshop at SFD-SMVDU and also he conduct the session of AI Circle at his College regularly. Anubhav Kesari Currently at fInal year of engineering from IIIT Guwahati. Two worked on the same problem and solved it using Hyperopt. Anubhav is the summer intern at MateLabs as well. He has worked at Cadence Design Systems in summer of 2017 as Software Development Intern. He has also been working on development of blockchain based distributed neural networks at MateLab", + "Speaker Links": "Tanay Agrawal https://github.com/tanayag https://angel.co/tanay_agrawal Anubhav Kesari https://github.com/kesarianubhav https://www.linkedin.com/in/anubhav-kesari-588a03131", "Target Audience": "Intermediate", - "Type": "Talks", - "author": "kanika_96", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-lip-reading-system-to-recognise-visual-speech-using-python~dNG2e/", - "title": "Building A Lip Reading System To Recognise Visual Speech Using Python" - }, - "99": { - "Content URLs": "Brief content is here: https://github.com/yashug/Pandas Actual workshop will cover more inf", - "Description": "The Goal of this workshop is to make you more fluent at pandas to answer data science questions. Python has long been great for data munging and preparation, but less so for data analysis and modelling. pandas help fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R", - "Last Updated": "04 Jun, 2018", - "Prerequisites": " Laptop with Anaconda installed Basics of Python", - "Section": "Data science", - "Speaker Info": "Yaswanth is a Senior Software Engineer, currently working in ZeMoSo Technologies and Graduated from IIT Guwahati. Free and open source software enthusiast, and passionate about Python and Machine Learning", - "Speaker Links": "Linkedin | Githu", - "Target Audience": "Beginner", "Type": "Workshops", - "author": "Gosula Yaswanth (~yashug)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-pandas-for-better-data-science~aKGGa/", - "title": "Using Pandas for Better Data Science" + "author": "tanay_agrawal", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-ml-learn-how-to-improve-accuracy-by-optimizing-hyper-parameters-using-hyperopt~aMmGa/", + "title": "Advanced ML: Learn how to Improve Accuracy by optimizing Hyper-Parameters using Hyperopt" }, - "100": { - "Description": "The Jupyter ecosystem of tools lets you interleave code and stories for a literate computing experience, where you can visualize your data as html, plain text, svg and images. You could also view the same rich displays in multiple environments - on the web, on your desktop, in your shell or even your IDE . But how is this possible without duplicating logic, re-inventing the wheel multiple times? How do visualization libraries like Bokeh, Plotly work across frontends - like jupyter notebook, jupyterlab and nteract? This talk explores Jupyter's display system and how it handles multiple display formats in multiple environments. We will see how this idea is applied in some open visualization libraries. After this talk, you will know how to integrate your python objects better with the notebook. You will also get an idea of how to create a visualization library that works across the Jupyter ecosystem of tools. Duration 45 mins (Content can be modified to fit into 30-minute slot too) Outline - Setting some terminology for the rest of the talk (what is a frontend, kernel, displayhooks) (5 mins) - How to use Jupyter's display hooks for your python objects with the notebook (10 mins) - The Jupyter messaging protocol - specifically, the display_data and update_data messages (5 mins) - Custom mime-types (and this is the secret to Jupyter's display system!) - separating what to display from how to display it (10 mins) - Examples of custom mime-types in the wild (a look at altair , vdom , plotly and more) (10 mins) Additional notes This proposal might seem to overlap with another - Jupyter Notebooks: Internals and Extension - which explores how jupyter works under the hood and how to create alternative frontends. My talk's focus will be different, and will dive into a very specific part of Jupyter - the display system - in depth", - "Last Updated": "04 Jun, 2018", - "Prerequisites": "Some experience using either the jupyter notebook or jupyterlab ", - "Section": "Others", - "Speaker Info": "I am a software developer at D.E.Shaw, Hyderabad. I've occasionally contributed to projects in the jupyter ecosystem - the notebook, ipywidgets, hydrogen, nteract", - "Speaker Links": "Github Twitte", + { + "Content URLs": "https://gautam-ankit.github.io/HomeAR", + "Description": "In this project, we are going to create a home finder in which we are going to give an individual marker/bar code to each and every home and going to create a web-app which will tell about the home on starring the camera on the marker/bar code. This idea will help out to find some place way better than the Google maps because one can generate its own marker for his/her home and can edit the details of there home, through which one can recognize the home. For management of this data we are going to use several concept of Big data also. But this is the best way possible to implement and link augmented reality with python", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "HTML and CSS and basic Javascript,\nbasic python ,\nsome programming concepts", + "Section": "Core python and Standard library", + "Speaker Info": "As a Microsoft student partner, I gave several presentations for Hour of code. And as a Mozilla campus club caption, I gave several presentations for Virtual reality and Augmented reality using Aframe web framework", + "Speaker Links": "https://www.linkedin.com/in/ankit-gautam-9b0524108", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Ankit Gautam (~Gautam-ankit)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/home-finder-using-python-and-augmented-reality~dNnvd/", + "title": "Home finder using Python and Augmented Reality" + }, + { + "Content URLs": "Will be updated soon", + "Description": "In this talk, I will provide a concise understanding of Threading and Global Interpreter Lock(GIL) in Python. In the modern era of hybrid cores and processors, there is an in demand need for concurrent and parallel programming paradigms. Python, since its inception has amazing support for single threaded applications. The extensive use of Python in booming fields like Machine Learning has paved the way to constantly improve multi-threaded applications in Python. I will speak from ground level covering very crucial aspects of Threading and Locks which will provide a better roadmap for community to develop better Python applications. Program outcomes: How threading can improve performance, its pros and cons. What works best in which environment between threads and processes. Why GIL matters the most in Python How to leverage the power of open source source code to understand the crux of language. Contents to be covered: 1. Threading for noobs: Terminologies: Process, threads, multithreading, multiprocessing, types of threads, locks, mutex, CPU and I/O bound processes. Multithreading in Python: Threading module (with example) Comparative analysis of Sequential vs Multithreaded execution in Python (with example) 2. Understanding the global interpreter lock (GIL): What and why of GIL Impact of GIL on CPU and I/O Bound Processes In-depth understanding of GIL using cpython interpreter source code Reference counting Ticks via context switching 3. Infamous concepts: Cooperative vs Preemptive multitasking Parallelism vs Concurrency Thread Safety in Python 4. Removing the GIL: Famous GIL removal patch Guido on GIL, Larry Hastings Gilectomy 5. Questions Agenda: 0 - 6 minutes : section 1, Threading for noobs 6 - 15 minutes : section 2, Understanding GIL 15 - 25 minutes : section 3, Infamous concepts 25 - 28 minutes : section 4, Removing the GIL 28 - 30 minutes : section 5, Questions ", + "Last Updated": "26 Jun, 2018", + "Prerequisites": " Basics of Python: Class, objects, list, libraries", + "Section": "Core python and Standard library", + "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself from scratch. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", + "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", "Target Audience": "Beginner", "Type": "Talks", - "author": "Madhumitha psg (~madhumitha)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyters-rich-display-system~dJ1Kb/", - "title": "Jupyter's Rich Display System" + "author": "Chirag Shah (~avidLearnerInProgress)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-multithreading-by-deciphering-the-cpython-interpreter-source-code~aOora/", + "title": "Understanding multithreading by deciphering the cpython interpreter source code" }, - "101": { - "Description": "With the advent of Tableau and languages like Python and R, converting raw data into meaningful insights is much easier and convenient than before. Tableau is a tool used to visually represent data and is powerful enough to analyze the given data at any required level. At an industry perspective, the tool comes handy in finding the trends in marketing and sales with a click of a button. Introducing Python to Tableau using TabPy can help define calculated fields in Python, thereby giving it the power to leverage a large number of Machine-learning libraries right from the visualizations. This widens the scope of its applications to any field that deals with big data and its analytics. Optimisation and cross-sharing of data models facilitated by TabPy immensely enhance the efficiency and usability of the tool. With just a few lines of code, we can churn out predictive models and increase the accuracy of future predictions. The talk will primarily focus on: An introduction to data manipulation and visualization using Tableau. An overview of the steps to leverage TabPy in Tableau. The impact and advantages of Tableau-TabPy combination in the real world.", - "Last Updated": "03 Jun, 2018", - "Prerequisites": "A rudimentary understanding of Data Science and Python scripting", - "Section": "Data science", - "Speaker Info": "I am a sophomore undergrad in computer science from Amrita School of Engineering, India of which I am a part of an intra-college FOSS initiative called FOSS@Amrita. Developing small but useful things that improve lives of the common and affects the open-source community has always been my passion. I believe that with the right technology applied, it can do wonders for the lives of people. Furthermore, I have completed the Google Summer of Code\u201917 with The Wikimedia Foundation and was also a Google Code-In mentor for the same community. Worked on the project that aimed at the improvement and enhancement of the ProofreadPage Extension and Wikisource , through important bug fixes that are left as backlog and implementation of significant features that would make it more user-friendly. This was done so that the extension and Wikisource become easier to use and are raised to the contemporary Mediawiki standards. Apart from this, I'd love to \u200bexpress\u200b \u200bviews\u200b on\u200b \u200bcontemporary\u200b \u200bworld issues,\u200b \u200bget\u200b to know\u200b \u200bthe\u200b \u200bdifferent dimensions\u200b of\u200b \u200bit and analyze the\u200b \u200bmultiple\u200b\u200b ways\u200b \u200bin\u200b\u200b which\u200b \u200bthe\u200b \u200bproblems\u200b \u200bcould be rectified", - "Speaker Links": "Linkedin Blog Gerrit GitHu", + { + "Content URLs": "Slides will be uploaded soon. Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv", + "Description": "There lies a huge gap between a website made as a hobby/college project and that made for professional purposes. The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! Before delving into the open source world, my code screamed that it's owned by a college kid. But things changed once I interned with Wikimedia (under the Outreachy program). I want to share this very experience with my audience that how some gotchas and design decisions can bring about this transition. In this talk, I'll touch upon some of these areas that mainly deal with backend and database. My talk will summarize my learning from using Django in an application built for Wikipedia and is capable of handling huge amount of Wikipedia's data. To give a bit of background - I built this application for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/). The app summarizes the contributions of the Wikipedia editors and presents it in a CV-like format. The biggest development challenge was dealing with millions of edits and doing all the related computations within seconds. Without any kind of optimizations, the webpage took 3 hours to load. Through my talk, I want to bring out the journey from 3 hours to 3 seconds on the table! Broad outline of my talk is as follows: Why Django : It's very important to understand why and when to use Django. Majorly I'll be touching upon the scalability aspect and how it's a full package when it comes to web development. Reducing the response time : When one is dealing with a database as huge as that of Wikipedia's, response time becomes of paramount importance. Optimizations like implementing a cache layer , using cron jobs , sessions etc will be discussed. Also, design choices will be compared - like cache layer using database vs sessions in python. Database Optimizations : In this I'll be covering how database choice and query optimizations can affect the performance when dealing with large datasets. Hope you will find this talk interesting. :)", + "Last Updated": "26 Jun, 2018", + "Prerequisites": "Basic knowledge of Python, Django and querying RDBMS is required", + "Section": "Web development", + "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia.\nOther than coding, I love reading, writing and trying out new things", + "Speaker Links": " Blog: https://medium.com/@meghasharma4910 Github: https://github.com/MeghaSharma21 Outreachy project: https://github.com/MeghaSharma21/WikiCV Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018", "Target Audience": "Beginner", "Type": "Talks", - "author": "Amrit Sreekumar (~amrit95)", - "created_on": "03 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-leveraging-python-in-tableau~dGAKa/", - "title": "Data Analysis: Leveraging Python in Tableau" + "author": "Megha Sharma (~megha480)", + "created_on": "26 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/optimizations-in-web-development-journey-from-a-college-project-to-a-professional-product~dPp4d/", + "title": "Optimizations in Web Development: Journey from a college project to a professional product" }, - "102": { - "Content URLs": "We will share the Github repository for the workshop here couple of weeks before the conference", - "Description": "\"Our Business Is Our Business None Of Your Business\u2026\" Yes, they wish, but we want to know everything about Bollywood! Who is more popular, Katrina Kaif or Deepika Padukone ? When budget is not a problem, do producers prefer Shah Rukh Khan or Salman Khan ? Which city in India is home of the most active actresses and actors? What movie is the most similar to PK ? And lots of other questions. Do you want to know the answers? And even better, would you like to discover them yourself by using Python and popular libraries such as pandas, Gensim and scikit-learn? And cutting-edge data science techniques? Join us for a workshop full of insights where you will be able to answer your own questions while learning the most advanced Python libraries and algorithms. The workshop is designed for Python programmers new to data science. Everybody is welcome, but data analysts and people experienced with pandas will find some parts quite basic. What will we cover? Loading, merging, cleaning and analysing your data with pandas Advanced data visualisation with Bokeh Embeddings and natural language processing with Gensim Forecasting with statsmodel Basic machine learning with scikit-learn All this while answering the questions above, and letting you answer your own questions", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Laptop with Anaconda3 installed Clone of the workshop repository Knowledge of Python Good knowledge of Bollywood desirable :)", + { + "Content URLs": "Tutorial Series https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-2 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-3 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-4 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-5 Github Repo (Most starred repo for a Python implementation of YOLO v3, at 589 stars at the time of speaking) https://github.com/ayooshkathuria/pytorch-yolo-v", + "Description": "The workshop will walk the audience on how to implement a state of the art object detector (YOLO: You only look once) from scratch using the PyTorch deep learning framework. The main The aim is not to merely show the audience how to implement the detector that can work on videos, but give them a deep insight about the problems that rear their heads only when one is implementing a deep architecture. Some of these issues include, Rapid Prototyping with PyTorch : Which PyTorch classes and abstractions to use to quickly code up neural network. How to implement a layer if it doesn't already ship with PyTorch. Our detector has 3 such layers! How to deal with complex architectures efficiently : What if your network has more than a 100 layers? Our detector certainly has 106 ! Do we write 106 lines of code for each layer? What if we want to run our detector over a folder containing 100000 images that we can't fit into our RAM at once. Best PyTorch practices to get around problems like these will be discussed. Speeding up Python code with Vectorisation : Python can be a slow language, but PyTorch does provide a lot of functions that are merely wrappers for super fast C code under the hood. Vectorisation and broadcasting will be covered in great detail. Using vectorised code instead of loops to do iterative tasks can give speed ups as much as 100x. Our detector can not work in real time without these optimisations. Managing GPU resources : How to write device-agnostic code, parallelize GPU/CPU ops, practices to reduce redundant GPU memory usage, and how to time GPU code. We will review the entire code base, and spend much time on justifying design decisions. A lot of non-critical code will be provided as it is to the audience, while they are expected to code along when it comes to the critical parts. These parts would be discussed in greater detail. Important PyTorch features might also be demonstrated using toy examples outside the detector code base, which the audience is also expected to code along. A docker image as well as Jupyter notebook will be provided to the audience. Google Colab may also be considered with notebooks provided. Most of the tutorials online demonstrate how to write code that is more proof-of-concept rather than being performant. When it comes to learning to code complex architectures, especially when we are transitioning from beginner to intermediate stage, most of us have to rely on the laborious process of reading open source code. The idea of this workshop is to help audience move along this journey", + "Last Updated": "27 Jun, 2018", + "Prerequisites": " Knowledge of Python Basic understanding of convolutional neural networks, image classification and preferably, but not necessarily object detection (Will spend 15 min or so giving an overview of YOLO algorithm) Basic understanding of PyTorch (the level that can be reached by taking the official 60 min tutorial)", "Section": "Data science", - "Speaker Info": "Himanshu is the organiser of Kanpur Python and PyData Kanpur. Free and open source software enthusiast, and passionate about Python and data analysis, He is currently working for KanpurFOSS organization which organize free technical workshops in India. Yai Workshop\u2026 Data Analysis Ke Workshop Hai\u2026 Kisi Ke Data Analysis sikha kar He Khatam Hoge... Marc (known online as datapythonista) is a data scientist from London. Pythonista since 2006, pandas contributor, and organiser of the London Python Sprints group. Worked for companies like Bank of America, Tesco, Unilever or NTT Communications. Regular speaker at PyCon and PyData conferences. His favourite actor is Aamir Khan, but wouldn't mind teaching Python to Asin", - "Speaker Links": "Himanshu : https://twitter.com/IHackPY | https://www.slideshare.net/HimanshuAwasthi14/ | https://speakerdeck.com/johim9493 Marc : https://twitter.com/datapythonista | https://www.linkedin.com/in/datapythonista/ | http://datapythonista.github.io", - "Target Audience": "Beginner", + "Speaker Info": "I'm currently an research intern at a DRDO Lab where I work on video semantics, detecting violence as well as unusual activity in surveillance footage. My other interests include weakl supervised, unsupervised learning and generative modelling using GANS. I've recently graduated college, and while at college, I founded AI Circle, SMVDU, a club dedicated to helping students get started with machine learning through lectures and hands-on sessions, many of which were conducted by me. I am very passionate about sharing what I've learned, and write articles regularly at Paperspace and Medium", + "Speaker Links": "Paperspace blog: https://blog.paperspace.com/author/ayoosh/ Medium : https://medium.com/@ayoosh Github : https://github.com/ayooshkathuri", + "Target Audience": "Intermediate", "Type": "Workshops", - "author": "Marc Garcia (~marc)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decoding-bollywood-with-python-and-data-science~eEyWe/", - "title": "Decoding Bollywood with Python and data science" + "author": "Ayoosh Kathuria (~ayoosh)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-implement-a-yolo-object-detector-from-scratch-using-pytorch-and-opencv~aQq9a/", + "title": "How to implement a YOLO object detector from scratch using PyTorch and OpenCV" }, - "103": { - "Content URLs": "PyCon India 201", - "Description": "What's a good way to Set up many development version(s) ? Developers need consistent isolated development environment, running exact same container(s) as what runs in production , automated test tools, package, ship & deliver. Let's touch features of docker to make it run for Python programs/web apps. Outlines First 5 minutes, I'll be talking about current developers need and present solution. Next 5 minutes, what is docker and how it can solve these problems. Next 10 minutes, I'll be demonstrating, how I use docker for in my Python development tasks (Python library, Python web app). After 20 minutes I will have delivered the enough knowledge for the docker, and next 5 minutes I will let the audience know about the some advance features in docker that they can learn from various resources, to get the maximum power of docker. Q/A along with this. Detail description Basic terms of docker Docker Container Docker Image Dockerfile Docker Compose Docker Repository and Docker Hub Docker Daemon, Docker Client and Docker Engine Docker Swarm Docker Machine Docker for Developers Reproducibility and Developer teams Isolation Security Environment Management Continuous Integration Creating Custom Images and Containerizing Your Application Sample Dockerfile to build an image of an small python program. We will run the image and play with this container. Using Docker Compose in development adds an important constraint: your services are not on the same machine anymore. Container Logs Learn how you can see or capture the logs of the container(s) and services. Docker for Python developers In this section I will demonstrate, how you can setup a development version of real world software.\nI will setup the development version. After creating an image and running it in a container, I will show volume sharing techniques as well. Audience will understand how I have created an consistent isolated container, integrated CI which is easy and fast to ship. Docker for Python Web applications Django and Flask web app will be run under the docker container, different environments in one system. We will learn how to use microservices and advantages of making services using docker-compose. Advance and new features of docker Now audience have understood the docker and they can learn many more powerful features of docker. I will share some good resources and let them know about docker swarm, docker machine, Dealing with Logs, etc ", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "Prior experience with docker is not a necessity but having some exposure to Python development, version control system, Unix System is recommended. At the starting talk basic developers need, basic docker features will be covered. So starting point, anyone (entry/intermediate) can understand the docker concepts. Slowly moving to docker for developers, expert Python developers will get ideas to use docker in their development system and how they can solve most of the development conflicts because of using having multiple environments", - "Section": "Developer tools and Automation", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Advanced", + { + "Content URLs": "in progres", + "Description": "Data classes have been introduced in Python 3.7 (Refer to PEP 557 -- Data Classes). This talk is to introduce data classes to the audience. Talk about why data classes and how they are different from other alternatives like named tuples, et", + "Last Updated": "27 Jun, 2018", + "Prerequisites": "Knowlede of Object Oriented Programming with Pytho", + "Section": "Core python and Standard library", + "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.\nI have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delhi I have done a talk \"How import works in Python\" at Pycon 2017 Delh", + "Speaker Links": "github link - https://github.com/sdonapar\nlinkedin profile - https://www.linkedin.com/in/sasidonaparthi\ntwitter handle - @sdonapa", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/containerizing-your-application-is-the-solution~dBvQd/", - "title": "Containerizing Your Application is the solution" + "author": "Sasidhar Donaparthi (~sasidhar)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/what-you-need-to-know-about-data-classes-in-python-37~dRrEd/", + "title": "What you need to know about data classes in Python 3.7" }, - "104": { - "Content URLs": "Slides will be updated soon. Django2 release note", - "Description": "Django is one of the most used Python framework in the world of Python and is even used more than Tensorflow(Stack Overflow 2018 Developer Survey). Django is an excellent web-application framework to build scalable, extensible and high-performance web applications that can serve hundreds of thousands of requests per second -- while keeping the development cycle optimal and maintaining the sanity of developer mind-space. The latest version of Django 2.0 has been just released this year. The new Django 2.0 begins a new era without any backward incompatible changes except the removal of Python2.7 in latest version and it aims to completely remove Python2 support for Django environment when LTS Django 1.11 expires in 2020 with Python2 . This release also starts the Django using the loose form of semantic versioning. Django 2 has introduced a lot of major changes like : SImplified URL routing syntax Performance optimisation and improvements Mobile Friendly Admin site Newer functions like Windows and more modified aggregate functions More stricter schema Made Mysql isolation as read committed Talk Outlines What is Django and why use Django? Django design patterns - MTV kind of MVC How does Django works? Simplified URL routing syntax in Django2 Other new features in Django2 When should you move your old project to Django2 and Django release Cycle Tips on converting your legacy code to Django2 This talk aims to provide some general insights on Django and latest Django2 version. Apart from being a talk focussed exclusively on Django, the talk aims to give be an introduction to what server side programming is and in general to Web Development ", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Python Django (preferable) After all this is a Hitchhiker\u2019s guide, this talk will focus on a general introduction to Django and don\u2019t be afraid all the noobs in Python and Django will welcomed and be accommodated in this talk", - "Section": "Web development", - "Speaker Info": "Kurian is currently in his sophomore year, pursuing an undergraduate degree in Computer Science from Govt. Model Engineering College, Kochi. He has interned in multiple startups like Entri.me, WiM as a product intern developing products using Python and web frameworks like Django. He is also a Open source Enthusiast and have contributed to multiple organisation like Zulip , FOSS Asia. He is an active member of FOSS club in his college(FOSSMEC) and of Kochi Python Club(Python Meetup Group of Kerala)", - "Speaker Links": "Github LinkedIn Medium Twitte", + { + "Content URLs": "http://www.thedurkweb.com/automated-anonymous-interactions-with-websites-using-python-and-tor", + "Description": "Need to get some repetitive task done on your web browser? Want to automatically fill boring forms? Or maybe you want to crawl pages that annoyingly check whether you are a browser or a robot. Or maybe you want to repeatedly bias an online poll in your favour (as long as you don't harm anyone). Circumvent all of that with Selenium, the browser automation tool. And if want you want to protect your IP while doing it then just fire up tor-selenium browser, which gives you the power of tor and browser automation. In this talk: I'll show you how to set up the browser. How to access the website through code. How to design your script to navigate through the pages and button clicks. How to effectively do your activity, like filling up text fields etc. And then a demo of it working completely.", + "Last Updated": "27 Jun, 2018", + "Section": "Developer tools and Automation", "Target Audience": "Beginner", "Type": "Talks", - "author": "Kurian Benoy (~kurianbenoy)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-hitchhikers-guide-to-django-2~aAr9b/", - "title": "The Hitchhiker\u2019s Guide to Django 2" + "author": "Ved Mathai (~ved47)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automate-anything-on-the-web-using-python-bindings-for-tor-selenium-and-hide-your-ip-while-doing-it~eVyXd/", + "title": "Automate anything on the Web using Python bindings for Tor-Selenium and hide your IP while doing it." }, - "105": { - "Description": "The goal of this talk is to explain this quote : \u201cYou shall know a \u2018word\u2019 by the company it keeps!\u201d In this talk, we will go through as to how to build a model for text summarisation (from scratch) and its possible applications in the real world scenario. An intuitive explanation will be provided (the talk would not be all mathematical!) as to how to do the data preprocessing for a large dataset and provide a reasoning as to why we choose a specific model for training. We will also talk about how certain Python libraries make it easier to structure a machine learning pipeline. We will also walk through the best practices and various caveats while building these kinds of complex models and how to circumvent these", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "The prospective audience should have a basic understanding of neural networks and natural language processing", + { + "Content URLs": "Would be uploaded soo", + "Description": "My talk would be starting from the very grounds of machine learning . What is it and how is it connected with our biological brain. I will be introducing some biological concepts and infrastructure of our brain to explain to them how our natural ability of thinking and deduction work, because at last the whole field of artificial intelligence is just an attempt to mimic our brain. Isn't it?\nThis will be through a series of fun QnA . Then we will see the mathematics core which enables us to lay down the logic and basics of the brain as formulas . \n- Then we will start with the classic linear regression . Will study the basic idea behind it and also see what kind of problems we should apply it.\n- Next will be the logistic regression , a classification algorithm. Learn the difference between these two and how logistic regression could be implemented and study the beautiful mathematics behind it. \n- Then we will go for a clustering algorithm, that is, Knn . Study the simple dynamics and application of this algorithm\n- Then a glimpse over the structure and mathematics of neural network . As this talk is for the novice I would keep the mathematics to the minimum and would no go deep into \"deep\" learning.\nWe will wrap up seeing some of my projects in action so that the audience could feel the power of AI", + "Last Updated": "27 Jun, 2018", "Section": "Data science", - "Speaker Info": "Harshdeep is currently a student at the University of Manchester pursuing his Bachelors in Artificial Intelligence and is interested in Natural Language Processing. My experience with Python started at IBM Bristol where I worked for a year developing the compliance automation tool. After that, I worked on my final year research project using Python which was based on finding summaries and sentiment of news articles. I have previously spoken at PyCon APAC in Malaysia last year in August which was a talk about the basics of Neural Networks. After university, I will be working with some early stage startups in India related to AI and Aviation", - "Target Audience": "Intermediate", + "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", + "Speaker Links": "udayupreti.m", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Harshdeep Harshdeep (~harshdeep)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/text-summarisation-made-fun~azAqe/", - "title": "Text summarisation made fun!" + "author": "uday1201", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/evolution-and-basics-of-machine-learning~bWzxa/", + "title": "Evolution and basics of Machine Learning" }, - "106": { - "Content URLs": " Initial version of slides (will update regularly and mark it complete once done)", - "Description": "Abstract Being one of the most used collaboration tools used by software engineers and data scientists, \"Jupyter Notebooks\" are transforming the way \"data science\" is happening in the industry. Started as a smart Python interpreter, the Jupyter project has grown into a common platform that supports the development of data science and scientific computing tools across multiple programming languages. This talk is aimed at understanding the technical internals of Jupyter project. Agenda A brief introduction to Jupyter How is it different from IPython Component architecture Kernel Frontend Communication protocol used between a frontend and kernel How does a kernel work Magic commands How to create one Let's create a Jupyter frontend Wait! What if you can use Slack as a Jupyter notebook? Jupyter, Interactive computing, and possibilities What will you learn Process that powers an interactive Jupyter session Do you know how does the tab-completion work? Extending the capabilities offered by Jupyter ecosystem for a custom use-case We will learn how to create magic commands and frontend Black magic", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Basic understanding of Python, comfortable with functions/classes Experience working with Jupyter/IPython notebooks (Optional) Interested in knowing how stuff works", + { + "Content URLs": "This talk will be based on my article on Towards Data Science The hands-on examples have also been open-sourced on GitHu", + "Description": "Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. We will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D) using a hands-on approach with Python and popular open-source visualization libraries like matplotlib and seaborn. The talk shall be structured as follows: Motivation for Effective Data Visualization A quick refresher on Data Visualization Brief introduction into python open-source frameworks for visualization pandas matplotlib seaborn bokeh Univariate analysis with hands-on examples Multivariate analysis with hands-on examples Visualizing data in 2, 3, 4, 5 and 6 dimensions Visualizing a combination of numeric and categorical data Strategies for effective data visualization Conclusion", + "Last Updated": "25 Jun, 2018", + "Prerequisites": "Basics of Python, data terminology (rows, columns, feature, data points, data types) helps but we will be covering briefly during the session. Hence it's not essential", "Section": "Data science", - "Speaker Info": " Tech & Product at Vernacular.ai Data-driven journalism practitioner Featured in Tech in Asia and Global Investigative Journalism Network Contributor to Go programming language", - "Speaker Links": " Website GitHub Twitter", + "Speaker Info": "Dipanjan Sarkar is a Data Scientist at Intel, on a mission to make the world more connected and productive. He primarily works on data science, analytics, business intelligence, application development, and building large-scale intelligent systems. He holds a master of technology degree in Information Technology with specializations in Data Science and Software Engineering. He is also an avid supporter of self-learning. Dipanjan has been an analytics practitioner for several years now, specializing in machine learning, natural language processing, statistical methods and deep learning. Having a passion for data science and education, he is a Data Science Mentor at Springboard, helping people up-skill on areas like Data Science and Machine Learning. He also acts as a contributor and editor for Towards Data Science, a leading online journal focusing on Artificial Intelligence and Data Science. Dipanjan has also authored several books on R, Python, Machine Learning, Social Media Analytics, Natural Language Processing & Deep Learning. More about me: LinkedIn: https://www.linkedin.com/in/dipanzan/ GitHub: https://github.com/dipanjan", + "Speaker Links": "LinkedIn: https://www.linkedin.com/in/dipanzan/ Blog Posts: https://towardsdatascience.com/@dipanzan.sarkar GitHub: https://github.com/dipanjanS Featured stories on KDnuggets: https://www.kdnuggets.com/?s=dipanjan+sarkar Recent books:- https://www.springer.com/us/book/9781484223871 https://www.springer.com/us/book/9781484232064 https://www.packtpub.com/big-data-and-business-intelligence/hands-transfer-learning-pytho", "Target Audience": "Beginner", "Type": "Talks", - "author": "Pravendra Singh (~pravj)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyter-notebooks-internals-and-extension~dyz6e/", - "title": "Jupyter Notebooks: Internals and Extension" + "author": "Dipanjan Sarkar (~dipanjan)", + "created_on": "25 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-art-of-effective-visualization-of-multi-dimensional-data-a-hands-on-approach~ep6Vb/", + "title": "The art of effective visualization of multi-dimensional data - A hands-on approach" }, - "107": { - "Content URLs": "Programs in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=", - "Description": "Mention of \u201cCancer\u201d evokes words like tumor, chemotherapy, hair loss, vomiting and pain. Interestingly our knowledge and thereby cancer treatment has changed radically in the past few years and is changing rapidly every passing day. In 2003, human genome was sequenced and for the first time we could read entire human DNA from end to end. Interestingly DNA and cancer are deeply connected. Scientists deciphered that always a change in DNA (mutation) led to cancer (oncogenic mutation). Cigarette smoking, alcohol, pollution etc only led to such DNA change (oncogenic mutations). This led to numerous diagnostic companies starting to extract and sequence tumor DNA, to detect the root cause of each patient tumor. While drug companies formulated new drugs that targeted specific DNA change (mutation). These were called targeted therapies which were very different from chemotherapy in being very precise, less toxic, less side effects and they could be taken orally just like any regular pill. Thus, an oncologist (cancer doctor) could treat a cancer tumor effectively if s/he knew the precise location of mutation in the entire patient tumor DNA and the drug that targeted it. Suddenly oncologists in India and elsewhere, found themselves struggling to comprehend tumor DNA and the technology around it. Already burdened with tomes of ever changing patient treatment guidelines, now they were needed to integrate tumor DNA information to make accurate treatment decisions. For eg. NCCN (National Comprehensive Cancer Network, USA) which publishes treatment guidelines for all cancer for oncologists across the world, published lung cancer guidelines that is 271 pages long. To this, add the complex data of patient\u2019s tumor DNA, various mutation databases, clinical trials and research papers. Modern day oncologist are often overwhelmed. They need tools to simplify and hasten their decision making. I am a molecular biologist who understands the tumor DNA and the technologies around it. As Chief Scientist (molecular oncology) of Neuberg diagnostic lab, I also write patient DNA reports that guide oncologists to take treatment decisions. While meeting various oncologists and marketing them different DNA tests for different type of cancers, I got acutely aware of the problems oncologists faced. To simplify their decision making, I created algorithms that combined patient\u2019s clinical history, histo-pathology data, molecular test decisions, mutational databases and NCCN guidelines. Subsequently I coded these integrated and complex decision algorithms as Python programs that can be executed from a browser. They are available for free and oncologists are/can use it.\nPrograms in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=0 \nMy article on need of Python programing for cancer treatment: https://sites.google.com/view/molecularpathology/programming/is-it-time-for-precision-medicine-app?authuser=", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Interest in using programing to resolve healthcare problems in India", - "Section": "Others", - "Speaker Info": "I am a PhD in Biochemistry with significant research experience at the University of North Carolina at Chapel Hill, in the areas of molecular oncology, cardiovascular biology and biology of infectious diseases. Currently, I prepare molecular diagnostic reports for cancer patients as Chief Scientist (Molecular Oncology), Neuberg Center of Genomic Medicine, Ahmedabad", - "Speaker Links": " Molecular pathology of cancer: https://sites.google.com/view/molecularpathology/home?authuser=0 The DNA Labs: https://sites.google.com/site/thednalab/ , https://www.facebook.com/TheDNALab , https://www.youtube.com/channel/UCf2HKt1vgjhe8MXbvMSwELg/feed", + { + "Content URLs": "To be uploade", + "Description": "Sarcasm is an intensive, indirect and complex construct that is often intended to express contempt or ridicule. But in speech, it is multi-modal, involving tone, body language, and gestures along with linguistic artifacts used in speech. Sarcasm in the text , on the other hand, is more restrictive when it comes to such non-linguistic modalities. This makes recognizing textual sarcasm more challenging for both humans and machines. Sarcasm detection plays an indispensable role in applications like online review summarizers, dialog systems, recommendation systems and sentiment analyzer . This makes automatic detection of it an important problem. However, it has been quite difficult to solve such a problem with traditional NLP tools and techniques . So we will talk about the ongoing research and techniques developed to counter these problems. I have been trying to solve this problem for a while now so let's discuss it and hope that we solve it in the near future. Some of this techniques include tracking physiological gestures like eye tracking, extraction of psychological triggers or building a sarcasm dataset with the help of context features ", + "Last Updated": "27 Jun, 2018", + "Prerequisites": "The only thing I require from the audience is their attention and interest in this fun but a very serious problem in the world of data science", + "Section": "Data science", + "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", + "Speaker Links": "udayupreti.m", "Target Audience": "Beginner", "Type": "Talks", - "author": "siddharth srivastava (~siddharth40)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/helping-oncologists-to-take-complex-decisions-in-treating-cancer~axylb/", - "title": "Helping oncologists to take complex decisions in treating cancer." + "author": "uday1201", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sarcasm-detection-in-natural-language-processing~eXAga/", + "title": "Sarcasm Detection in Natural Language Processing" }, - "108": { - "Content URLs": "share here soon", - "Description": "Flutter is Google\u2019s mobile app SDK for crafting high-quality native interfaces on iOS and Android in record time. So lets create web services for Flutter app using python/Flask framework", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Basic of Python Knowledge of Webservices REST and JSON Hello world Knowledge of Mobile App. Familiar with Android Studio and Pycharm", - "Section": "Web development", - "Speaker Info": "I am opensource lover. I love to explore opensource technologies for mankind. I am organiser of \"Arduino and IoT ,Kanpur\" . I teach kids under coderdojo program", - "Speaker Links": " https://twitter.com/vivdroid https://github.com/vivekaris", + { + "Description": "Need to understand the customers better way based on the attitudes and then serve better and also find the algorithm by which we can classify the future customer", + "Last Updated": "27 Jun, 2018", + "Prerequisites": "Python , Jupyter notebook and some statistical conceptual understandin", + "Section": "Data science", + "Speaker Info": "A doctor in statistics from Osmania University. I have been working in the fields of data analysis and research for the last 14 years. My expertise is in data mining and machine learning \u2013 in these fields I\u2019ve also published papers. I love to play cricket and badminton", + "Speaker Links": "https://www.linkedin.com/in/statsvenu\nhttps://www.linkedin.com/in/suresh-chekuri", "Target Audience": "Intermediate", "Type": "Talks", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/write-python-web-services-for-flutter-app~avw8b/", - "title": "Write Python Web services for Flutter App" + "author": "statsvenu manneni (~statsvenu)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-customers-in-better-way-a-market-research-application-using-python~bYB2d/", + "title": "Understanding customers in better way- A Market research application using python" }, - "109": { - "Content URLs": "https://github.com/vivekaris/firebase-io", - "Description": "Now Days Internet of Things are Trending technology for every makers. Lets Build Python based Automation controller for any Hardware (tested on Raspberry Pi and Node MCU).\nWe will use firebase as a data storage and Action handling.\nWith the help of Firebase Realtime Database ,we can control hardware from any geographical location", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Keen to learn Basic of Python Knowledge of PIP Knowledge JSON Basic Knowledge of C for Arduino(Node MCU Programming) Laptop with Linux/Mac/Win 7 onwards. Node MCU v3 2 LED with 4 Jumper Wire Internet Connectivity Google Account enter code her", - "Section": "Web development", - "Speaker Info": "I am opensource tech lover", - "Speaker Links": " https://github.com/vivekaris https://twitter.com/vivdroid http://makerspacekanpur.com/blog/", + { + "Description": "Django as a web framework Django is one of the most powerful web frameworks out there! (This is definitely subjective) According to stackoverflow , python has ~10% developer base. They also predict that by 2020, the developer base would be 16-19%, if it grows at the same pace, making it the leader. Usage of python for web development has been increasing significantly. When it comes to python web framework, Django is the name that rings the bell. Will discuss about a social media processing data pipeline that can be processed using the frameworks available for python. Discuss about the pitfalls to be taken care of and advantages of using these.", + "Last Updated": "27 Jun, 2018", + "Prerequisites": " Python Basics of web development Rest APIs", + "Section": "Core python and Standard library", + "Speaker Info": "I am Rahul Reddy, graduated from IIT Varanasi, Product Lead at Setuserv informatics PVT Ltd. I lead a team building data analytics pipelines that handles more than 200-300 Million records a month. Enthusiastic about building even larger, robust, secure data pipelines", + "Speaker Links": " Stackoverflow LinkedIn", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-firebase-build-amazing-iot-application~erp2b/", - "title": "\"Python and Firebase\" Build Amazing IoT Application" - }, - "110": { - "Content URLs": "Kubernetes Docker Azure Kubernetes Service aka AK", - "Description": "Kubernetes is considered as the new Kernel of the Cloud. It's a distributed computing platform letting users not have to care about infra and helping them concentrate mainly on business logic. By having your web app deployed on a kubernetes cluster you can make sure your app is highly available, and can fail-over when there's a problem. One of the main goals of the Kubernetes project is to democratize distributed computing. With Kubernetes being open source, Companies do not have to redo the mundane task of writing a distributed computing platform to achieve high availability, automated deployment, scaling and management of your applications. Kuberentes will take care of that for you. Kubernetes is also considered as a container orchestrator, as it manages containers to achieve the above said goals. In this talk: We will first write a basic python web app. Next, We will go through what a container is Containers are becoming the de-facto way of deploying applications as they remove the complexities of dependency management,etc. Running apps on Individual Containers provide the isolation almost to that of a Virtual Machine without having the overhead of having individual Kernels as they all share the host kernel. Isolation is provided by using kernel level features like cgroups and namespaces. We will containerize the application using docker and push it to a Container Registry. Once we have the image deployed to a registry, this image will be used to create instances i.e containers of the web app. We will next create a kubernetes cluster on Azure, all along going through what a Kubernetes cluster is, and its components. We will then deploy our python web app onto the cluster. Now As we have our python web app up and running, We can then do some experiments on how Kubernetes self-heals the application when a node goes down,etc. After that I will run down some points on where Kubernetes is being\n used, its impact. To Finally answer the question, Is Containers and Kubernetes worth all the Hype ? This talk will be demo focused, But before going to a demo we will have some slides explaining the overview of the components and how they work. By the end of the talk, Audience will have a brief overview of what containers and kubernetes are, and how to deploy a web app on Kubernetes. From this overview, Audience can start digging deeper online and know more", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Understanding of Python. Basic Understanding of Deployment of a web app. It's good if you already have some basic understanding on what containers and kubernetes are", - "Section": "Developer tools and Automation", - "Speaker Info": "Tarun Pothulapati is currently pursuing his B.Tech in Computer Science and Engineering in Hyderabad.\nHe is a Tech Enthusiast and codes mostly in Python and C#. He is very much interested in distributed computing platforms like Kubernetes and Microsoft's Service Fabric which are trying to democratize \nthe technology which was before only a privilege of the Big-Tech firms.\nHe spends most of the time learning about it and trying to contribute to their repositories. He is also very enthusiastic about sharing the knowledge about these cutting edge technologies.\nTarun has also worked on many projects on chatbots, Web apps etc and have won some\nhackathons held by IEEE, IBM & Amazon and he was one of India's 40 finalists of AICTE's \nStartup Contest 2017", - "Speaker Links": "Twitter Github Linkedin Websit", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Tarun Pothulapati (~Pothulapati)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deploying-a-python-web-app-onto-a-kubernetes-cluster~bqo7e/", - "title": "Deploying a Python web app onto a Kubernetes Cluster" - }, - "111": { - "Content URLs": "---In progress, will be ready to share by July last week can make it to July first week if urgent--", - "Description": "Signal processing is a fundamental part of ECE and is also used in many other fields. Students for years have been using expensive Matlab for learning this skill. The talk/workshop/interactive session can be used by students to get a better understanding of signal processing and implementing it with python. The use of python language in signal processing is preferred as it is portable, easily available and fast to deploy Topics covered include but are not limited to Sound and Signals Noise Fourier Transform Filtering Modulation Sampling LTI Systems The talk will be at a simple level so that even a high school student can understand signal processing and implement it. If time allows another session on using python to solve electrical networks and visualizing them can also be implemented", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic knowledge of python and Signals and systems (WikiPedia knowledge is enough.) NumPy (Used for array manipulation ) SciPy (For computation) matplotlib (For plotting various signals etc.)", - "Section": "Others", - "Speaker Info": " Speaker is a 3rd year ECE student with experience in python for numerical computations, web development and most importantly signal processing , and electrical networks Interested in using python in modern electronics like the pyboard and raspberry pi and advocates the use of python over expensive software. An avid python user, always tries to find a way to implement given task in python and believes that where there is a task to be done there is a suitable python library.", - "Speaker Links": "LinkedIn Faceboo", - "Target Audience": "Beginner", "Type": "Talks", - "author": "Abel Joseph John (~abel91)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/digital-signal-processing-with-python-and-applications-in-audio~epnQb/", - "title": "Digital Signal Processing with Python and Applications in Audio" + "author": "rahul reddy (~rahul01)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-chained-from-personal-interactive-websites-to-complex-data-pipelines~eZD5b/", + "title": "Django Chained - From personal interactive websites to complex data pipelines" }, - "112": { - "Content URLs": "https://www.py4e.com/\nhttps://www.coursera.org/specializations/pytho", - "Description": "This session will take a look at the \u201cPython for Everybody\u201d series of courses on the Coursera platform. This course has impacted over 1.3 million students over the last five years. We will look a the history and goals of the course and how the course works to create a learning community. We will show how the free open educational resources (OERs) and book associated with the course have been used by teachers, students, and courses around the world to form a network of educational activities centered around Python. We will also cover briefly the Tsugi (www.tsugi.org) software that is used to build the learning assessments and distribute the OER materials in a way that enables maximum reusability of the materials for other teachers", - "Last Updated": "31 May, 2018", - "Prerequisites": "No pre-requisite", - "Section": "Core python and Standard library", - "Speaker Info": "http://www.dr-chuck.com/\nhttps://www.si.umich.edu/people/charles-severance\nhttps://twitter.com/drchuck/\nhttps://github.com/csev\nhttps://www.sakaiproject.org\nhttps://www.tsugi.org\nhttps://www.slideshare.net/cse", - "Speaker Links": "http://www.dr-chuck.com/dr-chuck/resume/index.htm Charles is a Clinical Professor and teaches in the School of Information at the University of Michigan. He is the Chair of the Sakai Project Magament Committee (PMC). Previously he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project and worked with the IMS Global Learning Consortium promoting and developing standards for teaching and learning technology. Charles teaches ten popular MOOCs and two specializations to students worldwide on the Coursera platform: Internet History, Technology, and Security, Web Applications for Everybody, and Python for Everybody and is a long-time advocate of open educational resources to empower teachers. Charles was the editor of the Computing Conversations column in IEEE Computer magazine from 2011-2017 that features a monthly article and video interview of a computing pioneer. Charles is the author of several books including: Python for Everybody, Sakai: Building an Open Source Community\", \"Using Google App Engine\", from O'Reilly and Associates and the O'Reilly book titled, \"High Performance Computing\". Charles has a background in standards including serving as the vice-chair for the IEEE Posix P1003 standards effort and edited the Standards Column in IEEE Computer Magazine from 1995-1999. Charles is active in media as a hobby, he has co-hosted several television shows including \"Nothin but Net\" produced by MediaOne and a nationally televised program about the Internet called \"Internet:TCI\". Charles appeared for over 10 years as an expert on Internet and Technology as a co-host of a live call-in radio program on the local Public Radio affiliate (www.wkar.org). Chuck's hobbies include off-road motorcycle riding, karaoke and playing hockey. Charles has a B.S., M.S., and Ph.D. in Computer Science from Michigan State University", + { + "Description": "root@pycon2018:~# python zer0-day_exploit.py [+] Checking for vulnerability.... [+] Triggering BoF.... [+] Sending staged payload... [+] Waiting for server response... <=HeLL0 fri3nd=> Do you want to know how hackers use Python for development of their hacking tools and arsenal? Have you ever thought how hackers compromise vulnerable computers around the globe with the power of automation that comes with python? If you are looking for answers to these quentions then you have come to right place... In this talk, I will demonstrate various use cases of python programming in hacking and cybersecurity. We will go through various python libraries such as Sockets, Httplib2, Scapy, Shodan etc. In the beginning, we will see the various Python implementations to perform computer networks auditing and attacks such as port scanning, ARP spoofing, DoS attack and remote code execution with buffer overflow vulnerability. Shodan is the search engine for computers and IoT devices connected to the internet around the globe and has API wrapper as a python library. With shodan, I will demonstrate how we can look up for IoT devices. We will see python script in action using shodan to find MQTT brokers to extract GPS information out of them via CVE-2017-7650 vulnerability and due to poor access control list configuration in them", + "Last Updated": "27 Jun, 2018", + "Prerequisites": " Python programming Basics of computer networking", + "Section": "Networking and Security", + "Speaker Info": "I am Chirag Jariwala ( @CJHackerz ), B.Tech (4th year) Information Technology student from SRM Institute of Science and Technology - Chennai. I am independent cybersecurity analyst and researcher and have been self-learner in this space quite for a while. I use lots of python scripting in my hacking adventures. I have done numerous workshops and training to teach people about ethical hacking and penetration testing inside my university campus. Have been active community member and given few talks at Null Chennai Chapter (an open source cyber security community which hosts meets for OWASP)", + "Speaker Links": " GitHub: https://github.com/CJHackerz Twitter: https://twitter.com/cjhackerz LinkedIn: https://www.linkedin.com/in/cjhackerz/ Null community profile: https://null.co.in/profile/8808-script-alert-chirag-jariwala-script", "Target Audience": "Beginner", "Type": "Talks", - "author": "Charles Severance (~charles)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/inside-the-worlds-largest-python-course-on-coursera~bomYe/", - "title": "Inside the World's Largest Python Course on Coursera" - }, - "113": { - "Content URLs": "Slides: https://docs.google.com/presentation/d/1z-pWhSOERi-vl_wPLVsdCNpl54G3IA0D8K7ve13HFZI/htmlpresent Source code for the examples: https://github.com/minhajuddin/collaborative-canvas-demo", - "Description": "Outline/structure of the Session\n1. An introduction to Elixir\n2. An introduction to Phoenix\n3. Outline and design overview of our canvas app\n4. Implementing our app\n5. Deploying it to a server\n6. Q&A Learning Outcome\nLearn how easy it is to use Elixir and Phoenix to create real time applications at a massive scale", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic understanding of the web applications", - "Section": "Web development", - "Speaker Info": "I am a very passionate programmer. I am also the CEO of a Micro ISV, Cosmicvent Software. I have been in the software industry for 10 years.I love writing code and have worked with Elixir, Golang, Ruby, .NET and Javascript among other technologies", - "Speaker Links": "Follow me on twitter https://twitter.com/minhajuddin Follow me on GitHub https://github.com/minhajuddin/ My Blog: https://minhajuddin.com/ Previous presentation: https://www.youtube.com/watch?v=WabGxSZhPE", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Khaja Minhajuddin (~minhajuddin)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-collaborative-canvas-using-elixir-and-phoenix~enl5b/", - "title": "Building a collaborative canvas using Elixir and Phoenix" + "author": "Chirag Jariwala (~chirag18)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/journey-into-the-world-of-hacking-and-cyber-security-with-python-programming~e1zma/", + "title": "Journey into the world of hacking and cyber security with Python programming" }, - "114": { - "Content URLs": " Postman Jmeter Burp", - "Description": "API testing is fun! For a small team of 7 (Dev + QA), having dedicated resources to do functional, Security and Performance of the APIs is close to impossible.\nHence, We came up with a framework which automates the process of API testing covering the basic functionality, Security, and Performance so that we don't miss out testing any of these layers. I would cover up the basics of Postman, Burp and JMeter components used for the framework", - "Last Updated": "31 May, 2018", - "Prerequisites": " Interest in automating the Webservices testing :)", - "Section": "Developer tools and Automation", - "Speaker Info": "A tech enthusiast who has 7+ years of experience in the Software Testing in Startups. I love to explore new technologies and automate mostly everything which takes more time. A strong believer in processes. Love testing Webservices. Would love to share the experience we had in building the framework for API testing", - "Speaker Links": "https://www.linkedin.com/in/sarala-v-620b0b1a/ https://twitter.com/saralaVeerann", + { + "Description": "About a month ago my inbox was flooded with emails beginning with We have decided to update our Terms and Conditions... . Though I am a technical person working in a financial services company and thus terms and conditions are supposed to be my cup of tea, I couldn't get myself to go through any of the actual Terms and Conditions . A python based Natural Language Processing Engine to summarize the often twisted contents of a legal agreement and defining the pros and cons for the agreement in question for the user would better equip an user to understand what exactly they are agreeing to. This is very important in today's age where we've seen our personal data being breached for the benefit of social media based companies who then sell this data to achieve gains that could be political too. In the financial and legal world such documents are of utmost importance. The process of developing a solution like this would be about defining the Gives and Takes of an agreement. Every agreement consists primarily of the things that a user is expected to receive from the other party/user and vice versa. The next step would be quantifying that particular give or take. This would give the user an estimate of what he/she would be expected to give/spend. Comparing that with the takes would help the user make a decision as to whether to agree with the terms and conditions or not. The quantifying system could consist of a number of attributes and the \"twisted ones\" or the ones affecting the user's privacy or other sensitive aspects cold be flagged appropriately so that the user can review and choose. This talk would talk about the steps, right from defining legal contexts to setting up the words, phrases and understandings for typically legal content", + "Last Updated": "27 Jun, 2018", + "Prerequisites": "Anyone who'd want to see themselves make better decisions and understand how agreeing to certain Terms and Conditions could affect their lives and their privacy", + "Section": "Data science", + "Speaker Info": "Aroma is a graduate fresh out of the National Institute of Technology, Warangal. As a techno-activist she has been a part of many projects that promote diversity and inclusion. She believes that Automation is the path to Inclusion. In 2016, a teammate of her \"Shoes for the Visually Impaired\" project presented it at the FOSSASIA. She reads, writes and enjoys walking to explore places. She presently works in a financial services firm and believes that solving problems that she has would solve problems for a large chunk of the world. An ML enthusiast she has about 20+ Coursera Certifications with the respective project work to support her learning in that field. Python is one of her favorite languages and hackathons her favorite party", + "Speaker Links": "Aroma Rodrigue", "Target Audience": "Beginner", "Type": "Talks", - "author": "Sarala V (~sarala)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-rest-api-testing-for-functional-security-and-performance-testing~bmkRe/", - "title": "Automating REST API testing for functional, security and performance testing" - }, - "115": { - "Content URLs": "https://github.com/radhikascs/cryptography-pytho", - "Description": "This talk is meant for the end users who aspire to learn basics of cryptography and its implementation in real world projects. \nThis tutorial is also useful for networking professionals as well as hackers who want to implement new frameworks instead of following traditional approach", - "Last Updated": "31 May, 2018", - "Prerequisites": "It is expected that the end user should know basics of cryptography and algorithms. The knowledge of cryptography algorithms becomes a cakewalk for a user who reads this tutorial", - "Section": "Core python and Standard library", - "Speaker Info": "A pinch of optimism with a blend of hard work and focus defines Radhika Subramanian. She works as an Academic Writer and Tutor with various organizations. She has completed MSc(CA) from Symbiosis International University. She also includes a passion for research work in Artificial Neural networks and it's technologies. She is currently working as an Author with BPB Publications and Apress Media LLC", - "Speaker Links": "https://www.linkedin.com/in/radhika-subramanian-486a771a/ https://www.unanth.com/tutor/radhika-subramanian-14135", + "author": "ARodz (~AromaR)", + "created_on": "27 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-nlp-to-demystify-terms-and-conditions-and-summarize-the-contents~b2Aza/", + "title": "Using NLP to demystify \"Terms and Conditions\" and summarize the contents" + }, + { + "Content URLs": "Slides Talk Specific Slides On Their Way References QN-S3VM Python Package: http://www.fabiangieseke.de/index.php/code/qns3vm Semisupervised Learn Python Package: https://github.com/tmadl/semisup-learn S3VM Seminal Work: https://papers.nips.cc/paper/1582-semi-supervised-support-vector-machines.pdf", + "Description": "Machine Intelligence algorithms, in their application to real world problems, are largely models trained in a supervised manner. Hence, they are hindered by the reality that in most practical situations unlabelled data is easier to come across and obtaining appropriately annotated and labelled data may be prohibitively expensive. Herein lies the appeal of semi-supervised learning algorithms that allow us to draw inferences with only a few labelled data samples existing among a vast amount of unlabelled data. In this talk. through the application of a variation of the tried and tested SVM, called the S3VM(Semi Supervised SVM) on standard dense and sparse data sets, we will explore the merits and demerits of semi-supervised learning. We will also take a cursory look at a few approaches used to solve the modified optimisation problem that arises when we adapt the SVM for use in a semi-supervised setting. The outline of the talk will broadly be the following: Why Semi-Supervised Learning Advantages of using Semi-Supervised algorithms rather than Supervised algorithms on limited data Approaches to Semi-Supervised Learning: Transduction vs Induction+Deduction Modifying the SVM for Semi-Supervised Learning Approaches for solving the modified SVM: Label-switching vs deterministic annealing Semi-Supervised Learning is not a silver bullet: Discussion of disadvantages", + "Last Updated": "28 Jun, 2018", + "Prerequisites": " Familiarity with Python Programming Minimal proficiency in Optimisation Methods Intermediate proficiency in Support Vector Machines", + "Section": "Data science", + "Speaker Info": "I'm Indraneil Paul, a final year Computer Science student at IIIT Hyderabad. I have been involved in machine learning, computer vision and mathematical optimisation for the best part of the past three years due to my research work. I was previously working in the Computer Vision lab on an autonomous driving project and am currently working on applying graph based machine learning models to social networks. I was also a Google Summer of Code '17 student under electric vehicle startup Green Navigation (now nav-e). I occasionally foray into experimentation with Blockchain technology with Hyperledger", + "Speaker Links": "Github: https://github.com/iNeil7", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Radhika Subramanian (~radhika14)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cryptography-and-python~elkjd/", - "title": "Cryptography and Python" + "author": "iNeil77", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/semi-supervised-learning-with-svms-in-python~e3pRa/", + "title": "Semi Supervised Learning with SVM's in Python" }, - "116": { - "Content URLs": "To get a feel of Numba see - first step", - "Description": "Thinking parallel is an art, applying it is another. While applying it, the first hurdle for us is to move to another language like C or C++ to get performance gains. \nWhat if we write simple python code and someone magically helps us gain C like performance? Sounds like a dream, it ain't ! . Enter Numba :) In this workshop you will - Witness how Numba help you get insane performance gains to your code without changing a line of it. Learn to harness the power of your GPU/CPU for performing math intensive computations. See how it compares to other libraries like Numpy , etc. and how they can complement it. Use Numba to parallelize the very famous Particle Swarm Optimization Algorithm Flow of the workshop - Where to use Numba in your code - (time profiling, small examples) The wow of Numba in my life, a small example of how it helped in my research Introduction to jit complier, internals of Numba Introduction to the Particle Swarm Optimization (this is where the fun starts :) ) Code up basic PSO Profile PSO to find pain areas Try to speed up the pain areas using Numba Kick up a hierarchical swarm (just for fun, if time permits) QA Session", - "Last Updated": "31 May, 2018", - "Prerequisites": "numpy, matplotlib, jupyter, ipython, numba, line_profiler , llvmlite. A more specific description is available her", - "Section": "Others", - "Speaker Info": "Hi, I am Shubham Bhardwaj. I am currently a Research Intern at Jio CoE for AI/ML and a final year undergrad at VIT University, Vellore. I am a die-hard pythonista. \nMy daily work involves developing and implementing algorithms for interesting problems in AI. Apart from this I am also an organizer at GDGVIT, I love dev :) and contribute to various open source organisations, organise workshops, promote python whenever I can", - "Speaker Links": " LinkedIn Github", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Shubham Bhardwaj (~shubham0704)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/leveraging-the-power-of-your-gpucpu-for-math-intensive-computations-with-python~bkjJa/", - "title": "Leveraging the power of your GPU/CPU for math intensive computations with python" + { + "Content URLs": "Talk specific slides will be updated soon. References: https://docs.python.org/3/library/unittest.mock.html https://docs.python.org/3/library/unittest.mock-examples.htm", + "Description": "Testing is one of the cornerstones of good software engineering. It addition to help ensure that your code works as expected, it also has the advantage of iterating over your code faster. With sufficient tests, you can be pretty sure that your new code doesn't break any old ones. One of the biggest issue I find with writing tests is that there is a lot of boilerplate code that needs to be written to get even the basic unittests to work. This talk will focus on mock and patch . These are awesome utilities provided with unittest module to make your testing life much more painless but not a lot of people know about them. The flow of the talk will be as follows: Intro to testing: Why do we actually need testing? The basic problem I find with testing: Boilerplate code. (with examples) Introduction to MagicMock and patch . Applying them to real tests. Enhancing those tests: Assertions on mock. Caveats associated with their use.", + "Last Updated": "28 Jun, 2018", + "Prerequisites": "Some basic knowledge about unit testing in Python would be great", + "Section": "Developer tools and Automation", + "Speaker Info": "I am a student at IIIT-Hyderabad on the verge of completing my M.S.\nFor the last two years, I have also been working part-time as a sysadmin for all institute servers and was involved in maintaining services like proxy, directory and the mail server. I have previously interned as a Production Engineer for Facebook and am currently a Google Summer of Code intern with CCExtractor", + "Speaker Links": "Github LinkedIn Blo", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Aaditya M Nair (~AadityaNair)", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/supercharge-testing-by-mocking~b4qxd/", + "title": "Supercharge Testing by Mocking" }, - "117": { - "Content URLs": "The Magenta Project Music Composition using Recurrent Neural Network", - "Description": "Music is mainly an artistic act of inspired creation and is unlike some of the traditional math problems. But, a sequence of specific chords and notes can be observed when we listen to music. With the recent advancements of the AI tech, sequence models are used invariably in innumerous fields, one such sequence model, LSTM( Long Short Term Memory Networks) can be used to generate melodies and beats. So, this talk is about how deep learning models, specifically LSTMs were used to produce music - catering particularly to the Electronic Dance Music Industry. CONTENTS AND ORDER OF THE TALK Learning how LSTMs help in generating music, and the concepts behind it. Preprocessing the MIDI data for the melodies and beats using MIDI packages created by the Python community. Building the LSTM network using Keras with Tensorflow as backend and understanding it. Train the network with the melodical data to create the LSTM network for melodies and same thing for beats. Generating melodies and beats(using pretrained model) and combining the two to create different type of genres of music. I am including a piece of music generated by an MIT alumnus, but I will be explaining the steps from scratch . Generated Techno Beat", - "Last Updated": "30 May, 2018", - "Prerequisites": "Tensorflow, Keras, Recurrent Networks and a Good taste in music ;", + { + "Description": "Less technical people are often afraid of terminal and command line utilities, but are happy to enter the same data on a website. What if Jupyter Notebook could provide cheap, human-friendly UIs for everyone? Less technical people are happy to interact with graphs and tables, but even with Jupyter Notebook, they are anxious to run cells. What would a permissioned nbviewer look like for enterprise? The goal of this talk is to get you thinking about how to use Jupyter to enable rapid-development and low-cost solutions to empower those without technical know-how in constrained environments", + "Last Updated": "28 Jun, 2018", + "Prerequisites": "Familiarly with Jupyter Noteboo", "Section": "Others", - "Speaker Info": "I am Kumar Abhijeet, a sophomore from RV College of Engineering, Bengaluru and an AI enthusiast. I am a budding EDM producer and a python programmer as well(no doubt in that). I have worked with small AI startups in building their frameworks. I am an open source contributor and a GSOC aspirant. I have always loved the idea of mixing technology with regular phenomena, which I will be doing with music. I love going to meetups and meet different kinds of communities to learn from them", - "Speaker Links": "LinkedIn ID Github Lin", + "Speaker Info": "I am a developer for the JavaScript team at the D. E. Shaw group. One of our core principles is that users come first; we are hyper focused on improving the user experience for developers, technical users, and non-technical users of everything from intranet sites to the interactive python environment. We aim to delight", "Target Audience": "Beginner", "Type": "Talks", - "author": "Kumar Abhijeet (~kumar80)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-beats-and-melodies-with-lstms-using-python-and-tensorflow~ejgya/", - "title": "Generating beats and melodies with LSTMs using Python and Tensorflow" + "author": "Marc Udoff (~mlucool)", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/empowering-the-less-technical~e5r8a/", + "title": "Empowering the Less Technical" }, - "118": { - "Content URLs": " https://www.djangoproject.com/ http://www.celeryproject.org/ https://sensu.io/", - "Description": "Monitoring is a key aspect for any business. It enables us to find and be notified about the problem way ahead our customer notices it, which enables us to keep our businesses running and making customers happy. I will be talking about how we SREs at Opentable Inc, tries to solve the good old monitoring problem, sensu with puppet, using Django, Sensu and Celery. If you are fed up with the limitations of what current monitoring tools offer, this is the talk you wanna look out. At the end of talk, audience would have an alternative approach for monitoring using python. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce monitoring and how we use currently at Opentable Inc. Describe limitations we have with our previous monitoring stack. Alternate new generation monitoring architecture using python tools Django and Celery, keeping sensu intact. How we developed a site using Django, which help us to maintain the checks and add new check definition. How we used Celery distribution system to run checks on multiple worker nodes and send results to sensu. I will talk about how we scaled celery worker nodes by setting up different queues, and prioritising the tasks and by using Flower.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic knowledge of Sensu. Basic knowledge of Django and Celery. Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", + { + "Description": "Nearest Neighbour(NN) algorithm, which is a lazy and a non-parametric method used for classification is one of the most intuitive and widely used machine learning algorithms. It is most often sought by business consultants for its simple and easy to understand framework. The performance of the algorithm can be enhanced by optimally tuning its hyper-parameters, which includes the k-value and the distance metric. However, practitioners tend to focus only on optimising k and ignores the other. The very term \"nearest-neighbour\" means that we employ some notion of near, i.e. we use some distance metric to quantify similarity and thus define neighbours. This emphasises the importance of the Distance Metric in the NN algorithm. In this talk, we present some of the novel approaches used, to learn the distance metric from the training data. Also, we demonstrate how slight amendments to the approach can lead to an inception of a dimensionality reduction technique. The above mentioned approaches are bundled together as a python package and is showcased to the audience. Structure of the Talk: 1. An overview of K-NN algorithm\n2. Theory of Distance metrics\n 2.1 Mathematical definition of a metric\n 2.2 Some common distance metrics\n3. Deep dive into Metric Learning techniques\n 3.1 Why is it important?\n 3.2 The math behind metric learning \n 3.3 Application in Dimensionality Reduction\n4. Implementation using some popular dataset", + "Last Updated": "28 Jun, 2018", + "Prerequisites": "Basic programming skills in python, machine learning(familiarity with common classification and dimensionality reduction techniques) and linear algebra", + "Section": "Data science", + "Speaker Info": "Kousik is pursuing his undergraduate studies at Chennai Mathematical Institute and shows immense interest in Machine Learning and Finance. He has contributed to multiple open source projects and has interned with the research and development teams of various organisations. His primary research interests include computer vision, graph based machine learning algorithms and quantitative finance. He has also involved in different technical talks at IIT-M and is one of the members of the Chennai Python Meetup group", "Target Audience": "Intermediate", "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-infrastructure-and-application-using-django-sensu-and-celery~e0o5d/", - "title": "Monitoring infrastructure and application using Django, Sensu and Celery." + "author": "Kousik Krishnan (~kousik)", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/comprehensive-study-of-distance-metric-learning-in-nearest-neighbor-algorithm~e7w1e/", + "title": "Comprehensive Study of Distance Metric Learning in Nearest Neighbor Algorithm" }, - "119": { - "Content URLs": " https://github.com/errbotio/errbot http://errbot.io/en/latest/", - "Description": "The wikipedia definition of ChatOps is, a collaborative, conversation-centric way of working that brings people, discussions, bots, tools and files together in one central location: the workplace messaging app. That's it! That's what exactly I am gonna talk about. I am gonna talk about Chatops bot, Errbot which is written in python and can be used across various messaging apps like Hipchat, Slack, telegram, skype, etc. Using chatops one can automate the tedious, boring tasks and let the bot do the work for you. It also enables various engineering teams to collaborate and exchange information easily at one place: their official messaging app. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce chatops - culture, uses, possibilities. I will talk about the possible scenarios where we could use chatops in our daily tasks. I will then introduce Errbot and its plugin architecture. Tell audience about various features of errbot and its builtin plugins. Demonstrate errbot to audience by creating a command and using it in Slack. How to set up a alternate storage for errbot. I will conclude the talk explaining the ACLs(Access control List) in errbot.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic Python Passion for automation Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", + { + "Content URLs": "This GitHub repo links to any content relevant to the talk", + "Description": "This talk intends to provide a fairly gentle introduction to the fundamental ideas behind quantum computing and the concepts of quantum physics that allow quantum computing to surpass the limits of classical computing. We then proceed to a quick demo of using the QISKit Python SDK provided by the IBM Q team to run experiments on a simulated (or real) quantum computer", + "Last Updated": "28 Jun, 2018", + "Prerequisites": "This talk touches upon a topic that doesn't have any hard and fast prerequisites (apart from Python syntax, of course), but basic knowledge of the following topics will make things easier to grasp during the talk and later down the line: Some idea of what quantum physics is The concept of a quantum superposition of states Familiarity with linear algebra (not really for the talk, but will help later down the line)", + "Section": "Others", + "Speaker Info": "I'm a full-stack JS developer, Python enthusiast and Rust lover who revels in learning new technologies. I enjoy sharing my knowledge and the company of witty people", + "Speaker Links": " GitHub LinkedIn My Tech Blog on Medium", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Ajmal Siddiqui (~ajmalsiddiqui)", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-quantum-computing-with-the-qiskit-sdk~e9yDe/", + "title": "Introduction to Quantum Computing with the QISKit SDK" + }, + { + "Content URLs": "Will share slides link soon.. Key Takeaways from the talk: Why we decided to build our own machine learning platfrom from scratch How to build machine learning platform using python Lessons Learned while building machine learning services How to extend this platform by distributed computation engine like Spark and deep learning platform like tensorflow", + "Description": "Abstract The purpose of this talk is to describe how helpshift has leveraged python ecosystem to build a machine learning platform without using any third party framework, and how you can build one too. In particular, You can learn how to build the following components of machine learning platform using python from this talk. How we use python celery framework to distribute model building tasks\n to celery workers How models heavier in size can be served to prediction node in real time How to monitor model building tasks on celery worker Python data science stack in Helpshift - Numpy, Scipy, Scikit-learn, etc Python libraries/framework used - Celery, S3/Azure Storage, Bottle, etc Description Helpshift provides customer service platform to around 2000+ companies across various business domains like gaming, e-commerce, IoT, banking, entertainment, travel, hospitality, productivity apps and many more. Helpshift provides a suite of ML features that include auto ticket classification, FAQ suggestions to user query and other features. As each company using our platform has a different business domain, we build separate ML models for each of our customer and for each of feature. To handle thousands of models and CRUD operations on them in production, we needed highly scalable and reliable machine learning platform for model building and serving models. Possible solution was to use Spark or Tensorflow for model building. But these frameworks did not provide facility to store thousands of models, and serve those for prediction in production. We decided to use celery framework for distributing model building tasks to celery workers and use core python data science libraries to build models. Model building using celery worker Each Celery worker in ML platform is registered to one or more model building queues. Each type of task is associated with one celery queue. In real time, the backend server submits model building task to pre-defined celery queue. One of available celery worker picks the pending task, builds the model and pushes it to blob storage like s3/azure with new model version. Model management in s3/azure We have written python wrapper around s3/azure client library to provide all required CRUD operation on models in s3. CRUD operations are simple operations like get_model, put_model, update_model with some version. Serving models to prediction Nodes Model size ranges from 5 - 25 mb. To do predictions within 30 ms, we have to either load all models in memory or store them on local disk of each prediction nodes. We decided to store all the models on local disk as loading them in memory was not a scalable approach. The challenge here is, whenever a particular model is updated, it has to be copied on each prediction node. A python service on the prediction node takes care of syncing updated model from s3 to local disk. Prediction service Prediction service is gunicorn server which fetches model from local disk and does prediction on incoming requests. Monitoring model building task running on celery worker As there are always some jobs in celery queue waiting for celery worker, we built active monitoring service which tracks the status of each submitted task. Monitoring service decodes metrics from celery worker to find failure of task and time spent by each task in waiting/running state. For any task that crosses the threshold time for wait or run state, an alert is sent", + "Last Updated": "28 Jun, 2018", + "Prerequisites": " Basic knowledge of Python ecosystem Interested in building scalable machine learning platform", + "Section": "Data science", + "Speaker Info": "Hello, I am shyam shinde , actively developing machine learning platform at helpshift . I have diverse experience in developing backend systems, designing and developing system to handle big data. Developed production systems using Java, Clojure and Python. Currently, interested in deploying machine learning services at scale. As side projects, I learn machine learning concepts and try to implement them. Apart from that, I like trekking, reading books and watching movies", + "Speaker Links": "GitHub LinkedI", "Target Audience": "Intermediate", "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatops-using-python-bringing-developers-and-operations-together-making-tasks-easier~e9AJe/", - "title": "Chatops using Python - Bringing developers and operations together, making tasks easier!" + "author": "Shyam Shinde (~shyam91)", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-helpshift-built-machine-learning-platform-using-python-at-large-scale~e0mLa/", + "title": "How Helpshift built machine learning platform using Python at large scale" }, - "120": { - "Content URLs": "https://github.com/aj-jeste", - "Description": "Google Cloud Platform Deployment Manager (GCP DM) allows you to codify your infrastructure with minimal setup, just need to download the gcloud library and you're off to the races. While its simple to get started with GCP DM, its a whole 'nother ball game to write extensible and reusable DM code. In this talk I will show you how to scaffold your code into two distinct groups: configs and templates. By separating these out you can reuse the same templates across multiple deployments with different configs and make your codebase a little bit smaller. How to write a basic DM deployment. Convert the basic DM deployment into a template. Launch multiple deployments with different configs but same template. Create custom helper functions in DM Best practices when using DM", - "Last Updated": "30 May, 2018", - "Prerequisites": "Understanding of Google Cloud Platfor", + { + "Description": "SQL is a powerful tool. It is the simplest way to analyse a dataset. In recent times however unstructured data has started to get a lot of mileage. A lot of effort is spent in converting this to structured data. Some Statistics 80% of the data is unstructured As more people go online, it will lead to generation of more unstructured data. Currently the count sit at 3 billion people, so there is a lot of capacity for data overload in the coming days SQL is the world's easiest and most used programming language. The reason it is most used is because of its simplicity and power What I want to propose is a tool that will help analysts directly use SQL on text data. This will be more than just applying NLTK functions on the SQL text. It will involve the following components Data Structures ( similar to RDBMS etc) Parsing Ability to join etc Advantages The entire world of text data will be open for people with basic SQL skills to analyse. This will not just help in more productivity but help in seamless integration of business and technology Cross functional text data can be analysed easily Injection of populated knowledge graphs etc will ensure that new information gets added easily SQL will help reporting/logic storage very easy", + "Last Updated": "28 Jun, 2018", + "Prerequisites": " Python Jupyter SQL", "Section": "Developer tools and Automation", - "Speaker Info": "As a freelance Site Reliability Engineer and Cloud Architect, AJ has traveled all over the world helping startups setup and manage Cloud infrastructure. He has also architected and deployed large Hybrid on-prem/cloud infrastructure for existing well established companies that wanted a taste of the cloud but needed to keep their physical data-centers as well. This is his 11th year as a SRE/CA and has automated, scaled and monitored infrastructure anywhere from 150 to 3500+ nodes, both physical and virtual. Currently he is looking for his next challenge, perhaps its this pycon talk. Brought up and currently lives in New York City but travels all over the world in search of the best train journeys and awesome foods which seems to bring him back to India again and again", - "Target Audience": "Beginner", + "Speaker Info": "I am a data scientist at Morgan Stanley. I have been working in the analytics domain for the past 7 years\nI love applied machine learning and have been working in this capacity for the past 3 years", + "Speaker Links": "https://github.com/anantguptadbl https://www.recommendbot.in https://www.linkedin.com/in/guptaanant/ https://www.simplyanant.blogspot.co", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "aj", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-cloud-platform-deployment-manager-scaffolding~b8zje/", - "title": "Google Cloud Platform Deployment Manager Scaffolding" + "author": "Anant Gupta (~anant79)", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sql-on-text~egGke/", + "title": "SQL on Text" }, - "121": { - "Content URLs": "I will share the slides after my talk as a Github repository", - "Description": "If you are working in the field of research than you might be wondering about symbolic solutions which must be needed while working in such arduous fields like Mechanical Engineering or Computer Science or Quantum Mechanics. Sympy is the solution for that. Sympy deals with the computation of mathematical objects symbolically. This means that the mathematical objects are represented exactly, not approximately, and mathematical expressions with unevaluated variables are left in symbolic form. This talk will cover Introduction and Uses of Sympy Library", - "Last Updated": "30 May, 2018", - "Prerequisites": "Basics of Python is good. \nDon't know Python? It's still okay. You will definitely find something new", + { + "Content URLs": "Slides will be uploaded soon", + "Description": "Almost all of us have used VLC, simply because it's so good at what it does. Reads multiple file formats, transcodes videos, makes basic filtering (brightness correction,etc) effortless, and so on. VLC uses libavcodec in the backend, which is just a way for it to access FFmpeg 's api. But have you ever wondered what makes VLC (via ffmpeg) so efficient? At this talk, we will take a look at what it takes to build a video transcoder in python as efficiently as FFmpeg . It will cover Basics of computer vision - What are images and videos really, how they are stored and managed How to handle videos in python using OpenCV, an open source computer vision library Basics of concurrency and parallelism in Python How to use parallelism effectively to handle videos", + "Last Updated": "29 Jun, 2018", + "Prerequisites": " Basic understanding of OpenCV and threads is preferable Working knowledge of Python", "Section": "Core python and Standard library", - "Speaker Info": "Nikunj Parmar is a Sophomore year student at Nirma University. His major field is Flexible Robotics. He has been working with Python for last 2 Years as a Researcher. As a Junior Undergraduate student, He has worked on many projects focused on Robotics, Machine Learning, and Core OS Programming. His interests lie in the fields of Robotics, Design and Control Engineering, Computational Engineering, and its applications in a broad range of circumstances", - "Speaker Links": "https://www.linkedin.com/in/nikunj-parmar-b87739138/ https://github.com/nikunjparmar82", + "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", + "Speaker Links": "R S Nikhil Krishna Personal Website Github Linkedin StackOverflow Lokesh Kumar T Github Linkedin StackOverflow", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-to-beat-vlc-and-ffmpeg-at-video-operations~ejkva/", + "title": "Using Python to beat VLC and FFmpeg at video operations" + }, + { + "Content URLs": "TB", + "Description": "Web crawling is hard. Large scale web crawling - which involves crawling millions of web pages in a month across 500 to 1000 websites, is even harder. Python comes with a number of libraries which allow you to do such crawling-at-scale but a lot of real-world issues have to be tackled to get the crawling infrastructure right Some of which are, Crawl rates - You need to strike the right balance here to make sure you don't crawl too aggressively but at the same time don't crawl too slow that the crawl finishes too late. Right Data - You need to make sure you crawl the right parts of the websites to get the right data you want. Dont get blocked! - Crawling from the same set of IP addresses will get you blocked across most modern websites. One needs some kind of rotating web proxy infrastructure to make sure that crawls can continue without getting kicked out. Capturing Errors - How to capture crawling errors so you can detect most issues and surface them up, while doing distributed crawling. Having nearly a decade of experience writing custom web-crawlers, the speakers have developed a set of custom tools to make crawling easy and painless. One of this is a tool to create a set of rotating web proxy caching nodes which use Squid and frontend by a HTTP load-balancer. The other one is a distributed crawler which uses Django as the middleware to distribute crawling across multiple crawler nodes while managing crawls at one place. In this talk, the author(s) discuss about one such tool they have created and have successfully used in multiple businesses and software companies over the last 3 years. The tool allows one to quickly and cheaply create an infrastructure of custom web proxy nodes which supports multiple VPS backends. Using this tool one can rune an industrial strength web crawling infrastructure with a set of rotating proxies of up to 50 nodes with a monthly cost of just under 300 $. The authors will talk about their experience and background creating and using the tool over the years, how it works with any web-crawler and the open source nature of the code which allows it to support different infrastructure backends and also the Squid configuration for the nodes which allows to hide the IP addresses behind the crawler. The other tool is a distrubuted web crawling monitor and management tool which uses Django to schedule and manage crawls across multiple nodes via Redis and simple HTTP APIs with the crawls performed via Scrapy derived crawlers", + "Last Updated": "29 Jun, 2018", + "Prerequisites": " Some knowledge of web crawling and or web scraping. Any knowledge of Scrapy and some experience using it is very handy Knowledge of HTTP proxy servers is a huge plus.", + "Section": "Developer tools and Automation", + "Speaker Info": "Anand B Pillai is a technology professional with 20 years of software development, design and architecture. He has worked in a number of companies over the years in fields ranging from Security, Search Engines, Large Scale Web Portals and Big Data. He is the founder of the Bangalore Python User's Group and the author of Software Architecture with Python (PacktPub, April 2017). Anand has a lot of experience in web-crawling having written the original Python web-crawler HarvestMan in 2005 and developing a number of custom crawlers for various startups solving various problems. Anand is currently VP of Engineering at the early stage Legal Tech startup, Klarity Law. Noufal Ibrahim is the CEO and Founder of Hamon Technologies at Calicut, Kerala. He was key to starting the very first PyCon India conference in 2009 and has since been involved in the conference closely throughout the years. Noufal was the keynote speaker of PyCon India 2017. Noufal has made a name not just by his Python community activities, but also by his creative Python introductory talks he has conducted in various universities and institutions in Kerala. He is also a professional trainer in Python and git. Both Noufal and Anand are Fellows of the Python Software Foundation (PSF)", + "Speaker Links": " Anand B Pillai - https://twitter.com/skeptichacker Noufal Ibrahim - https://twitter.com/noufalibrahim , http://hamon.in/", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Nikunj Parmar (~nikunjparmar828)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sympy-symbolic-computation-with-python~b6xOe/", - "title": "Sympy : Symbolic Computation with Python" + "author": "Anand B Pillai (~pythonhacker)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/large-scale-web-crawling-using-python~bkl6d/", + "title": "Large scale web crawling using Python" }, - "122": { - "Content URLs": "https://docs.google.com/presentation/d/1PZ56AYSH6GZ8s-V8rfxHuZ16UCmDg03Y1L2EiTCBiUs/edit#slide=id.p \n(Subjected to changes, not final one)", - "Description": "Talk is about how python is useful in web development, what are the most powerful and popular python frameworks used i.e., Django, Pyramid, Flask and how they are used in making web applications. My talk covers : What a web framework means Why to choose python frameworks over the normal other frameworks Explanation on Django, Pyramid, Flask. Which framework should be chosen based on dependencies. Starting Web development with python. Django, Pyramid, Flask will be explained in short with the help of small code snippets. Examples of organizations using these frameworks will be given. Uses of one framework over the other will be told in detail", - "Last Updated": "29 May, 2018", - "Prerequisites": "No prerequisite is required. Desire to learn is enough to attend this talk", - "Section": "Web development", - "Speaker Info": "About Me I am Jameer, a third year Computer Science and Engineering undergrad at Amrita Vishwa Vidyapeetham, Kerala, India. I love to code in Python. So, I started my open source career by contributing to Coala organisation. Due to my open source enthusiasm, I started learning how python is useful in Web development and using Django, Flask etc., I am also an OSFY author and published an article related to how Hadoop is being used in Big Data Analysis. I am also a ACM-ICPC Regional participant at Amritapuri. I also have a keen interest in Chatbots", - "Speaker Links": "https://github.com/JameerBabu https://www.linkedin.com/in/jameer-babu-0199a2137", - "Target Audience": "Beginner", + { + "Content URLs": "Python 3.7 Release note", + "Description": "In this talk, we will deep dive into features of Python3.7 breakpoint() Data Classes Customization of Module Attributes Typing Enhancements Timing Precision Order of Dictionaries \u201casync\u201d and \u201cawait\u201d Are Keywords \u201casyncio\u201d Face Lift Context Variables importlib.resources Developer Tricks Optimizations So, Should I Upgrade?", + "Last Updated": "29 Jun, 2018", + "Prerequisites": "Core python and its internal", + "Section": "Core python and Standard library", + "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape Tech Enthusiast - Django & Chatbot specialist Mentor/Speaker Build2learn , Chennai Geeks", + "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavani Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Jameer", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-web-development~e5wYb/", - "title": "Python - Web Development" + "author": "Bhavani Ravi (~bhavaniravi)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/whats-new-in-python37~elmMa/", + "title": "What's new in Python3.7" }, - "123": { - "Content URLs": " https://fasttext.cc/ https://github.com/PacktPublishing/Learn-fastText https://github.com/facebookresearch/fastText/tree/master/python", - "Description": "FastText has been open-sourced by Facebook in 2016 and with its release, it became the fastest and most cutting edge library in Python for text classification and word representation. It is to be seen as a substitute for gensim package's word2vec. It includes the implementation of two extremely important methodologies in NLP i.e Continuous Bag of Words and Skip-gram model. Fasttext performs exceptionally well with supervised as well as unsupervised learning. The tutorial will be divided in following four segments : 0-10 minutes: The talk will begin with explaining common paradigms that are present right now. Are deep learning really necessary? 10-15 mins: what are word representations 15-25 minutes: The code will be shown and explained line by line for both the models (CBOW and Skip-gram) on a standard textual labelled dataset. Showing how you can do fast prototyping with minimal code. 25-30: How to use the pre-trained word embeddings released by FastText on various languages and where to use them. Why python3 is the best language for multi-language support and a note on general deep learning using fasttext. 30-40 minutes: For QA session. ", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic python knowledge. Some Knowledge on common NLP techniques.", - "Section": "Data science", - "Speaker Info": "Joydeep is a machine learning engineer/python developer and is a Principal Engineer at Nineleaps. 5 years back he saw the Zen of Python, fell in love with Python and has been in love with it since then. Apart from his day to day work is involved in blogging and podcasting on medium and flawcode. Teaching is another passion of his and he is a python/ML trainer at tecmax", - "Speaker Links": " Medium: https://medium.com/@joydeepubuntu/latest Github : https://github.com/infinite-Joy LinkedIn : https://www.linkedin.com/in/joydeep-bhattacharjee-934a1157/ Machine Learning Podcast: https://flawcode.com/episode/show/12 twitter: https://flawcode.com/episode/show/12", + { + "Description": "Users leave; but their credentials usually stick around. And this leaves a security hole to be filled. Though a lot of services integrate with GSuite but tools/third-party services/ssh credentials - places where individual or shared user accounts are managed out of band - remain a security risk. In the spirit of automation and predictability, we have been working towards a \u201c Centralized User management solution \u201d and automating everythin", + "Last Updated": "29 Jun, 2018", + "Section": "Networking and Security", + "Speaker Info": "I am working as an Information Security Engineer at Grofers. Earlier I was with Makemytrip and Expedia, and have a total of 3 years experience in the InfoSec field. I'm also a part time bugbounty hunter - acknowledged by various MNCs and some top companies of India. I am also an active blogger on Medium where I write about interesting vulnerabilities that I find on my bugbounty journeys. Some of the articles have been published in various Security magazines and newsletters like Hakin9, Bugcrowd. Managing application security, performing penetration testing, hardening network and infrastructure, and automating security tasks to reduce manual effort are some of the things I take care of on a daily basis", + "Speaker Links": "https://medium.com/@logicbomb_1 https://twitter.com/@logicbomb_", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Joydeep Bhattacharjee (~infinite-Joy)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cutting-edge-nlp-classifiers-in-one-hour-with-python-and-fasttext~b4v7e/", - "title": "Cutting edge NLP classifiers in one hour with Python and fastText" + "author": "Avinash Jain (~avinash86)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/centralized-user-management~eno7a/", + "title": "Centralized User Management" }, - "124": { - "Content URLs": "I'll be sharing the slides after my talk as a Github repository. Soon will be sharing a gist", - "Description": "Abstract One of the feature people love about Python is how it\u2019s dynamically typed. A lot of people are very reluctant on hearing this idea of static typing, they will come back bashing on what's the use of Python then when we introduce static typing in it. With the torch bearers of Python in the industry like Google, Quora, Instagram, and a lot of others retaining their stack on Python and introducing static checking there have to be some non-superficial benefits, which are worth discussing. This is Python class Employee(NamedTuple):\n name: str\n id: int = 3\n\ndef fib(n: int) -> Iterator[int]:\n a, b = 0, 1\n while a < n:\n yield a\n a, b = b, a+b Contents of the talk What's static typing Need of static typing Static typing in Python 3.6 Type checkers Demo mypy vs pytype Pros and Cons QnA and discussion", - "Last Updated": "29 May, 2018", - "Prerequisites": "Basic Python knowledge and a little overview of what is dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Harshil Rastogi is working as a backend software engineer @Innovaccer, previously he has worked as an NLP Scientist @Evalueserve", - "Speaker Links": "Find me on github , ohh you like QnA forums stackoverflow . Oops were you looking for a professional platform? Okay, LinkedIn it's", + { + "Content URLs": "Contents related to the talk will be added later", + "Description": "During my M.Tech. programme at IIT Guwahati, I observed that researchers in both industry and academia work with testbeds , both real and virtual, for making advancements in Computer Science , whether it is in algorithms, networking protocols or data science by running exhaustive experiments. I realised that Python, being a very versatile language , can be used to do everything related to experimental research and analysis , without requiring the usage of any other scripting language. Based on my experiences, I am presenting a talk to explain how to build automated testbed experiments, data collection and analysis with Python and a few libraries, avoiding big and bulky frameworks as much as possible . My talk is structured as follows: Building a testbed for computing and networking experiments Using Python and paramiko to provison entities (PCs, smartphones, Raspberry Pis, routers, switches, etc.) in the testbed Running tests on the entities with subprocess and paramiko Collecting log files and other trace data from testbed entities Parsing log files and trace information to collect statistics with basic text processing and regex and storing them in appropriate Python data structures like lists, tuples and dictionaries for easy access Analysing collected statistics with Python math and generating reports Visualizing graphs from statistics with python-gnuplot or matplotlib I hope that after attending my talk, you will be able to automate your testbed experiments to the extent of spending less time on experimentation and data collection and more time on actual research and publishing papers", + "Last Updated": "29 Jun, 2018", + "Prerequisites": "There are minimal prerequisities for my talk. You need to have knowledge of the following: Basic algorithms and data structures Computer networks, especially IP addressing Python basics Also you need to have: The willingness to learn and experiment", + "Section": "Developer tools and Automation", + "Speaker Info": "Hello everyone! I am Sunit Kumar Nandi , a Trainee Teacher at National Institute of Technology, Arunachal Pradesh. I have completed my M.Tech. at IIT Guwahati this year and am also enrolling for Ph.D. I am deeply interested in computer networking, telecommunications, operating systems and distributed systems design . I use Python for most of my daily work involving a great deal of experimentation. Apart from that I contribute to SuperX OS , a Linux distribution with KDE, based out of Assam, India. I love BSD and Linux based systems and have been involved with them since my childhood. As a result, I have had 14 years of experience with managing Linux servers, networking equipment and designing automated systems in the simplest way possible. In my free time, I spend my efforts running Techno FAQ , an e-magazine for science, technology, education and business", + "Speaker Links": "You can follow me on: Facebook Twitter My open source contributions: SuperX OS Packages I maintain for Arch Linux: utserver quassel-core-static Other projects I run: Techno FAQ", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Harshil Rastogi (~harshil9968)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/static-typing-with-python-what-why-and-why-not-to~e3rAd/", - "title": "Static typing with Python. What? Why? and Why not to." + "author": "Sunit Kumar Nandi (~sunitknandi)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-testbed-experiments-data-collection-and-visualization-with-python~bo0Xd/", + "title": "Automating testbed experiments, data collection and visualization with Python" }, - "125": { - "Content URLs": "Content will be shared on github after the workshop. I will share detailed plan for the workshop in a while for the review", - "Description": "Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero ( https://deepmind.com/blog/alphago-zero-learning-scratch/ ). \nOpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms. In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding. Content Introduction to Reinforcement Learning (~ 15 mins) Introduction to Reinforcement Learning algorithms (~ 15 mins) Setting up OpenAI Gym and other dependencies Implementing simple algorithm using one of the atari games from OpenAI Gym (~ 1 Hr 15 mins) Quick overview of deep reinforcement learning and important papers in the area (~ 15 mins)", - "Last Updated": "29 May, 2018", - "Prerequisites": "Participants must be well versed with python. Some exposure to analytics libraries in python such as numpy, pandas, keras, tensorflow, pytorch would help", - "Section": "Data science", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company. I have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures. Since past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", - "Target Audience": "Advanced", + { + "Content URLs": "http://openaccess.thecvf.com/content_ICCV_2017/papers/Zhang_StackGAN_Text_to_ICCV_2017_paper.pdf https://pytorch.org/ Slides to be uploaded soon", + "Description": " The workshop is intended to introduce, explore and get a hands on experience on one of the most interesting application of GENERATIVE ADVERSARIAL NETWORKS which is - given the description of an image, the GAN model generates an image according to that description. The workshop is to be divided in two parts: \n1. Giving a hands on of using word embeddings to encapsulate the textual information and basics of how to train a vanilla GAN.\n2. Combining the word embedding and training a 2 stage stacked GAN to generate relevant Image ( We will be providing with pre-trained models as training takes a lot of time ) The workshop would then aim to go over the plausible applications that it could have.\nThe first part of the workshop will be as follows: We would be teaching basics aspects of NLP i.e word embeddings with hands on experience of python libraries NLTK etc. We would be then moving on to the next part where we will teach the basics of how to train a vanilla GAN on their laptops using Pytorch followed by a simple application. We will be providing the audience with Jupyter notebooks with skeleton code and the remaining code will be written on the spot.\nAim of the teaching the training procedure is to get the audience a hang of what parameters to keep in mind while training a Neural Network. The second part of the workshop will be as follows We will be training the Gan using the word embeddings to get a rough Image representation followed by another GAN ( stacked one after other ) to get a full resolution image ( details given in Paper ) We will be providing the trained model of GAN as it requires a lot of time to train the GAN. We will be providing the Jupyter Notebooks giving the architecture and will be writing some parts of the Stacked GAN\u2019s on the spot. We will be discussing the possible applications of GAN\u2019s in both research and industry.", + "Last Updated": "29 Jun, 2018", + "Prerequisites": "Basics of NLP ( word embedding ), Basics of Neural Network, Basics of Python numpy and Pytorch", + "Section": "Others", + "Speaker Info": "I ( Sairam ) am currently a research associate at Center for Visual Information Technology, IIIT Hyderabad. I graduated from Electronics Engineering from IIT BHU last year. My experience with Computer Vision is of 4 years, with varied internships at CWNU, South Korea working on face recognition, NTU Singapore working on Maritime vessel detection to Crowd modelling. I\u2019m currently working on Cancer detection from slide images of cancerous tissues.I have been the lead of many workshops and tutorials conducted at my college, for acquainting freshmen with the basics of Vision and ML. Zeeshan is currently a research fellow at Center for Visual Information Technology, IIIT Hyderabad. He has graduated in Electrical Engineering from VJTI, Mumbai. He has an experience of 2 years in developing trading systems at Citi. Currently he is working on gradient estimation for stochastic neural networks", + "Speaker Links": "My LinkedIn profile can be viewed at: https://www.linkedin.com/in/sairamtabibu/ Zeeshan's Profile: https://www.linkedin.com/in/zeeshan-ashraf-508587137", + "Target Audience": "Intermediate", "Type": "Workshops", - "author": "saurabh1deshpande", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-reinforcement-learning-using-openai-gym~b2qMa/", - "title": "Introduction to reinforcement learning using OpenAI Gym" - }, - "126": { - "Content URLs": "https://github.com/hasura/gitkub", - "Description": "Gitkube is an open-source project that brings the developer experience of Heroku, on your own kubernetes vendor within 60 seconds . This means that you can take your python app, deploy it with a git push & scale it massively all on infrastructure you own at a fraction of the cost on Heroku. After a brief introduction, this talk will be a live-coding demo + tutorial. \nAudience members are encouraged to bring their own laptops with python apps and follow along in the talk to deploy their app. Permitting time, the talk will cover how gitkube works and how developers can contribute", - "Last Updated": "29 May, 2018", - "Prerequisites": "Python\nGi", + "author": "Sairam tabibu (~sairam)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/synthesising-images-from-text-using-generative-adversarial-networks~epqVa/", + "title": "Synthesising Images from text using Generative Adversarial Networks" + }, + { + "Description": "A data scientist's job is usually to train a model often in the form of a jupyter notebook. However, to take this model to production takes different skills, a significant engineering effort and a lot of hidden technical debt accumulated over time. Grace, a platform agnostic deployment framework addresses this problem (thus reducing the machine learning engineering effort) by acting as an orchestration tool to deploy deep learning models in production environment leveraging tensorflow serving , docker and kubernetes. Any deep learning model to be deployed is configurable through a json spec containing input, output, model weights etc,. Other services essential to maintenance like deep-dive monitoring tools, load testing tools, structured centralized logging are provided out of the box", + "Last Updated": "29 Jun, 2018", + "Prerequisites": "python, basics of machine learning/ deep learnin", "Section": "Developer tools and Automation", - "Speaker Info": "Tanmai runs a startup, Hasura, where they're building tools to make it easier for developers to move to GraphQL and Kubernetes. \nThey were early adopters in the container ecosystem (pre-1.0 adopters for both Docker and Kubernetes) and have grown and contributed to the ecosystem as a company especially in India. Before this, Tanmai ran a consulting firm where their work included everything from MVPs for startups to helping one of the largest banks in the world migrate from legacy monoliths to containerised microservices. Tanmai has been building applications for over 8 years with a variety of frameworks. He is a firm advocate of democratising the power to develop applications and is the proud teacher of one of the largest tech MOOCs in India, imad.tech", - "Speaker Links": "Kubecon talk on gitkube: https://www.youtube.com/watch?v=gDGT4Gf_4JM Hasura: https://hasura.io LinkedIn: https://www.linkedin.com/in/tanmaig/ Twitter: https://twitter.com/tanmaig", + "Speaker Info": "Venkat Karun is a full stack generalist and polyglot with 15 years of experience building high performance, distributed systems including a decade at Google. He enjoys reading up on functional programming and lambda calculus and tinkering with ev3dev and the lego Python ecosystem in his spare time. He is currently working as Chief Architect at NicheAI pvt ltd. Venkatesh Mondi, an aerospace engineer by education worked in ISRO before finding his love for programming and machine learning. He worked as a software programmer in various platforms before co-founding NicheAI pvt ltd . He has been working on a variety of production grade computer vision solutions since it's inception. He can be found experimenting with gadgets, software, mathematics in his free time", + "Speaker Links": "Venkat Karun Venkatesh Mond", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Tanmai Gopal (~tanmai)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demo-tutorial-git-push-to-deploy-your-python-app-to-kubernetes-heroku-style~e1pZd/", - "title": "Demo + tutorial: Git push to deploy your python app to kubernetes - heroku style!" + "author": "Amith Reddy (~velutha)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/grace-a-deployment-tool-for-deep-learning-models~bqrpd/", + "title": "grace - a deployment tool for deep learning models" }, - "127": { - "Content URLs": "Slides Repositor", - "Description": "I'll be sharing how Python has been of help in my transformation from a hobby developer to a researcher.\nCoding and in particular, simulations are used extensively in the field of research to verify results and sometimes serve as experiments when it is physically not feasible. I'll describe step by step, how to design a real-time simulator using the example of an aerial swarm of drones in a survivor rescue scenario with the help of common Python libraries", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic understanding of Python classes and objects Enthusiasm to learn something new Love for Python", + { + "Content URLs": "https://www.dowhatucant.com/pyconindia18", + "Description": "While introducing people to Python metaclasses I realized that sometimes the big problem of the most powerful Python features is that programmers do not perceive how they may simplify their usual tasks. Therefore, features like metaclasses are considered a fancy but rather unuseful addition to a standard OOP language, instead of a real game changer. This talk wants to show how to use metaclasses and decorators to create a powerful class that can be inherited and customized by easily adding decorated methods", + "Last Updated": "29 Jun, 2018", + "Prerequisites": "An experience working with and developing python programs and a general understanding of the python syntax", "Section": "Core python and Standard library", - "Speaker Info": "Aniq Ur Rahman, Final year undergraduate student from NIT Durgapur. Summer '18 Research Intern at CERN GSoC '17 Intern at RoboComp Summer '17 Research Intern at SWAN Labs, IIT Kharagpur", - "Speaker Links": "Linked In Blo", - "Target Audience": "Beginner", + "Speaker Info": "I am just an average guy who got into programming and fell in love with it. 3rd year undergrad at IIT Dharwad and a Google Summer of Code 2018 student with coal", + "Speaker Links": "https://github.com/ishanSrt https://gitlab.com/ishanSrt http://dowhatucant.com/gsoc_archive.htm", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Aniq Ur Rahman (~Aniq55)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-research~eZGQa/", - "title": "Python and Research" + "author": "ishan srivastava (~ishan38)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/metaclasses-and-decorators-a-match-made-in-space~ervpe/", + "title": "Metaclasses and decorators: a match made in space" }, - "128": { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "Artificial Intelligence is spreading in the modern world and it has changed the face of technologies in past several years, especially Information technology. Today we are much engaged with using and developing so-called intelligent computing systems and devices. This paradigm has evolved in many sub-areas likewise Machine Learning, Deep Learning & Neural Networks. These sub-areas of AI have a greater role in solving Vision problems( e.g. image recognition, object & activity detection etc.), Speech problems( e.g. ASR, trigger word detection, language translation etc.) and many more complex problem domains with help of robust algorithms & models. this talk will be focused on Sequence Neural Models used for solving the Speech and text problems and we will be introduced to real-world applications. topics covered during the talk Introduction Recurrent Neural Networks Word embeddings Attention Models(Trigger word detection) Real World Applications", - "Last Updated": "29 May, 2018", - "Prerequisites": "Machine Learning\nBasics of Neural Networks\nPython Programming Machine Learning( Basics) Basics of Neural Networks Python", + { + "Content URLs": "Will be updated soon", + "Description": "It seems like every tech company is slinging around buzzwords like \u201cbig data,\u201d \u201cartificial intelligence,\u201d and \u201cmachine learning\u201d. Machine learning is able to make sense of digital data at a much faster rate than any human is capable of doing and hence choosing the application of ML-Recommendation Systems, tends to be a decision of priorities. These systems are personalizing our web experience, telling us what to buy (Amazon), which movies to watch (Netflix), whom to be friends with (Facebook), which songs to listen (Spotify) etc.\nIn this talk I\u2019ll explain the amount of work going behind this, diving into the mechanism of one such way to build these recommendation systems. OUTCOME After this talk, the audience would be able to understand the actual working of these systems. It involves knowledge of different types of recommendation systems, algorithms used, evaluation of the systems generated, working of deep recommendations \u2013 at last eventually building one(model) from scratch.The talk would answer the queries about the domains of the systems created- media, e-commerce, travel & real estate , education , job-boards, etc.- 'how AI has revolutionized e-commerce.' -giving a clear insights to mechanisms responsible for the same. AGENDA Introduction to recommendation systems. Domains of recommendation systems. Categorising algorithms and their evaluations Describing the python libraries used. Building a music recommendation system using the libraries \u2013 popularity based model & personalised collaborative filtering model Performance analysis of both models & real world instances of recommendation systems. Q & A Session", + "Last Updated": "29 Jun, 2018", + "Prerequisites": "Basic knowledge of machine learning & love for pytho", "Section": "Data science", - "Speaker Info": "The speaker, Prashant Kumar Rai, is a final year M.C.A. student at Department of Computer Science (Pondicherry University, Puducherry) who has been working on Machine Learning and data science for quite a while. he pivoted from C to Python in his first year of Master's and currently using this for his projects. He used to blog at his leisure time. Prashant is also a course mentor for 'Sequence Models' part of Prof. Andrew Ng' s Deep Learning Specialization on Coursera, where he helps learners who need in-course assistance and feedback to successfully complete a course", - "Speaker Links": "Github Twitter Quora LinkedIn Mediu", + "Speaker Info": "Aakanksha Chouhan Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence, occasionally working on blockchain projects. I\u2019m a member of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, Blockchains and Computational Biology. I also regularly participate and give talks in paper-reading sessions and meetups like PyData Amaravati ", + "Speaker Links": "Connect with me on linkedin Twitter email : akankshachouhan98@gmail.co", "Target Audience": "Beginner", "Type": "Talks", - "author": "PRASHANT KUMAR RAI (~pkraison)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/follow-the-sequence-in-deep-way-introducing-sequence-models~bYYAb/", - "title": "Follow the Sequence in Deep way - Introducing Sequence Models" + "author": "AAKANKSHA_CHOUHAN", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-machine-learning-and-media-building-your-own-recommendation-system-from-scratch~avz5a/", + "title": "Deep Dive : machine learning and media -building your own recommendation system from scratch" }, - "129": { - "Content URLs": "https://docs.microsoft.com/en-us/python/api/overview/azure/?view=azure-pytho", - "Description": "Python SDK for Azure is natively available. We would explore how this SDK can be used for automation and management of Azure. Python makes it easier for IT Pros and Developers to build a rock solid DevOps pipeline with simple script", - "Last Updated": "28 May, 2018", - "Prerequisites": "Basic understanding of Azure or any cloud\nBasic Python knowledg", - "Section": "Developer tools and Automation", - "Speaker Info": "Wriju works for Microsoft as Cloud Solution Architect. He is with Microsoft for more than 13 years and total of 17 years of industry experience. He is one of the first to play with Azure in its very early stage back in 2008. His day to day job is to help a big Oil and Gas Enterprise to adopt cloud as the strategic platform. His key area of focus is to help customer migrate their line of business applications to Microsoft Azure. Application modernization is another aspect. This involves designing and implementing Serverless workflow and Microservices. He helps Architects to design and implement the solutions which are cloud scale", - "Speaker Links": "Twitter handle: @wrijugh\nBlog: https://blogs.technet.microsoft.com/wriju\nLinkedIn: https://www.linkedin.com/in/wrijughosh", + { + "Content URLs": "Tensorflow for poets Fast Image classification using Bottlenecks Tensorflow Debugge", + "Description": "Accelerating Transfer Learning using Effective Caching Technique Transfer Learning is something which has become a routine today. Neural Networks have a lot of parameters (millions of them) which are trained iteratively in a data-driven fashion. With these many parameters come huge representational power (ability to model hyper dimensional complex functions). In cases where we train a custom classifier (say a CNN), we might not be having that much data so the network can easily overfit when trained from scratch. So here comes transfer learning, use the previously accumulated knowledge (in form of weights in neural nets) to learn our problem. In case of fine-tuning also we will be training final layers of the network only. (If you are not aware don't worry this will be covered). Huge networks take significant time train completely. To reduce this time comes methods of effective caching or informally called Training with Bottlenecks This method though is easy to implement, can give very good results. ResNet50 which took 45 sec for an epoch to train using normal transfer learning procedure, now takes 8 sec per epoch. Which is almost 6x speed up! * *Trained on Nvidia GeForce GTX 1050, i5-7300HQ Processor (5 category flower dataset) Learning Outcome Why is Computer Vision difficult problem? The role of Deep Learning in Computer Vision Deep Convolutional Networks for Image recognition Different Convolutional Architectures for Image recognition Difficulty in Optimizing large neural nets and hints for effective training Uses of pretrained models and basis of transfer learning What is Transfer Learning and why is it important? Different methods of Transfer Learning Accelerating training a neural network by caching the non-trainable model's output (Hands on Implementation in keras ) Analysing the speedups and potential limitations in this procedure How to debug Tensorflow Program? This presentation is not about how to debug DL model (Example DL model is not fitting well). Its about how to debug your program in programming perspective . Debugging a tensorflow program can be difficult due to many reasons out of which some are, The concept of computational graph construction Abstraction of tf.Session() many more. So we will introduce commonly used tensorflow debugging tools like (main ones are listed) Tensorboard Tensorflow Debugger tfdbg ", + "Last Updated": "29 Jun, 2018", + "Prerequisites": " Basic understanding of Deep Learning , Tensorflow and keras Working knowledge of python ", + "Section": "Data science", + "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", + "Speaker Links": "R S Nikhil Krishna Personal Website GitHub LinkedIn StackOverflow Lokesh Kumar T GitHub LinkedIn StackOverflow ", "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Lokesh Kumar T (~tlokeshkumar)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/accelerating-transfer-learning-using-effective-caching-and-how-to-debug-tensorflow-programs~dwA8a/", + "title": "Accelerating Transfer learning using Effective Caching and How to Debug TensorFlow programs" + }, + { + "Content URLs": "Will provide the links soon", + "Description": "Apache Spark is an open-source Distributed Computational Framework. It sits on top of Cluster Manager and Distributed Storage. Spark program runs in driver and utilizes Cluster manager to run tasks. Apache Spark has become the most preferred option in the field of Machine Learning due to its faster processing utilizing in-memory computations with Resilient Distributed Dataset (RDD). With the Python being the most preferred language for Machine Learning and Deep Learning tasks, PySpark has become most important weapon in the arsenal of Data Scientists/Data Engineers. PySpark is Python API to the Scala Core of Spark allowing Python programmers access to run Distributed jobs in Spark. This session will introduce you Spark architecture and show how to use PySpark to run Machine Learning tasks on Spark", + "Last Updated": "29 Jun, 2018", + "Prerequisites": "Knowledge of Machine Learning Knowledge of Pytho", + "Section": "Data science", + "Speaker Info": "Shashi Jeevan is an author, trainer, architect with over two decades of experience in the software industry working in various domains including Finance, Digital Signage, Rich Media Management, etc. He loves to master new technologies and share his learnings. He regularly presents and organizes free technical sessions through the Hyderabad Software Architects meetup group which he founded in 2015", + "Speaker Links": "https://www.linkedin.com/in/shashijeevan/ https://shashijeevan.com https://github.com/shashijeeva", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Wriju Ghosh (~wriju)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-and-automating-azure-with-python~eXXve/", - "title": "Managing and Automating Azure with Python" + "author": "Shashijeevan M.P. (~shashijeevan)", + "created_on": "29 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-pyspark~egGGe/", + "title": "Introduction to PySpark" }, - "130": { - "Content URLs": "I will share the slides on my github repo for the evaluation by the team in some days.\nOther content will be shared on github after the talk", - "Description": "Training a machine learning / deep learning model is one thing and deploying it to a production is completely different beast. Not only you have to deploy it to a production, but you will have to retrain the model every now and then and redeploy the updates. With many machine learning / deep learning projects / POCs running in parallel with multiple environments such as dev, test prod, managing model life cycle from training to deployment can quickly become overwhelming.\nIn this talk, I will discuss an approach to handle this complexity using Docker and Python.\nRough outline of the talk is, Introduction to the topic Problem statement Quick introduction to Docker Discussing the proposed architecture Alternative architecture using AWS infrastructure Demo", - "Last Updated": "28 May, 2018", - "Prerequisites": " Basic Python Basic Docker", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company.\nI have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures.\nSince past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", + { + "Content URLs": "Slides Deck: https://slides.com/ineil77/deck/fullscreen References Imbalanced Learn Python Library: http://contrib.scikit-learn.org/imbalanced-learn/stable/index.htm", + "Description": "Classification algorithms are known to under perform when faced with data that is heavily skewed towards one class as most of them are designed to work under assumptions of uniform class distribution. Another such caveat is the assumption of uniform cost of misclassification of all samples. For instance in a transaction fraud detection setting, the fraudulent transactions are vastly outnumbered by the genuine ones. Also the cost of wrongly classifying a fraudulent transaction as a genuine one far outstrips the inconvenience caused by flagging a benign transaction as a malicious one. This talk aims to cover the various approaches used to cope with this commonly faced problem: Oversampling Methods Undersampling Methods Synthetic Data Generation Cost Sensitive Learning Key takeaways from this talk: How imbalanced data sets undermine classifier performance How to eliminate class imbalance The advantages and disadvantages of over/under sampling and synthetic data generation Robust evaluation metrics insensitive to class imbalance", + "Last Updated": "30 Jun, 2018", + "Prerequisites": " Basic Python Understanding of basic performance evaluation metrics", + "Section": "Data science", + "Speaker Info": "I'm Indraneil Paul, a final year Computer Science student at IIIT Hyderabad. I have been involved in machine learning, computer vision and mathematical optimisation for the best part of the past three years due to my research work. I was previously working in the Computer Vision lab on an autonomous driving project and am currently working on applying graph based machine learning models to social networks. I was also a Google Summer of Code '17 student under electric vehicle startup Green Navigation (now nav-e)", + "Speaker Links": "Github: https://github.com/iNeil7", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "iNeil77", + "created_on": "30 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-comprehensive-overview-of-dealing-with-imbalanced-datasets-in-python~ejkPa/", + "title": "A Comprehensive Overview of dealing with Imbalanced Datasets in Python" + }, + { + "Content URLs": "CHAOS", + "Description": "Software development projects, in particular the open source ones, heavily rely on the use of tools such as Git, GItHub and mailing lists to support, coordinate and promote their development activities. \nDespite their paramount value, they contribute to fragment the project data, thus hindering the work of both practitioners and researchers to collect, clean, link and analyse this data to derive insightful analytics about the software project. In this context, the Community Health Analytics and Open Source Software (CHAOSS) project, under the umbrella of the Linux Foundation is currently working towards analysing open source communities and how they function. This talk presents GrimoireLab, a Python-based open source platform, part of CHAOSS. GrimoireLab allows us to seamlessly analyse open source projects, measuring their activities, processes and communities.\nWe will discover the tools composing GrimoireLab and learn how to use them. At the end of the talk we will know how to: Collect data in an automatic and incremental way from almost any tool related with contributing to open source development (e.g., source code management, issue tracking systems, forums), Enrich the collected data with additional information like contributors affiliation and geographical data as well as manage and unify identities (e.g., emails, username) belonging to the same contributor. Visualize your project data through interactive dashboards and reports. I will also touch upon my experience as a Google Summer of Code-18 student under CHAOSS and how you can participate in the community and contribute to the project", + "Last Updated": "30 Jun, 2018", + "Prerequisites": " Willingness to learn about new tools Interest in Open Source Development [A must] A good understanding of how APIs work Knowledge about how the command line works Basics about how Elasticsearch works is appreciated but not necessary", + "Section": "Data science", + "Speaker Info": "Hey!! I am Pranjal Aswani. I recently finished my engineering from TCET, Mumbai . I am an Open Source enthusiast and a Python Dev. As you might have guessed from my Proposal, I am working with CHAOSS under GSoC-18. I have a high interest in Data Analysis and this is going to be my first PyCon talk! (if selected :P) If you are a potential employer or just want to talk, please feel free to visit my website for more information! (link below", + "Speaker Links": " aswanipranjal.github.io blog GitHub LinkedIn Twitter", "Target Audience": "Intermediate", "Type": "Talks", - "author": "saurabh1deshpande", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-devops-and-ab-testing-using-docker-and-python~bWKEb/", - "title": "Machine Learning DevOps and A/B testing using docker and python" + "author": "Pranjal Aswani (~pranjal2)", + "created_on": "30 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-is-your-open-source-project-doing~bklNd/", + "title": "How is your Open Source project doing?" }, - "131": { - "Content URLs": "https://speakerdeck.com/aravindputrevu/introduction-to-application-performance-monitorin", - "Description": "Often late, the time to debug that particular bug/issue occurring in production with respect to your application is increasing. It might also cause business disruption and affect your organization financially. In this talk, I'd explain how you could use Application Performance Monitoring to understand your application. Application Performance Monitoring (APM) is a solution built on Elastic Stack. APM helps you to build/store data points in Elasticsearch and visualize. It automatically collects information from your python application/service. This talk mainly targets at introducing the solution, why it is needed and what you can do with data. It ends with once data is stored within Elasticsearch, what else you can use the same data for (ex. Infrastructure Monitoring, Machine Learning)? Agenda What is APM?\nWhy APM?\nWhat it can do to your Application?\nDem", - "Last Updated": "28 May, 2018", + { + "Content URLs": "Info about selenium: http://selenium-python.readthedocs.io/getting-started.html Project repo: https://github.com/pareksha/WhatsApp-Automatio", + "Description": "I was fed up with the daily 'Good Morning' messages I had to send to my crazy not so important friends as well as waking up till midnight just to send 'Happy Birthday' messages. I decided to automate all this stuff and I found 'Selenium' to be just fit for the purpose. Selenium is simply a web browser automation tool but what you can do with it is totally up to your imagination. This talk will be about the numerous crazy ideas you can implement using Selenium including automating WhatsApp messaging like wishing birthdays at midnight and sending bulk messages on one click. The talk will also include how quickly and easily these things can be implemented using Selenium", + "Last Updated": "30 Jun, 2018", + "Prerequisites": "Knowledge regarding basic python syntax (or of any other programming language)", "Section": "Developer tools and Automation", - "Speaker Info": "Aravind is a loquacious person, who has something to talk about everything. He is passionate about evangelising technology, meeting developers and helping in solving their problems. He is a backend developer and has six years of development experience. Currently, he works as a Developer Advocate At Elastic and interact with developer community in South East Asia and India. He has deep interest in Machine Learning, Security Incident Analysis and IoT tech. In his free time, he plays around Raspi or a Arduino", - "Speaker Links": "https://aravindputrevu.in will have links to all my social accounts. I have been doing community work for last 3 years. Presenting the same talk at PyCon Bangkok on June 16-17. https://th.pycon.org/talks/#monitoring-your-python-applicatio", + "Speaker Info": "Currently, I am a Google Summer of Code intern with coala . I love coding and python is my favorite programming language. Regarding college, I am a CSE 2nd year undergrad at UIET, Panjab University", + "Speaker Links": "GitHub: https://github.com/pareksha GitLab: https://gitlab.com/pareksha GSoC blog: https://pareksha.wordpress.com/ LinkedIn: https://linkedin.com/in/pareksha", "Target Audience": "Beginner", "Type": "Talks", - "author": "Aravind Putrevu (~aravind34)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-your-python-application~eV2ze/", - "title": "Monitoring your Python Application" + "author": "Pareksha Manchanda (~pareksha)", + "created_on": "30 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-messaging-using-selenium~bmn9d/", + "title": "Automating messaging using Selenium" }, - "132": { - "Content URLs": "https://tools.ietf.org/html/rfc7047\nhttps://github.com/openstack/ovsdbapp\nhttp://www.openvswitch.org/support/dist-docs/ovsdb-server.1.htm", - "Description": "OpenvSwitch is an OpenFlow virtual switch implementation. It has its own database implementation based on JSON-RPC (https://tools.ietf.org/html/rfc7047) to store its internal state and data.\nThis session gives an overview of this database implementation and how it used in OVN, an SDN controller from the OpenvSwitch community and in OpenStack networking. This session will look\ninto how it is different from other traditional SQL databases and the python clients available to interact with the OVSDB server and the APIs it provides to carryout the CRUD operations with the OVSDB server", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of databases", + { + "Content URLs": "Will update shortly", + "Description": "The talk aims to provide an understanding of popular tools at disposal for writing efficient tests using pytest. This intermediate to advanced talk will do a walk through of all components involved in writing production-ready test cases using fixtures, auto-fixtures, factories, faker, mocker etc in a django application. Once the tests look good, they will be integrated with Jenkins (Blue Ocean) where a coverage report of tests will be displayed. Continuous Integration of code on VCS (GitHub) with Jenkins will provide test-runs on every code push to remote repository. This will arm the audience with a robust test suite which is ready to be deployed", + "Last Updated": "30 Jun, 2018", + "Prerequisites": "Familiarity with python web-framework (any)", + "Section": "Developer tools and Automation", + "Speaker Info": "I am Aditi Bhatnagar, a senior software developer at a start-up in Bangalore. I have industry experience of 6 years and find myself constantly in need of writing well-tested code. Robust integration tests have often protected me from accidental errors seeping in production", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Aditi Bhatnagar (~aditi95)", + "created_on": "30 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/testing-with-pytest-and-continuous-integration-with-jenkins~enoWa/", + "title": "Testing with pytest and continuous integration with Jenkins" + }, + { + "Content URLs": "Will be updated soon", + "Description": "In this talk the enthusiasts will get to see the integration of Django, DRF, Django Channels and Angular to create a modern Real-time web App Goal:\nTo clear the clouds around creating Modern WebApps Using Djang", + "Last Updated": "30 Jun, 2018", + "Prerequisites": "Python\nDjango\nDRF\nAngula", + "Section": "Web development", + "Speaker Info": "Hello I am Jaipreet Singh. I am a developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", + "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Jaipreet Singh (~Jaipreet95)", + "created_on": "30 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-modern-real-time-apps-with-django-drf-django-channels-and-angular~bo0Bd/", + "title": "Building Modern Real-time Apps with Django, DRF, Django Channels and Angular" + }, + { + "Content URLs": "Will be updated soon", + "Description": "Objective To explain the various design patterns that Django programmers use and prevent reinventing the wheel in each of your projects. Takeaways of this talk would be to know the answers to: What are the current best practices in Django and what are not?\nWhich are most common and useful design patterns?\nHow to identify and implement these patterns? Description Design Patterns are patterns we see and code in almost every Django projects. They are scenarios for which we wished had a canonical and elegant solution. Based on the seminal work on design patterns in the Gang of Four book and Martin Fowler's book, the talk takes you through several well known design patterns to improve your Django code. It might also cover several new patterns in web application development that you can apply to other frameworks", + "Last Updated": "30 Jun, 2018", + "Prerequisites": "Basic knowledge of OOPS and Python\nShould have completed atleast one Django Projec", "Section": "Core python and Standard library", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": " https://numans.blog/about http://stackalytics.com/?metric=commits&release=all&user_id=numansiddique https://github.com/openvswitch/ovs/commits?author=numansiddique", - "Target Audience": "Beginner", + "Speaker Info": "Hello I am Jaipreet Singh. I am a developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", + "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", + "Target Audience": "Advanced", "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/openvswitch-database-based-on-json-rpc~dRKVe/", - "title": "OpenvSwitch Database based on JSON-RPC" + "author": "Jaipreet Singh (~Jaipreet95)", + "created_on": "30 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/design-patterns-in-python-and-django~epqpa/", + "title": "Design Patterns in python and Django" }, - "133": { - "Content URLs": "https://en.wikipedia.org/wiki/OpenFlow\nhttps://www.openvswitch.org/\nhttps://3vf60mmveq1g8vzn48q2o71a-wpengine.netdna-ssl.com/wp-content/uploads/2014/10/openflow-switch-v1.5.1.pd", - "Description": "Networking is a key aspect of any cloud infrastructure solution. All the VMs and containers\nspawned in a cloud deployment should have seemless layer 2 and layer 3 connectivity. All this is\npossible because of virtual switching and virtual routing. This session talks about what is OpenFlow specification, OpenvSwitch (which implements OpenFlow)\nand how it is used as an important SDN layer in cloud infrastructure solutions (taking OpenStack and OVN as an example)", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of networking", - "Section": "Networking and Security", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": "https://numans.blog/about/\nhttp://stackalytics.com/?metric=commits&release=all&user_id=numansiddique\nhttps://github.com/openvswitch/ovs/commits?author=numansiddiqu", + { + "Content URLs": "Will be updated soon", + "Description": "If things work out as you\u2019ve envisioned, there will be a time in your webapp\u2019s lifecycle when it\u2019s serving a large number of users. By the time things get to this point, it\u2019s ideal if you\u2019ve architected your webapp to both scale gracefully to meet this load, and also be resilient to arbitrary failures of underlying compute resources. This talk is about how you can use Docker containers and Kubernetes to help your Django webapp achieve these architectural goals. While it meanders a bit through theory and philosophy, it does work up to a concrete example to help solidify concepts", + "Last Updated": "30 Jun, 2018", + "Prerequisites": " Basics of Linux Familiarity with Docker and docker files Kubernetes(optional)", + "Section": "Core python and Standard library", + "Speaker Info": "Hello I am Jaipreet Singh. I am a Sofware developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", + "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", "Target Audience": "Advanced", "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-introduction-to-openflow-and-openvswitch~aQKGd/", - "title": "An introduction to OpenFlow and OpenvSwitch" + "author": "Jaipreet Singh (~Jaipreet95)", + "created_on": "30 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/maintaining-scalability-of-django-powered-web-app-by-using-containers-and-kubernetes~bqr0d/", + "title": "Maintaining scalability of Django powered web App by using containers and Kubernetes" }, - "134": { - "Content URLs": "The repository where I have implemented concepts related to this talk https://github.com/tanayseven/http_quiz Contents for the presentation for the talk https://github.com/tanayseven/pycon_2018_python_web_app_tes", - "Description": "Abstract One of the first projects that I worked in the industry was in Flask . This talk is based on my experiences in the project with respect to the test suite and different things that I learnt in that. On the bases of those learnings, I started my own open source project on Github and enhanced on those ideas on how all the things necessary for testing are done. This is based on Flask as the web framework and all the ideas are implemented in it. The topics it covers are those things that you can do to achieve a robust set of tests in your code. Outline of the talk Pushing for 100% code coverage Making your test execution fast! The evil of \u2018over mocking\u2019 The necessity of using dependency injection Test Pyramid or Test Cone? TDDing while making changes Layers that make the web app architecture How does this map to UI testing", - "Last Updated": "27 May, 2018", - "Prerequisites": "Although most of the things are implemented in Flask, it is not necessary to know it, although it is very much recommended to know some web framework or having some knowledge of web app programming", - "Section": "Web development", - "Speaker Info": "A passionate developer with Python as his primary language. Have worked with Flask in the industry in the past. Passionate about testing and writing the code in a way that is very clean and maintainable. A strong believer in TDD and massive test coverage", - "Speaker Links": "https://tanayseven.com https://github.com/tanayseven https://www.linkedin.com/in/tanay-prabhudesai/ https://twitter.com/tanayseve", - "Target Audience": "Intermediate", + { + "Content URLs": "http://pyflyby.or", + "Description": "Python is a wonderful programming language because of its lack of boilerplate. However, one remaining area of boilerplate is import statements. When writing a python program, it's tedious to go back and forth to the top of the file to add and remove import statements. When using Python interactively, it's tedious to type import statements. I have created a tool called Pyflyby to automate imports. Pyflyby has two killer features. (1) With one button, Pyflyby automatically modifies your Python code to add necessary imports and remove unnecessary imports. You can integrate into your editor or use the command-line tool. (2) Pyflyby enhances IPython/Jupyter to automatically import symbols on-demand. I started Pyflyby in 2011 as a side project. It has become wildly popular within my firm; most developers at my firm swear by it. I recently open sourced Pyflyby to make it available to the community. In this talk, I will present how to use Pyflyby, how it works, and how it has changed Python development at my firm", + "Last Updated": "01 Jul, 2018", + "Prerequisites": "Non", + "Section": "Developer tools and Automation", + "Speaker Info": "I have been a developer in the asset management division of the D. E. Shaw group since 2009. I also manage the Python infrastructure group at the firm", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Tanay PrabhuDesai (~tanay)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/having-a-robust-test-suite-for-your-python-web-app~dPKAb/", - "title": "Having a robust test suite for your Python web app" + "author": "Karl Chen (~quarl)", + "created_on": "01 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pyflyby-automatic-imports-for-python~erv4e/", + "title": "Pyflyby: Automatic imports for Python" }, - "135": { - "Content URLs": " Github reposistories: Keras_aud Audio-Vision Drive links: Content link : (Slides to be uploaded soon)", - "Description": "In this workshop, we will try to teach how to understand Deep Learning, various paths to follow, Domains to explore and the most important part- how to start with the paper selection and implementation. We will also learn how to deploy a simple model into production. This workshop aims at providing the attendees of all level a foundation of research and further prospectives in deep learning. Contents Paths and prospects in Industry and Academia (10 minutes) Difference between AI, ML, and DL. (5 minutes) Introduction to Deep Learning frameworks (Hands-on) (5 minutes) Paper selection (10 minutes) Implementation (Hands-on) (60 minutes) Understanding the dataset Feature Extraction Model Selection Data Formatting Comparison Demonstration of our work (General Overview) Audio Tagging Acoustic scene classification Visual Question Answering Publish/Deploy (Hands-on) (30 minutes) Stay Motivated Opportunites to explore The participants should have interest in Research. Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first-time learner\u2019s of AI to comprehend", - "Last Updated": "27 May, 2018", - "Prerequisites": "Preferred Basic Python concepts Basic knowledge about Machine Learning Algorithms. Preferred (but not necessary) Interest in working on Research problems Installed libraries: Keras Theano or Tensorflow", + { + "Content URLs": "Github: https://github.com/arijitsaha/FloodRis", + "Description": "Catastrophic floods had a deep impact on the early human psyche resulting in a potpourri of great flood stories ingrained in the mythology of early human civilisations spread across the globe. Despite all the human progress floods can still cause massive property damages, economic losses and casualty. Several major cities and towns in India reported a series of devastating urban floods in recent times, and the resulting human and financial loss makes study of models that can identify the flood risk of an area extremely relevant. This talk focuses on geo-spatial analytics and describes multiple techniques that can be used to assess the flood inundation risk of a geographical area. The techniques use freely available data captured by different satellites. The talk will demonstrate how we can use python libraries and Digital Elevation Models (DEM) to analyse a terrain with respect to it's elevation. The talk also also focus on how to build a first order flood fill model to identify flood inundation risks of a geographical area due to overflow of water from a nearby water body, and due to heavy rains. Some key take-aways from this talk are An introduction to various types of Remote Sensing data with extensive focus on Digital Elevation Models (DEM) Various types of public data sources available for Geospatial Analytics Working with translator library for raster and vector geospatial data like GDAL How to use other geospatial libraries like PyDEM for topographic analysis Descriptive Analytics using Python packages like numpy, pandas, scikit-learn, seaborn, matplotlib etc.", + "Last Updated": "01 Jul, 2018", + "Prerequisites": " Basic / Intermediate knowledge of Python Interest in Geospatial Analytics using Python or curiosity in application of analytics for catastrophic risk management", "Section": "Data science", - "Speaker Info": "Aditya Arora and Akshita Gupta are currently final year semester exchange students at Indian Institute of Technology, Roorkee. They have been working on research problems using deep learning specifically in Audio processing and visual Q&A. Aditya is a member of various open source societies such as rust-community while Akshita has experience in Academia research and is a selected as an Outreachy intern at Mozilla 2018. They have been working in python for the past 4 years and have been moving forward working on Computer Vision and Audio processing problems", - "Speaker Links": " Twitter : https://twitter.com/imaarora Twitter : https://twitter.com/akshitac8 Linkeldn: https://linkedin.com/in/aditya-arora145/ Linkeldn: https://www.linkedin.com/in/akshita-gupta152/ Github : https://github.com/channelcs Blog : http://channelcs.github.io/", + "Speaker Info": "Arijit Saha Arijit Saha is a data professional with over sixteen years of industry work experience in architecting, designing & developing large-scale data products, platforms & solutions for both big & medium size enterprises. Currently he is busy engineering Enterprise AI data platform & products for some of the most well-known global enterprises. He is an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Big Data Analytics, Geospatial Analytics and application of Artificial Intelligence in Enterprises. LinkedIn: https://www.linkedin.com/in/arijitsaha/ Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), Geospatial Analytics, and Reinforcement Learning. LinkedIn: https://www.linkedin.com/in/atulsinghphd", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Akshita Gupta (~akshitac8)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-into-the-world-of-deep-learning~aOXRb/", - "title": "Deep Dive into the world of Deep Learning" + "Type": "Talks", + "author": "arijit.saha", + "created_on": "01 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-flood-risk-in-this-modern-age-an-introduction-to-geospatial-analytics-with-python~avz0a/", + "title": "Managing flood risk in this modern age - An Introduction to Geospatial Analytics with Python" }, - "136": { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "The era of Artificial Intelligence is moving quite rapidly across the globe. It's being used in almost every application we know , from medical diagnosis to self driving cars and it's use is still growing exponentially. But should we blindly trust AI ? Is this technology robust enough? Are we capable enough to handle it's power? In this talk we will step back for a moment and look forward about the security issues and robustness of this technology. I'll be discussing the problems we can face , the precautions we have to take, etc. with the help of a famous problem, known as One Pixel Attack ", - "Last Updated": "25 May, 2018", - "Prerequisites": " A bit of Python Some knowledge of Machine Learning And a broader perspective ", + { + "Description": "Why a JavaScript talk at PyCon? JavaScript has become a crucial view for Pythonic data analysis via Jupyter Notebooks. Jupyter widgets have taken python data from read-only to a rich, interactive experience. This talk will focus on providing a delightful and consistent user experience across all platforms. Specifically, we\u2019ll talk about why we should want Jupyter to reuse our JavaScript ecosystem and how we achieve this. Finally, we\u2019ll end with a vision for enabling data to render similarly regardless of whether you view it in a Jupyter notebook, email, or a flask/nodejs powered website", + "Last Updated": "28 Jun, 2018", + "Prerequisites": "Familiarly with Jupyter Noteboo", + "Section": "Core python and Standard library", + "Speaker Info": "I am a developer for the JavaScript team at the D. E. Shaw group. One of our core principles is that users come first; we are hyper focused on improving the user experience for developers, technical users, and non-technical users of everything from intranet sites to the interactive python environment. We aim to delight", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Marc Udoff (~mlucool)", + "created_on": "28 Jun, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-enterprise-javascript-ecosystem~b6vRb/", + "title": "An Enterprise JavaScript Ecosystem" + }, + { + "Content URLs": "I will share presentation & relevant code soon to github", + "Description": "How I was able to scale training workloads which gave results in 3 days to experiments in 3 hrs! \nOfcourse it came with a lot of pain, but distributing the model across multiple nodes using a centralised control framework was totally worh it. A simple RESTFul framework for conducting Tensorflow training and evaluation \u2013 \nThis talk will help you: get the best results for any Tensorflow task using a distributed deployment scale your expirments to the next level run on multiple nodes to utilize faster and parallel training/inference systems What the talk will cover: Small intro to DeepLearning with Tensorflow - What it is? Why is it diffirent from other python libraries? Conducting an image segmentation task in Tensorflow How do you make it run on REAL data? ( Train + explore ) x N How to setup the an experiment for the best results in the least time", + "Last Updated": "01 Jul, 2018", + "Prerequisites": " Understanding of python object oriented programming Knowledge of RESTFul APIs Basic understanding of machine learning", "Section": "Data science", - "Speaker Info": "The speaker, Srajan Kant Jha, is a final year B.E. student who has been working on Machine Learning and Data Science from quite a while now. Nonetheless, he pivoted from C/C++ to Python and during the transition, has also developed some projects on the same. He used to blog at his leisure time and is still on a venture to provide the knowledge of ML and Data Science to enthusiasts through a project site. Srajan is also the City Ambassador (and one of the speakers) of AI-Saturdays, which is a community of over 5000+ students(over 100+ cities) that helps people try their hands on Deep Learning and Artificial Intelligence, free of cost. Inspite of this, he still has a lot to discover in this growing industry. (Follow him on social media to know more", - "Speaker Links": " LinkedIn : https://www.linkedin.com/in/srajan-jha Github : http://github.com/srajan23 (not much updated) Facebook : https://www.facebook.com/srajan23", + "Speaker Info": "Kshitij Agrawal I am a strong believer of using technology to solve real problems. With a deep specialization in computer vision, I have developed and deployed a wide array of computer vision applications on hardware as well as cloud. A deep interest in reliable large scale computer vision led me to work at solving challenges around autonomous driving at Intel India. Post my MS from IIIT-Hyd, I was working at Tonbo Imaging, a leader in thermal imaging devices for the military", + "Speaker Links": " LinkedIn Udacity Webinar on Computer Vision", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Srajan Jha (~srajan)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-robust-is-artificial-intelligence-ai-using-python~dNK2e/", - "title": "How ROBUST is Artificial Intelligence ? ~ AI using Python" + "author": "kagrwl", + "created_on": "01 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-deep-learning-managing-tensorflow-models-using-simple-resttful-frameworks~dwA1a/", + "title": "The Zen of Deep Learning \u2013 Managing Tensorflow Models using simple RESTtful frameworks" }, - "137": { - "Content URLs": "Fo now, I just have a gist: But I will create a proper package before the event: https://gist.github.com/dhilipsiva/3d7586e7bb941919f28afa70ccc39dd", - "Description": "Microservices are fun. But what would make them even more fun to work with, is if we can avoid duplicating the data layer across your micro-services. Django ORM is amazing. Let's share the joy of Django ORM with other languages. I have written a tool to automatically expose Django ORM to other languages and which can also generate respective client libraries in other languages. I heavily rely on Protobuf and gRPC and a lot of AST parsing", - "Last Updated": "25 May, 2018", - "Prerequisites": "You will need to know basics of: Django ORM Protobuf gRPC (or cap'n proto or any other RPC framework) Microservices", + { + "Description": "As we move towards microservices and distributed architectures it is important to ensure your tooling acts as an effective communication between different teams. This talk is not only about building better applications but improving business delivery through better visibility into your application through the elastic stack. The Basic structure of the talk shall be: Understanding logging and exceptions. What to log and what not to log? Building pipelines to ship logs for your distributed application. Understanding ElastAlert alerting rules. Real-world examples and mechanism of how you can tie in ElastAlert with your IT operations.", + "Last Updated": "01 Jul, 2018", + "Prerequisites": "Some understanding of building business applications for any stack should help", "Section": "Developer tools and Automation", - "Speaker Info": "Wannabe Astrophysicist. Full Stack + DevOps. I code for fun and profit. Mostly in Python. FOSS. Dad of 2. Environmentalist. Atheist. Story Teller", - "Speaker Links": " http://dhilipsiva.com/ https://twitter.com/dhilipsiva https://github.com/dhilipsiva/", - "Target Audience": "Advanced", + "Speaker Info": "Amit Sethi, is a Software Developer at E2E networks. A cloud computing company out of Delhi. His day job involves writing code for distributed applications running using API's and Infrastructures. Some of which he owns and some which he does not. He is passionate about understanding how to deliver a better customer experience of application he writes while ensuring sanity for himself and fellow colleagues", + "Speaker Links": "twitter linkedi", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "dhilipsiva Dhilip (~dhilipsiva)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automagically-exposing-djagno-orm-over-grpc-for-microservices-written-in-other-languages~aMKmd/", - "title": "Automagically Exposing Djagno ORM over gRPC for microservices written in other languages" + "author": "Amit Singh Sethi (~dusual)", + "created_on": "01 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/better-visibility-into-your-distributed-application-through-elastalert~axB3d/", + "title": "Better visibility into your distributed application through ElastAlert" }, - "138": { - "Content URLs": "will be sharing the slides after my talk as a Github repositor", - "Description": "AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment. CloudFormation allows you to use a simple JSON or YAML file to model and provision, in an automated and secure manner, all the resources needed for your applications across all regions and accounts. This file serves as the single source of truth for your cloud environment. In this talk, I will be using Python to generate the JSON and YAML files with which AWS CloudFormation can be done. During this talk I will be covering the below points What is AWS CloudFormation? Library in Python for AWS CloudFormation. What are S3 and EC2 AWS services. Creating basic S3(Simple Storage Service) and EC2(Elastic Compute Cloud) instance using Python. Installing MySQL in the EC2 instance.", - "Last Updated": "25 May, 2018", - "Prerequisites": "Basic Understanding of Python and how to use Libraries", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Mohan currently working as a Software Engineer at Amzur InfoTech Visakhapatnam.I have been in to Python Programming for the past 1 year. I have 2 years of experience as a Developer. I had worked on Data Migration. I am currently working on Data Science,MicroGrids Automation and AWS", - "Speaker Links": "www.linkedin.com/in/mohan-pavan-kumar-bailapudi-5628a296 https://github.com/MohanBailapud", + { + "Description": "All web developers who use python have come across django. It is both hated and loved to varying degrees. But what about day 500. What happens when you have a team of 15 people developing and 5 teams talking to the django application. What kind of baggage does django bring for day 500th. What kind of things it solves for the day 500. Some of the points we shall talk about? What kind questions does the day 500 bring? Admin. Your friend and your foe. Managing your database changes Configuration Management Django in a muti-skill, multi-team environment. Django in a distributed environment. Building visibility in your django app.", + "Last Updated": "01 Jul, 2018", + "Prerequisites": "An understanding of django and web development basics should be helpfu", + "Section": "Web development", + "Speaker Info": "Amit Sethi, is a Software Developer at E2E networks. He has had his own love-hate relationship with django. Apart from that he has worked with frameworks like pyramid, tornado and flask with python. And also used rails and beego with ruby and golang. He is an opinionated developer with love for elegant API'", + "Speaker Links": "twitter linkedi", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Mohan Bailapudi (~mohan57)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-cloudformation-with-python~dL1De/", - "title": "AWS CloudFormation with Python" + "author": "Amit Singh Sethi (~dusual)", + "created_on": "01 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-on-day-500~dyDEb/", + "title": "Django on day 500" }, - "139": { - "Content URLs": "I'll share my slides after my talk as a GitHub repository", - "Description": "This talk is for Python enthusiasts who are interested in building test automation framework and test suites for REST API functional testing. It would throw a light on how to write useful, business-oriented and maintainable functional API test suites in Python on top of existing test frameworks like lemoncheesecake . Contents: About myself REST API and it's testing - A quick introduction Choosing a test framework to write your tests on Making API requests from Python Writing suite configuration and teardown code Introduction to the \"component-tests\" model for structuring the test code JSON parsing, use of matchers, asserts for writing test case validation criteria Importance of logging and reporting - How logs and readable reports can ease the job of debugging bugs found using tests Bringing everything together", - "Last Updated": "24 May, 2018", - "Prerequisites": " Python basics REST API basics Basics of test frameworks like pytest Passion for test automation", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm currently working as a SDET Lead with AgroStar, India's largest agri-tech platform for the Indian farmer. I'm passionate about technology and automation, I'm willing to contribute in building robust software test frameworks accompanied with some of the best industry practices like CI/CD that would help ensuring the best possible software quality from time-to-time. The \u201calways exploring and learning\u201d attitude is something that keeps me going", - "Speaker Links": " LinkedIn Facebook Twitter", + { + "Content URLs": "To be updated soo", + "Description": "I wrote a few lines of code to build a web application using Flask back in University. Everyone found it so good, it was like a forest fire. I could never have estimated that a few lines of code can help thousands of people with stuff they do every day. In my case, I designed and developed a website 'Papercop' which did the simple job of downloading all the relevant question papers from the university's portal and all the student had to do was enter their roll number. No Ads. No signups. No logins. One input. One output. And everyone out there loved it. Thousands of students used the site before every examination I'd like to take the audience through the ups and downs of seeing how a simple idea they keep thinking of, can be brought to life using Python while talking about best practices and growth hacks", + "Last Updated": "01 Jul, 2018", + "Prerequisites": "Non", + "Section": "Web development", + "Speaker Info": "I am an IIT Kharagpur graduate(2017) who spent over 4 years coding in Python. Worked with all styles of python from website development using Django and Flask to scientific computing using numpy and scikit-learn to web-scraping using Selenium. It's been a wonderful journey all along and I'm now looking forward to bring as many people on board as I can to experience what I've experienced. I am also the founder of Papercop, an examination preparation portal for the students of IIT Kharagpur which has about 70k+ hits. I am a very passionate speedcuber( Can solve the rubiks cube in about 10s odd). Won plenty of medals in speedcubing competitions across the country. I now work as an analyst with American Express. Speaker at Pycon India '17 and invited to Pycon Italy'1", + "Speaker Links": "Links to previous talks: Pycon India'17 Twitter Linkedi", "Target Audience": "Beginner", "Type": "Talks", - "author": "Akshay Maldhure (~akshay61)", - "created_on": "24 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rest-api-functional-testing-with-python~aK7Ga/", - "title": "REST API functional testing with Python" + "author": "Anuj Menta (~anujmenta)", + "created_on": "01 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/can-a-few-lines-of-python-help-thousands-of-people~azEZe/", + "title": "Can a few lines of Python help thousands of people?" }, - "140": { - "Description": "The Talk will focus on the importance of satellite image processing with main focus on the utilisation of GDAL library to conduct various operations on satellite data. Datasets will include Optical imagery and Synthetic Aperture Radar Imagery. The power of GDAL library alongwith numpy and matplotlib will be demonstrated. Brief analysis of satellite images using python will be given", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of numpy and matplotlib libraries", + { + "Content URLs": "To be updated soon", + "Description": "We have always been taught that the earlier you book a flight, the cheaper it is. What if I said it isn't? You see it's not a straight line and it has a minimum at some point(someday before the flight). We are going to see how historical Airfare data can help us derive the best day to book a flight so that you 'actually' get the cheapest fares. The talk would talk about the entire process, from getting the data, to training a basic Neural network on the data. With advancements in deep learning in these few years, it is very easy to train a simple statistical model to predict the prices. Also, my thesis at IIT Kharagpur was titled 'Forecasting of Airfare prices using Neural networks' and the talk is based on that along with a few improvements I made on top of that", + "Last Updated": "01 Jul, 2018", + "Prerequisites": "A brief understanding of neural networks or any machine learning model in general could help you make the most out of your talk", "Section": "Data science", - "Speaker Info": "Shubham Sharma is a Junior Research fellow currently working on a collaborative project with Calibration and Validation Division of Space Applications Centre, ISRO, Ahmedabad. He has a rich experience in handling and processing of Synthetic Aperture Radar Images. Also, he has experience in building software tools in python for satellite Image analysis", + "Speaker Info": "I am an IIT Kharagpur graduate(2017) who spent over 4 years coding in Python. Worked with all styles of python from website development using Django and Flask to scientific computing using numpy and scikit-learn to web-scraping using Selenium. It's been a wonderful journey all along and I'm now looking forward to bring as many people on board as I can to experience what I've experienced. I am also the founder of Papercop, an examination preparation portal for the students of IIT Kharagpur which has about 70k+ hits. I am a very passionate speedcuber( Can solve the rubiks cube in about 10s odd). Won plenty of medals in speedcubing competitions across the country. I now work as an analyst with American Express. Speaker at Pycon India '17 and invited to Pycon Italy'1", + "Speaker Links": "Links to previous talks: Pycon India'17 Twitter Linkedi", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Anuj Menta (~anujmenta)", + "created_on": "01 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/forecasting-and-observing-airfare-trends-using-python-and-neural-networks~aA23b/", + "title": "Forecasting and observing Airfare trends using Python and Neural Networks" + }, + { + "Content URLs": "https://github.com/audreyr/cookiecutte", + "Description": "When starting with a new python project/django web app, starting with initial project structure may not be that easy. Thinking about best practices that you have seen some other popular opensource projects and doing it over and over is very tiring.. what if we can just create a project with very little effort and share your set of tools that used in project to other team members? This talk is mainly about cookiecutter, it is a cli utility that creates projects from templates. We will see how to use existing cookiecutter template and finally create a template that works well for you and your team and share that template", + "Last Updated": "02 Jul, 2018", + "Prerequisites": "Knowledge regarding basic python and may be jinja templating", + "Section": "Developer tools and Automation", + "Speaker Info": "Working as developer at Pramati technologies..Working with python from past 3 years, loves programming and automation", + "Speaker Links": "github - https://github.com/code-R\nlinkedin - https://www.linkedin.com/in/vamsi-krishna-29690614", "Target Audience": "Beginner", "Type": "Talks", - "author": "shubham_thb", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/satellite-image-processing-with-python~dJKKe/", - "title": "Satellite Image Processing with Python" + "author": "Vamsi (~code-R)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/scaffolding-made-easy-with-cookies-cookiecutter~dB2kd/", + "title": "Scaffolding made easy with cookies (Cookiecutter)" }, - "141": { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Python is a versatile, powerful, and general purpose language, its easy and clear syntax makes it very popular for the beginner as well as the advanced programmer. Malware is one of the top threats to today's digital society. Due to heavy financial loss along with other infrastructure losses, the software industry is investing hue money for malware research and at the same time due to the wide need of effective and efficient anti-malware solution, the anti-virus industry is emphasizing on malware research.\nThis talk will focus on the array of python resources (script, modules, library, frameworks etc.) available for various dimensions of malware research. During the talk, I will share my experience with various tasks or problems related to malware research and how with the use of Python, those were solved. This talk will try to draw a parallel connection with various tasks related to malware research and suitable Python resources available for achieving those tasks. The talk will be supplemented with the brief explanation of concepts and python snippets for the same. \nSome of the modules and topics that I will touch upon are: yara Accessing VirusTotal API with Python Cuckoo-sandbox Androguard pefile pyew file type filtration ClamAV and pyClamd etc.", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general", - "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", + { + "Content URLs": "https://www.slideshare.net/veerskyfire/cyber-disorde", + "Description": "How social media is affecting our real life, what would be the prevention we can take to protect our digital identity and will share many real life case studies of cyber-crime with whom people will relate easily to better understand the scenario of cyber disorder and how to prevent such data leakage", + "Last Updated": "02 Jul, 2018", + "Prerequisites": "No Prerequisites", + "Section": "Others", + "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", + "Speaker Links": "Website/Blog\nhttps://www.viralparmarhacker.com Linkdin\nhttps://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter \nhttps://twitter.com/viralparmarhack Github \nhttps://github.com/Veerskyfire", + "Target Audience": "Beginner", "Type": "Talks", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-arsenal-for-malware-research~dGXKe/", - "title": "Python Arsenal for Malware Research" + "author": "Viral Parmar (~Veerskyfire)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cyber-disorder~bD2ye/", + "title": "Cyber Disorder" }, - "142": { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Malware is a serious threat to all kind of Cyberinfrastructure. Since the first known malware (formerly or generally known as Virus) there have been malware detection techniques. There is the arms race between new incoming of Malware and defense against it. Traditionally, anti-virus software uses signature-based techniques to detect malware and protect the underlying system. Due to some critical limitations of signature-based techniques, anti-virus, and security agency looking for alternative techniques and investing in machine learning based techniques for malware detection.\nThis workshop aimed to train the participants through various steps involved in building malware classifier based on machine learning algorithms. Python is very suitable for the task due to its large number of useful modules suitable for each and every step. During this workshop, following topics will be explained with proper hands-on using Python. Explanation of the topic and draw out the various required steps. Data collection: How to collect Malware and Benign samples for the experiment. Pre-processing: How to carry out various pre-processing tasks\n (duplicate removal, file type identification etc.) to prepare the suitable dataset for the experiment. Labeling: How to label the sample i.e. malware v/s benign. (Required\n for supervised learning.) Feature extraction: How to extract features from the sample and\n build the proper representation of features to be used with various\n Machine learning algorithms. (We will restrict to static features\n for this workshop). Model training and Testing: How to train various machine learning\n algorithms and test their performance to select the best model. Making model persistence: How to make the selected model persistence\n to further use. ", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general. Required module/library:\n1. pefile\n2. androguard\n3. scikit-learn\n4. CS", + { + "Content URLs": "For Reference: https://github.com/Veerskyfire/auth0-pytho", + "Description": "This is introductory talk about the Authentication, where I will discuss about the role that Auth0 authentication plays in modern software development where it is a lot more than just the login screen. You will be able to learn about the different concept of authentication with python and In this talk the audience will learned about the different concepts that make up modern identity important for us to be secure, it will also enable people from the different peers technical as well as non-technical enthusiast to take opportunities to rethink of Authentication process of applications", + "Last Updated": "02 Jul, 2018", + "Prerequisites": "No Prerequisite", "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-malware-classifier-from-sample-collection-to-persistance-model-using-python~eEXWd/", - "title": "Building Malware Classifier: From Sample Collection to Persistance Model using Python" + "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", + "Speaker Links": "Website/Blog\nhttps://www.viralparmarhacker.com LinkedIn\nhttps://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter \nhttps://twitter.com/viralparmarhack GitHub \nhttps://github.com/Veerskyfire/ Facebook \nhttps://www.facebook.com/viralparmarhacke", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Viral Parmar (~Veerskyfire)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/authentication-with-auth0~eE2Ya/", + "title": "Authentication with Auth0" }, - "143": { - "Content URLs": " The main sunpy website - SunPy.org The code repository - sunpy My Experience with working on the SunPy project - Blog SunPy Gallery - Examples My Contributions to the SunPy Project - Code + Examples Contribution", - "Description": "There is plenty much research going on locating sunspot regions or potential regions of high solar density from the solar data collected from observatories like AIA or SDO. Solar Physicists mainly use IDL as a programming language for analyzing such solar data, but using IDL has its demerits due to its less popularity and complexity. So how using python we can benefit the astrophysics and helio-physics community to query solar data and analyze them much more efficiently and produce much more insightful results ? In this talk we will be discussing how we can analyze sunspots and solar flares through image-processing tools using a python package called sunpy . A small example Locating Solar Spikes in the solar Map Original observed AIA image After locating such region", - "Last Updated": "22 May, 2018", - "Prerequisites": " Knowledge of Python (Beginner/ Intermediate) Little bit knowledge about the sunpy package (not mandatory) Python modules like scipy and matplotlib since there is heavy use of this two modules. A lot of excitement and passion for open science", - "Section": "Data science", - "Speaker Info": "Prateek has been an open source enthusiast for the past 2 years with a deep love in the field of astronomy and helio-physics . He is currently an undergraduate in computer science also a GitHub Campus Expert working directly with GitHub Education to build open source communities and support them on campus. He is a core contributor to the SunPy project which is lead by researchers at the NASA Goddard Space Flight Center. He has worked with the community for past 1 year and has his name published for more than 10 releases along with researchers at NASA and others in the community", - "Speaker Links": " GitHub Profile - prateekiiest Twitter - prateekiiest Website - prateekiiest,github.io GitHub Campus Expert - prateekiiest @campus_expert Blog - Medium", - "Target Audience": "Intermediate", + { + "Content URLs": "https://www.slideshare.net/veerskyfire/who-is-spying-on-yo", + "Description": "Topics is about how our privacy is compromised every day, how it happens due to mass surveillance by governments, big tech company, data brokers & 3rd party apps etc., what are our rights to privacy & why it matters, what are the precaution we can take to secure it, secure communication channels like TOR and also will discuss about Broadband Policy, Net Neutrality & Cyber Warfare", + "Last Updated": "02 Jul, 2018", + "Prerequisites": "No Prerequisite", + "Section": "Others", + "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", + "Speaker Links": "Website/Blog https://www.viralparmarhacker.com LinkedIn https://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter https://twitter.com/viralparmarhack GitHub https://github.com/Veerskyfire/ Facebook https://www.facebook.com/viralparmarhacke", + "Target Audience": "Beginner", "Type": "Talks", - "author": "Prateek Chanda (~prateekiiest)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/predicting-sunspots-and-solar-flares-with-a-tinge-of-python~dBXQa/", - "title": "Predicting Sunspots and Solar Flares with a tinge of Python" + "author": "Viral Parmar (~Veerskyfire)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/who-is-spying-on-us~dG2Lb/", + "title": "Who is Spying on us ?" }, - "144": { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "RabbitMQ is a powerful messaging broker based on the Advanced Message Queueing Protocol (AMQP). Microservices do what they say on the tin. They\u2019re small, isolated services that represent an equally small portion of your business domain. Recently there's a trend to build an application using Microservices which place an emphasis on small processes. As an increase in Microservices, we need to a mechanism where we could use some channel(Pub-Sub) to talk between these Services. Contents 1) Introduction to RabbitMQ and Its Terminology 2) Microservices using Pub-Sub 3) Sample Execution At the end of this session, participants will be able to use the rabbitMQ for there application(Could be ETL's/ MicroServices etc", - "Last Updated": "22 May, 2018", - "Prerequisites": "1) Basic Pytho", + { + "Content URLs": "https://www.slideshare.net/veerskyfire", + "Description": "Topic is about how AI and ML are building dystopia for us. The big companies like Google, Facebook, Amazon who are in business of capturing-selling data & our attention to advertisers, gathering our data, harvesting it and use against us to manipulate us & control us. How Social media Ads influence us using its persuasion architecture. Will explain how AI prediction is a threat to our freedom with Case study of smart health care", + "Last Updated": "02 Jul, 2018", + "Prerequisites": "No Prerequisite", "Section": "Others", - "Speaker Info": "My name is Jigar Shah. I have completed my BTech from Walchand College of Engg Sangli. I am currently working as a Software Developer @Browserstack. Interests: Building Backend Architecture, System Design, Data Structures, Algorithms More Inf", - "Speaker Links": "Github Linkedl", + "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", + "Speaker Links": "Website/Blog https://www.viralparmarhacker.com LinkedIn https://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter https://twitter.com/viralparmarhack GitHub https://github.com/Veerskyfire/ Facebook https://www.facebook.com/viralparmarhacke", "Target Audience": "Beginner", "Type": "Talks", - "author": "Jigar Shah (~jigarshahindia)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rabbitmq-in-python-for-event-based-communication-between-microservices~az4qd/", - "title": "RabbitMQ in Python for event-based communication between MicroServices" + "author": "Viral Parmar (~Veerskyfire)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/we-are-building-dystopia-using-ai-ml~dJ2Jd/", + "title": "We are building dystopia using AI & ML" }, - "145": { - "Content URLs": " Will share my slides after my talk as a Github repository.", - "Description": " Abstract This talk is for Python web developers interested in learning what are\nthe core ideas behind microservices, what problems they try to solve,\nand what are the viable options to implement them in Python, both from\ntechnical and teamwork point of views. Some of the topics that will be\ndiscussed include the role of APIs, the improvements microservices\nbring to application scalability, upgrades, and maintenance, and the\nchallenges in breaking up a monolithic application. Contents of the talk About me - Basic introduction of myself. What are Microservices? Monolithic Python Web Application. Problems with Monoliths. Microservice Example. Advantages of Microservices. Disadvantages of Microservices. How to refactor a monolithic application into microservices? ", - "Last Updated": "22 May, 2018", - "Prerequisites": " Basic Python", + { + "Content URLs": "N.A", + "Description": "When I started using Python for scientific computing, it was simply a tool that helped me get the results I needed. It was a simple tool with a large and helpful community. Most of my code was simply an working amalgam of solutions found on Stack Overflow. I didn't take the time to learn about the fundamentals of the language, the tools that the language provided and the best practices. Only after I started working professionally did I take the time out to learn Python at a more basic level. As professional software developers, I think our job is to not just write code that works but to write code that uses the best practices. It's our duty to keep ourselves up to date about the advancements in the language and understand the language and the ecosystem at a more fundamental level. Towards this end, I will talk about a few language fundamentals such as attribute access on classes, decorators and closures in Python. I will talk about best practices such as using list comprehensions instead of explicit for loops. I will introduce a number of packages in the standard library that help write better Python code such as argparse and Path. Finally, I will introduces resources that helped me better understand the language and the ecosystem such as online documentation, books and talks by experts", + "Last Updated": "02 Jul, 2018", + "Prerequisites": "No prerequisites are expected from the audience. This talk will be accessible to developers with all levels of experience", "Section": "Core python and Standard library", - "Speaker Info": " My name is Kasam Sharif (Passionate Programmer | Startup Enthusiast |\nProblem Solver). I am currently Software Engineer at Agrostar, Pune.\nPreviously was working at Symantec having 3 year of experience in IT\nindustry. In free time love to learn new things.", - "Speaker Links": " Linkedln : https://www.linkedin.com/in/kasam-sharif-2027628b/ Twitter: https://twitter.com/kasam_sharif94 Github: https://github.com/kasamsharif", + "Speaker Info": "I'm a Scientific Software Developer. I've been using Python professionally for just over two years. I was using Python for almost 3 years before that for scientific computing. I have a B.S. & M.S. in Physics from IIT Madras.\nI've given a number of talks in the Pune and Chennai Python meetups. I've also conducted workshops at SciPy India, PyCon India and a few other locations", + "Speaker Links": "More information about me and my work can be found at - http://rahulporuri.github.io/\nI occasionally blog at https://rahulporuri.blogspot.com/\nI'm @rahulporuri on twitter and you can reach out to me personally at rahul.poruri@gmail.com ", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Kasam Sharif (~kasamsharif)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-microservices~dyA6d/", - "title": "Python Microservices" + "author": "rahul .poruri (~rahul66)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/growing-as-a-python-developer~aK2Me/", + "title": "Growing as a Python Developer" }, - "146": { - "Description": "Many at times, we need to encapsulate our core logic in order to protect it from being reverse engineered and being exploited. Having a strong IP may not be the only protection. Once the code is open for the analysts, they can easily implement a modified version to achieve their goals. Some areas where the code obfuscation plays an important role are financial domain, security, web/mobile. Many times developers / teams fail to achieve the right level of code obfuscation which in turn fails to provide the level of protection to their code. We will be walking through the existing code obfuscation techniques in python and the level of protection they offer. I will be sharing my experiments and learnings during the journey to achieve a better obfuscation mechanism for python code", - "Last Updated": "22 May, 2018", - "Prerequisites": "Required : None. As we will be covering the required basic for code obfuscation in the talk it self. Good to have : Understanding the python run time process and how the code gets converted to executable binaries can be helpful", - "Section": "Core python and Standard library", - "Speaker Info": "I am Kailash, currently working as a Senior Software Engineer in Visa. I have been into python programming for the past 6 years now. I had worked on multiple levels of python projects ranging from scripting and automation, DevOps, Machine Learning, Computer Vision, Algorithmic Trading, Website Backends", + { + "Content URLs": "https://pytest.org", + "Description": "Nowadays everyone follows agile and care about code quality and testing their code, which gives them the confidence to maintain their application. Do people take shortcuts while writing unit tests? what are the common things to look out for while writing unit tests and good patterns to follow? This talk would be focused on those set of people who already know about unit testing in Python but they often feel the need of knowing the unit test best practices or they question themselves whether they are doing it the right way or not. Writing unit tests for your code is fairly simple but if you don't write them in the correct way or not following some of the best practices then it becomes a nightmare in the long run. Some of the things that will be covered during the talk are, why your unit test suite should be faster, effective usage of mock/stub. During my talk, I'd not only be emphasizing on writing good quality unit tests and would also hope to motivate the audience to follow these practices by showing them some practical use cases. For this, I'll be illustrating real code examples of such scenarios, best practices, and principles during the talk. How do tests help maintain good documentation? Why people suggest following TDD and how tests help to improve the design of your code and maintain for the long run", + "Last Updated": "02 Jul, 2018", + "Prerequisites": "People should be familiar with writing unit tests using any test framework", + "Section": "Developer tools and Automation", + "Speaker Info": "Working as developer at Pramati technologies..Working with python from past 3 years, loves programming and automation", + "Speaker Links": "github - https://github.com/code-R \nlinkedin - https://www.linkedin.com/in/vamsi-krishna-29690614", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Venkata Naga Kailash Anantha (~avnkailash)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/effective-code-obfuscation-protecting-your-python-code-from-being-copied-reverse-engineered~axzld/", - "title": "Effective Code Obfuscation : Protecting your python code from being copied / reverse-engineered" + "author": "Vamsi (~code-R)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unit-testing-best-practices-some-common-pitfalls~dL2Xa/", + "title": "Unit Testing best practices & some common pitfalls" }, - "147": { - "Content URLs": "wikipedia article on the brain computer interface Text Summarizer neural network model code is in the following lin", - "Description": "Brain Mapping Using Python: Over the past few years, machine learning and artificial intelligence has been making headlines and advancing quickly by creating products that can make optimistic decisions. Now this machine learning technology can be implemented in making a machine which can perform complex actions just like in brain which can make human life easier. Now the real challenge is can we create a neural network model which can perform complex\nactions like human brain? How Python can be used to accomplish this task and how far we can achieve this feat?\nThis talk will be focusing on the methods approached by brain to generate conclusions or make decisions which can be replicated in computers and generate results. Contents of the talk About me - Basic introduction of myself. What is Brain Mapping? Functionalities of Human Brain. Neural Networks Using Python. Types of Data Summarisation techniques in Python. How Computers can make decisions. What can we expect from Brain Mapping in future.", - "Last Updated": "21 May, 2018", - "Prerequisites": " basic syntax knowledge of python basic machine learning terminology neural network models functionality", - "Section": "Data science", - "Speaker Info": " ROHITH PUDARI Rohith is a B Tech student who is passionate about integrating the most complex organ known to human which is brain with computers. He is winner of the Hyderabad best coder championship conducted by JNTUH. He is one of the few persons in India who is selected for the google Udacity scholarship. He is always interested in decreasing the interaction gap between computers and humans and started his research in creating an interface which will allow humans to interact with computers in a more natural way. He created a neural network model which generates a summary of a given essay which won the title \"Best innovative idea\" at IIT Kanpur", - "Speaker Links": "you can see the projects and previous work of Rohith in the following link to his github profile. and linkedIn profile Rohith contributed to the following open source projects: Atom- open source code Editor OpenWISP- software platform that implements a complete Wi-Fi service Sugar Labs- desktop environment and learning platform Sustainable Computing Research Group (SCoRe)", - "Target Audience": "Intermediate", + { + "Description": "Introduction to creating RESTful APIs in Python using django framework. This workshop is for everyone who develops web application backends or mobile app backends. Content which will be covered in workshop are as follows: HTTP methods Django Models Request & Response Status Codes Serializers Nested Serializers DRF classy views Hyperlinked APIs Permissions Authentication Authorization Viewsets and Routers In this workshop, we will be building Medium Clone from scratch by creating RESTful APIs", + "Last Updated": "02 Jul, 2018", + "Prerequisites": " Familiarity to *nix operating system. Basic python 3 & OOP concepts. Knowledge about HTTP and web development is plus.", + "Section": "Web development", + "Speaker Info": "Piyush Maurya: Piyush is currently working at Infosys, Mysuru & active volunteer @bangpypers . He has 2.5 years of experience in Python/Django, which includes building college event portal to large scale enterprise. He lives in Mysuru and can be found at every BangPypers Meetup. Nowadays, he is experimenting with Flutter SDK and uses django-rest-framework to build APIs for mobile apps. Karan Shah: Karan is currently working at Infosys, Mysuru. Right now he is exploring Flutter SDK and trying to develop a cross platform app", + "Speaker Links": "Github: https://github.com/piyushmaurya23 Twitter: https://twitter.com/piyushmaurya23 Linkedin: https://www.linkedin.com/in/piyushmaurya23", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Piyush Maurya (~piyushmaurya23)", + "created_on": "02 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/restful-apis-in-python-django-rest-framework-101~aM2Ob/", + "title": "RESTful APIs in Python: Django Rest Framework 101" + }, + { + "Content URLs": "Content will be updated soon", + "Description": "Note:- This talk will be co-presented by Me and Saurabh Ghanekar. Talk Summary:- For a long time we have faced many problems in transferring a file from one place to another without the use of a central server. But with the use of peer to peer, BitTorrent protocol, it is relatively easy for us to share our data. But there is a problem in here. It is not fully decentralized. There are still centralized servers that host these files. Moreover we at our college find it quite difficult to share our study material over LAN as nobody hosts their study materials (duh!!!). So we decided to create a decentralized file sharing application that enables us to share our file to all our friends even if we didn\u2019t hosted it on a server. In this talk we will be explaining the basics of decentralization. We will expand on what and how this could be used to make a file sharing application. We will also shed some light on how to make a fairly secure file sharing application based on the topics we will be covering at the beginning of our talk. Once we are through with the theory and our code, we would be presenting our proof of concept i.e. a small demo of the application. Outcome of the Talk:- After this talk you would expect to learn the basics of decentralized network, how to make a secure decentralized application and successfully learn how to make a decentralized file sharing system. Agenda:- Brief Introduction of Decentralization. [6 min] Basics of File Transfer over a Network. [4 min] What a fairly secure File Sharing Network mean? [5 min] Making and Implementation of making a Decentralized File Sharing Network. [10 min] Making and Implementation of making a Decentralized File Sharing Network. [10 min] A small Live Demo. [3 min] Q and A. [2 min]", + "Last Updated": "03 Jul, 2018", + "Prerequisites": "Love for Pytho", + "Section": "Networking and Security", + "Speaker Info": "This talk is co-presented by Me and Saurabh Ghanekar. Shubham Rao Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData . Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", + "Speaker Links": "Shubham Rao Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitHub E-mail me at : cshubhamrao [at] gmail [dot] com Saurabh Ghanekar Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", + "Target Audience": "Beginner", "Type": "Talks", - "author": "dvlpr_rohith", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/brain-mapping-with-python~bonYa/", - "title": "Brain Mapping with Python" + "author": "Shubham Rao (~shubham66)", + "created_on": "03 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-cool-way-to-share-files-in-this-21st-century~dNRDd/", + "title": "A Cool Way to Share Files in this 21st Century" }, - "148": { - "Description": "In this talk the main aim is to demystify data science and introduce the audience with the concepts of data science and machine learning in python. Goals : What is Data Science ? What is Machine Learning ? Why Python for Data Science ? How to solve a Real world problem with data science ?", - "Last Updated": "21 May, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Data science", - "Speaker Info": "Jatin Ahuja is a self taught data scientist and machine learning practitioner. He's currently working in Data Science domain . He's the core team member (designated as PR Director) and city ambassador of AI Saturdays which is a community of over 5000+ students(over 100+ cities) to spread the knowledge of AI free of cost. He actively blogs about machine learning in his personal blog site named as everythingai . He mentors the aspirants in their journey to become a successful data scientist , machine learning engineer or deep learning engineer at MentorCruise.com ", - "Speaker Links": " Website ; https://everythingai.co.in Github : https://github.com/A-Jatin LinkedIn : https://linkedin.com/in/jatin-ahuja-89677614a/ ", + { + "Content URLs": "if possible download Firefox: https://www.mozilla.org/en-US/firefox/new/ on your computer and/or phone", + "Description": "We as programmers often do not give a lot of thought/importance to our online privacy while using the web. This session/talk will be useful for programmers to guard their online privacy. Consider a programmer using google search engine to search for errors or using stack overflow to find answers to fix a broken python dependency. All of it is stored and profiled against the online identity of the programmer. This data can then be used to sell ads which as we all feel are annoying.\nThis session/talk will help everyone (who uses the web) learn the best practices of anti-tracking, ads blocking, anti-profiling clean browsing environments. We as programmers might be using the same browser for professional and personal work/browsing causing mix-match of data and annoying ads popping up during work sessions. \nThis session/talk will help such programmers keep it all separate via firefox profiles, just like clean python virtual environments :) What will happen during the session? Introduction to Firefox and Icebreaker - 3 mins Customize Firefox, Profiles, and Preferences - 10 mins How you can change Firefox configs to have a more customized and private experience - 10 mins How to block trackers on the web - 10 mins Best Privacy extensions - 5 mins Use of privacy respecting search engines - 5 mins QA - 7 mins This session/talk is for anyone and everyone who uses the web", + "Last Updated": "03 Jul, 2018", + "Prerequisites": " A couple of screens/monitors or a projector at the session will help participants hack, make, learn and share with other participants. Sticky notes Sharpies Optional firefox installed on computers or phones of participants. Open mind", + "Section": "Others", + "Speaker Info": "Ankit Gadgil is an open source and open web advocate who believes the web should be equally accessible to all for equal opportunity. He strongly supports data privacy. Ankit works for Red Hat as a senior software engineer and enjoys working with python, Js, algorithms, and architecture.\nHe usually contributes to open source projects like Mozilla, MediaWiki, Wordpress. He has also served as a member of the Mozilla Reps Council", + "Speaker Links": "Info: https://reps.mozilla.org/u/ankitgadgil/ Twitter: @anknit", "Target Audience": "Beginner", "Type": "Talks", - "author": "JATIN AHUJA (~jatin)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-science-with-python~enm5d/", - "title": "Data Science with python" + "author": "Ankit Gadgil (~anknite)", + "created_on": "03 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-firefox-like-a-boss-privacy-settings~aORYe/", + "title": "Using Firefox like a Boss - Privacy Settings" }, - "149": { - "Content URLs": "https://github.com/atulsinghphd/NL", - "Description": "In this hands-on course using Python, we will learn how to use machine learning for Natural Language Processing (NLP) through interactive notebooks. Natural Language Processing (NLP) is a field that covers computer understanding and manipulation of human language. Machine learning is a branch of Artificial Intelligence that focuses on the ability to automatically learn from existing information. Language processing uses models that attempt to understand and represent the information at various levels that includes morphology, syntax, semantics, pragmatics and discourse. In this training, we will learn how to use machine learning to build these models. This training includes the following topics: Representing text as a vector using count, TF-IDF and co-occurrence matrix Detecting similar documents Sentiment Analysis Identifying the themes in a set of documents Extracting the entities and the relationship between the entities (stretch goal depending on time) The course will introduce the participants to NLP libraries such as nltk, gensim and Spacy", - "Last Updated": "21 May, 2018", - "Prerequisites": "This is an advanced machine learning course. To benefit from this course the participants are expected to have:\n1. Understanding of supervised and unsupervised machine learning \n2. Knowledge of python, or a high-level programming language like Java or C#.\n3. Using jupyter Python notebook environmen", + { + "Content URLs": "Coming soon", + "Description": "Abstract Tox is a generic virtualenv management and test command line tool you can use for: checking your package installs correctly with different Python versions and interpreters running your tests in each of the environments, configuring your test tool of choice acting as a frontend to Continuous Integration servers, greatly reducing boilerplate and merging CI and shell-based testing. Description In this talk we will see what is tox and how we can use it to test our application using different python versions or different Django versions etc., we will see how tox help us in reducing the boilerplate code when integrating with jenkins/travis Outline Introduction to tox (3 min) Diving into tox (how tox works) (5 min) Writing a basic tox configuration - tox.ini (3 min) See how OpenStack leverages tox with Jenkins (4 mins) Some use cases with tox ex: bandit, pep8 (3 mins) Demo (5 mins)", + "Last Updated": "03 Jul, 2018", + "Prerequisites": "Basic understanding or virtual environments and unit testing using python", + "Section": "Developer tools and Automation", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Vamsi (~code-R)", + "created_on": "03 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tox-python-testing-wrapper~dP81d/", + "title": "Tox - Python testing wrapper" + }, + { + "Content URLs": "https://tutorial.djangogirls.org/en", + "Description": "Django Girls is a non-profit organization and a community that empowers and helps women to organize free, one-day programming workshops by providing tools, resources and support.\nYou'll work through a tutorial in small groups with a coach, so you'll be able to learn at your own pace. Every coach will guide their group of attendee and teach them Django. There will be general 2-3 meta coaches to help these coaches. \nDuring Django workshop you will create your website in Django ", + "Last Updated": "03 Jul, 2018", + "Prerequisites": "Basic knowledge of Python will be sufficient", + "Section": "Web development", + "Speaker Info": "As per workshop structure, there is no one speaker. There will be group of coaches, metal coaches, volunteers and organizers. I am final year student of Bachelor of Engineering in Computer. I have organized Django Girls workshop before at our city and it was amazing experience to see 45+ women get inspired and learned. I love contributing to open-source and got my first internship Zulip-Winter-of-Code at Zulip. Also got selected for GSoC-2018-with-Zulip and interned at IIT-Bombay", + "Speaker Links": "Portfolio GitHub Linkedin Django Girls Bhavnaga", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Dave Yashashvi (~dave)", + "created_on": "03 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-girls-start-your-journey-with-programming~aQR0b/", + "title": "Django Girls - start your journey with programming" + }, + { + "Content URLs": "To be updated soon !", + "Description": "90% of data in the internet today is either image or video.The exponential rise of visual data has continuously urged researchers to develop robust and efficient Object detection algorithms,but CNN or R-CNN or YOLO or SSD which algorithm can give best results.In this talk I will try to cover salient features in some of the most influential works in this problem statement.The talk begins with intro to CNNs and goes into detailed discussion of state-of-the-art deep learning algorithms used for object detection. Structure of the talk - The talk is structured into 3 sections :\nIn the first 20 minutes we will have a talk on the architectures, then 10 minutes will be dedicated for some hands-on demo to build a CNN using Keras/Pytorch and the rest of the time will be for QnA. Contents - The talk will begin with a discussion on Convolution Neural Networks and various terms associated like Convolution,pooling,activation used etc and there after discussing about the various state-of-the-art algorithms like R-CNN,Fast R-CNN,Faster R-CNN,R-FCN,YOLO and SSD.One of my analysis criteria will be on their speed at inference allowing real-time analysis. Take aways : What is a CNN,what are convolution,pooling etc. What are R-CNN,Fast R-CNN,Faster R-CNN,R-FCN,YOLO and SSD How to implement a CNN using keras/Pytorch.", + "Last Updated": "03 Jul, 2018", + "Prerequisites": " Basic python or any other language programming. Basic knowledge of Machine Learning and Neural Networks. Most importantly an interest to learn a new concept.", "Section": "Data science", - "Speaker Info": "Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), geo-spatial analytics, and reinforcement learning. Sasidhar Donaparthi I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company", - "Speaker Links": "Linkedin Profiles https://www.linkedin.com/in/sasidonaparthi https://www.linkedin.com/in/atulsinghphd/ Twitter Profiles @sdonapa", + "Speaker Info": "The speaker is a 4th year undergraduate student from the department of Computer Science and Engineering at IIIT Bhubaneswar. He is a Data science, Machine Learning and Deep learning enthusiast.He has an experience of over 2 years in this field and has worked on Machine Learning and Deep Learning and it's application to Computer Vision(CV) and Natural Language Processing(NLP). He has worked on few self projects and been a part of 2 research Internships, One at IIIT Bangalore and another at IIT Kharagpur . He has experience of working with various libraries like sci-kit ,Tensorflow ,Keras ,Torch and Pytorch", + "Speaker Links": "Get in touch with me through LinkedIn Also reach me on Twitte", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Atul Singh (~atul98)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deciphering-human-language-using-machine-learning~bm0Ra/", - "title": "Deciphering human language using Machine Learning" + "Type": "Talks", + "author": "saiamrit", + "created_on": "03 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-detection-demistified-state-of-art-deepnets~dR7Oe/", + "title": "Object Detection Demistified-State of art DeepNets" }, - "150": { - "Content URLs": "I will post presentation and Relevant codes soon on github. For reference please find the code here :\nhttp://magneplane.readthedocs.io/en/latest/index.htm", - "Description": "Content of My talk will have : Hyperloop : An Introduction How Python plays an Important role? Python Applications in the Project: Project Management, \nScripting the repeating processes, \nPython - ML in CFD, \nRaspberry Pi in Communications.", - "Last Updated": "20 May, 2018", - "Prerequisites": "An intermediate level knowledge of Python Knowledge of a Python and basic Math", - "Section": "Others", - "Speaker Info": "Suyash Singh is post graduate Student of Indian Institute of Technology, Madras Chennai. He is Head of Team Avishkar Hyperloop More Details about Avishkar Hyperloop : http://avishkarhyperloop.com/ He carries 4 years of work experience in Big Data and Data Science. Later his interest in fifth mode of transportation took him to IIT Madras. He has been pure pythonist. He has been a adviser to two small scale startups based out of Indore which deals with data science. He has a vision of transforming Transportation making it more efficient. He thinks Python will be an important tool to make it possible", - "Speaker Links": "LinkedIn Profile: https://linkedin.com/in/suyashao", - "Target Audience": "Beginner", + { + "Description": "Short description. Unit testing and continuous integration are core part of any software development team, in this talk you will understand how py.test and pytest-bdd (behaviour driven testing) helps us accelerate this process. Things you'll learn pytest basics, gherkin basics for pytest-bdd pytest Intermediate concepts - fixtures, parametrizing test cases pytest-bdd intermediate concepts - step definition, reusing pytest fixtures Jenkins integration for pytest", + "Last Updated": "05 Jul, 2018", + "Section": "Developer tools and Automation", + "Speaker Info": "I'm the head of technology at TenderCuts and Envee. We are an omni-channel meat delivery startup. At our company we make heavy use of python from our ERP to our mobile app", + "Target Audience": "Advanced", "Type": "Talks", - "author": "Suyash Singh (~suyash_singh)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hyperloop-how-python-helps-building-fifth-mode-of-transportation~el6jb/", - "title": "Hyperloop : How Python helps Building fifth mode of Transportation?" + "author": "varunxyz", + "created_on": "05 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/super-charging-python-testing-with-pytest-and-pytest-bdd-jenkins-integration~eXR5b/", + "title": "Super charging python testing with pytest and pytest-bdd + Jenkins Integration" }, - "151": { - "Content URLs": " Slides on Introduction to NLP : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction%20to%20NLP%20%26%20Spacy.pdf Jupyter Notebook : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction.ipynb Note : The above slides are not complete and are suited for a quick introduction to NLP in 20 mins I will be introducing the following Libraries (and use them to create chatbots) NLTK : https://www.nltk.org/ SpaCy : https://spacy.io/ I will be developing a bot on the following Chat Platforms with emphasis on Messenger: Messenger : https://developers.facebook.com/docs/messenger-platform/ Slack : https://api.slack.com/ Telegram : https://core.telegram.org/bots", - "Description": "Introduction to NLP Natural Language Processing is a prominent field in Artificial Intelligence that deals with parsing and understand Natural language, (an ordinary language such as English is any language that has evolved naturally in humans through use). NLP lies at the core of Google Duplex and other smart assistants that respond to questions in English and natural languages. I will be explaining the following : Corpus and Datasets Processing and tokenizing Text Tagging, Stemming and Lemmatizing Words WordNet Introduction to libraries NLTK Spacy Sentiment Analysis Word Embedding using BOW and word2vec Developing Chatbots With rising need for customer support, Chatbot are one of the most common applications of NLP. These are applications that are trained conversation with a human by answering some preset list of questions. I will be developing a chatbot on three platforms : Messenger (Facebook) Slack Telegram These will be deployed locally using Django with ngrok for tunneling. Additionally, due to the immense popularity of Messenger, I'll be also explaining the different message templates and other features that Messenger has. If you'd like to see me cover another platform such as Discord, Skype, Google Assistant or Alexa, feel free to drop a commen", - "Last Updated": "20 May, 2018", - "Prerequisites": "Basic knowledge of Python, English Grammar and HTTP Requests", - "Section": "Others", - "Speaker Info": "About me Hello world. I\u2019m Vishal Gupta, a 3rd yr CSE undergrad at SSN, Chennai, India. \nWhile most people generally pick up a topic, or a concept (like say Computer Vision, Big Data, or just Algorithms), understand it and aspire to excel at it\u2026 I fell in love with a language, Python. As someone who has started out by learning C++ in school, learning Python was as easy as surprising. The speed at which I could translate ideas to code was amazing, and oh boy, all I wanted to do was make things, write simple scripts to automate everyday tasks. And hence I continued to explore Python, the countless modules and possibilities with Python. I went to Hackathons, won some but more importantly made something that others could use. Chatbots and me UI/UX has never been my strong suit but Chatbots made it simple to use serve any application in a conversational manner. Over the last 2 years, I have developed over a dozen chatbot for a variety of purposes, from fetching torrent links to code education to keeping track of events. One of my best messenger chatbots is still functional with nearly ~500 subscriptions. PyGeon , scrapes a number of sites everyday for developer events such as meetups, hackathons and contests in 7 indian cities. Newly added events are sent to users every day. Experience : Chatbot intern at GoBumpr , Chennai CV intern at XR Labs , Chennai NLP intern at BicycleAI Google Summer of Code participant with Debian", - "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", + { + "Description": "A face animation software which will be very useful in the media and entertainment industry. Here, by just showing your face you can create an avatar", + "Last Updated": "05 Jul, 2018", + "Prerequisites": "Should know basics of Pytho", + "Section": "Core python and Standard library", + "Speaker Info": "A final year BCA student who is very enthusiastic about artificial intelligenc", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Swarnali Singha (~swarnali)", + "created_on": "05 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/face-avatar-using-artificial-intelligence~bYRMd/", + "title": "Face Avatar using Artificial Intelligence" + }, + { + "Description": "Django has swiftly made its way to the top of the web application stack and it is becoming extremely popular among the developers whether freshers or veterans due to its robust framework and inbuilt security features. However, a lot of the developers take this security for granted while developing a web application or an API and therefore often end up with some loopholes that can be exploited by the attackers directly impacting the consumer\u2019s data and the website's reputation. This workshop is intended to talk about those common and uncommon flaws giving special focus to the Owasp Top 10 standards of web application security, use cases where developers might fail to implement them and secure coding practices wrt the same. We will be presenting a live demo on intentionally made vulnerable Django applications with real-life use cases. We will understand how hackers may exploit them, common mistakes developers might make which can lead to a specific vulnerability and how to patch them/build them securely along with secure coding best practices. The demo application will be open source for the audience to try live during the workshop and after it too", + "Last Updated": "05 Jul, 2018", + "Prerequisites": " Beginner level Django and Python knowledge Interest in understanding common attack methodologies and developing secure web applications.", + "Section": "Web development", + "Speaker Info": "Soumya Singh Soumya Singh is a programmer at heart and she has 2+ years of experience in professional Django development and over 3 years experience with Android application development. She is currently working at BugsBounty.com - A crowd-sourced security platform for ethical hackers and organisations where she heads a team to build various security-related products. Besides this, she is LCCSA certified Ethical Hacker and takes cyber security rather seriously", + "Speaker Links": "LinkedIn Profil", "Target Audience": "Beginner", "Type": "Workshops", - "author": "Vishal Gupta (~vishal11)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-nlp-and-chatbots~bkMJe/", - "title": "Introduction to NLP and Chatbots" + "author": "Soumya Singh (~soumya96)", + "created_on": "05 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/owasp-top-10-web-security-loopholes-vs-django-which-is-allegedly-secure-no-matter-who-is-coding-with-it~eZRwe/", + "title": "OWASP Top 10 Web Security Loopholes v/s Django - Which is \u201callegedly\u201d secure no matter who is coding with it." + }, + { + "Content URLs": "Details of this talk can be found on my website. This talk was previously given at EuroPython 2017 slides on speakerdeck video of this talk being given at EuroPython 201", + "Description": "Command execution time can become important in a number of applications. Commands executed in command-line completion need to execute in less then 100ms or users will perceive a delay. In Shell scripting one might want to execute commands repeatedly in a for loop and fast execution times makes this more feasible. Python is a very powerful language but has a much slower startup time compared to other interpreted languages like Perl, Lua and Bash. It can take up to 10 times longer to startup then some of these other languages. MicroPython was written as a lean implementation of Python 3 with a small subset of the standard library mainly intended to run on microcontrollers. But it happily runs on Unix systems with excellent startup performance, making it an ideal candidate for implementing certain time sensitive commands. This talk will: Explain when achieving fast execution times matters and when it doesn\u2019t. Present two different approaches to measuring command execution time, one simple and the other more detailed and accurate. Compare execution times of a simple set of scripts that add two numbers in an number of different interpreted languages (micropython, python3, awk, perl, lua, bash). Present an example use case of MicroPython on Unix. Bash completion for pip install that completes the names of available packages live from a remote pypi mirror. Demonstrate the auto completion script with pip on a local pypi mirror. ", + "Last Updated": "06 Jul, 2018", + "Prerequisites": "Basic understanding of running python scripts on the command line", + "Section": "Embedded python", + "Speaker Info": "I'm a passionate Python developer living on the sunny island of Bahrain. I've been a speaker at Python conferences before and ran the Bahrain Linux User Group for five years. During that period I was a regular speaker at the groups monthly meetups. I\u2019ve taught courses in python programing and computer networking to both students and working professionals", + "Speaker Links": "I've given talks at two python conferences before: EuroPython 2017: Executing scripts in a few milliseconds with MicroPython PyLondinium 2018: Snow globe intruder alert syste", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Marwan Al-Sabbagh (~marwan)", + "created_on": "06 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/executing-scripts-in-a-few-milliseconds-with-micropython~e1DVd/", + "title": "Executing scripts in a few milliseconds with MicroPython" }, - "152": { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "Abstract In this talk, I would be telling people how to write better and faster Python. I've been developing Python programs, scripts and softwares for over 2 years now and I come across people who have a problem of Python being slow. \nWhenever someone has to write a faster python code they are left with one option of just shifting their entire code from Python to C or C++. This talk will clear that misconception. People can actually write faster codes in Python, the only missing fact is how? . And this is exactly why I am interested to give this talk. Contents of the talk The talk will start with a basic introduction of myself as a Python developer. I will then talk about the misconception about shifting the code to C or C++. Then I will proceed onto some basic usage of Python Programming Language. Introduction to optimization techniques in Python. Then I will talk about when and why should one optimize their application. I will introduce the basic concepts of optimization in Python. Tell people about the available/built-in functions that can come in handy. Then I will proceed onto giving a demonstration on 'Writing better functions'. The talk will conclude with some examples of optimized code that performs better than conventional approaches. The talk will be open to questions, to make it more interactive and fun. The slides will be shared to the audience after the talk", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Will to learn See, It does not require much", + { + "Content URLs": "Details of this talk can be found on my website. This talk was previously given at PyLondinium 2018 slides on speakerdec", + "Description": "Learn how to build a snow globe that sounds an alarm and flashes a red alert when intruders are about. Me and my six year old daughter designed and built this project to have fun with friends and learn a bit about computers along the way. Adafruit\u2019s Circuit Playground Express is a fantastic $25 computer packed with sensors, buttons, LEDs and a little speaker. Add this DIY Snow Globe Kit and some Conductive Thread and we have the makings of an ingenious Snow globe intruder alert system. All written in python using a simple text editor without the need for any special software, drivers or soldering. The globe has a rainbow mode that randomly fades different colors in and out and an alarm mode to detect intruders. Modes can be switched by giving the globe a tap which it detects with it\u2019s motion sensors. Once in alarm mode the globe will flash green until an intruder steps on the conductive thread which will sound the alarm and flash the globe red. The Circuit Playground was used to teach my six year old daughter the differences between computer inputs and outputs and how to issue commands to computers using the Python REPL. She learned about the different frequencies of sound waves by calling the beep function with different frequencies. This opened up the topic of the hearing range of humans compared to other animals like dogs. She then learned to set the color of each of the ten NeoPixel LEDs into a rainbow pattern by calling the light function multiple times with each color and position. We explored how any color can be displayed as a combination of red, green and blue by using a digital microscope to see these three LEDs change with different colors. This talk will cover: Tour of the Circuit Playground Express Assembling the snow globe The rainbow and alarm code REPL sound and light with a six year old Troubleshooting tips", + "Last Updated": "06 Jul, 2018", + "Prerequisites": "Basic exposure to python", + "Section": "Embedded python", + "Speaker Info": "I'm a passionate Python developer living on the sunny island of Bahrain. I've been a speaker at Python conferences before and ran the Bahrain Linux User Group for five years. During that period I was a regular speaker at the groups monthly meetups. I\u2019ve taught courses in python programing and computer networking to both students and working professionals", + "Speaker Links": "I've given talks at two python conferences before: EuroPython 2017: Executing scripts in a few milliseconds with MicroPython PyLondinium 2018: Snow globe intruder alert syste", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Marwan Al-Sabbagh (~marwan)", + "created_on": "06 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/snow-globe-intruder-alert-system~b2E1a/", + "title": "Snow globe intruder alert system" + }, + { + "Description": " With the rise of MEAN(MongoDB Express AngularJS NodeJS) stack framework with Python for secure server-side scripting. A simple introduction to using Python Capabilities for Server Management. Using NumPy and SciPy libraries in Javascript.", + "Last Updated": "04 Jul, 2018", + "Prerequisites": "Core Python. Javascript", "Section": "Core python and Standard library", - "Speaker Info": "My name is Manish Devgan . I am a second year Information Technology student at Netaji Subhas Institute of Technology, Delhi . I am an Open Source Contributor and a learner . I have contributed to various different open source projects and won many hackathons . I was FOSSASIA Codeheat 2017 - Grand Prize Winner and Google Code-In 2017- Mentor . Currently I am a GSoC 2018 Student under FOSSASIA and RGSoC 2018 - Coach . I have contributed to Python's ChatterBot Machine Learning Engine , variety of FOSSASIA's Projects , and a wide variety of OSS projects like Github Linguist etc. Python is my favourite programming language . From writing small scripts to building small Machine Learning libraries , I've tried a lot :", - "Speaker Links": " https://github.com/gabru-md https://twitter.com/gabru_md https://facebook.com/gabrumd https://www.linkedin.com/in/gabru-md/", + "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", + "Speaker Links": "GitHub Instagram Emai", "Target Audience": "Beginner", "Type": "Talks", - "author": "Manish Devgan (~gabru-md)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-faster-python-optimizing-your-code~ejJye/", - "title": "Writing Faster Python : Optimizing your code" + "author": "Aniket Chowdhury (~aniket43)", + "created_on": "04 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/integrating-python-with-nodejs~eV9vd/", + "title": "Integrating Python with NodeJS" }, - "153": { - "Content URLs": "Few resources that I will be using in the workshop. https://github.com/koshikraj/proof-of-ownership https://github.com/koshikraj/neo-python-contracts", - "Description": "Bitcoin has been gaining popularity in the recent years due to its market value. But more importantly, the underlying technology is gaining the attention among the developers. Many developer communities inspired by bitcoin have created their own platform to use the underlying technology widely known as \"blockchain\" to achieve decentralization. Ethereum is one such platform that has created a blockchain platform which allows developers to develop their own decentralized applications (dApps) in the ethereum network by coding the logic in the execulatable contracts called \"smart contracts\" . Although ethereum has gained a huge fame due to its smart contract implementation to create decentralized applications, it imposes developer to write the logic in an ethereum's domain-specific language called Solidity. In addition to coding in a new language, it mandates the developer to set up a new develop environment. NEO blockchain platform provides a convenient way to develop smart contracts in general purpose programming language. NEO achieves this by providing compilers to compile code written in most of the languages to bytecode that can be executed in NEO virtual machine. Currently, NEO allows compilation of python smart contracts through neo-python project. This is the first blockchain project to provide such a freedom to the developer. NEO project provides plenty of benefits over other blockchain platforms out there. \nIt plans to achieve smart economy by creating a strong digital identity. It achieves faster transaction rate which is the key to scale any platform. NEO is being referred to as the \"New Ethereum\" due to its increasing popularity. I plan on conducting a workshop to create a decentralized application by developing and deploying smart contract using neo-python. Following would be the agenda of the workshop. Introduction to Bitcoin, Blockchain, and consensus to achieve decentralization. (30 mins) Introduction to NEO and Setting up a NEO platform (30 mins) Creating and deploying Hello World contract using Python (15 mins) Creating a Proof of Ownership system (30 mins) Creating a user interface to create a complete Proof of Ownership DApp. (20 mins) Creating an Initial Coin Offering (ICO) using an existing template and Q&A (25 mins) ** This is a rough estimation of time and topics as of now. I will try to fit more topics if possible. An attendee will be able to create an asset management DApp such as document ownership system or launch a basic ICO after attending the workshop", - "Last Updated": "20 May, 2018", - "Prerequisites": " Novice level experience in python programming. Basic knowledge of how bitcoin or blockchain technology is\n implemented would help to grasp the topic pretty well. Although I will be using Ubuntu Linux distribution for the demo, Attendees can use any platform which has python 3.6 installed. Windows users might have to install a docker container manager as installation might create some issues.", - "Section": "Networking and Security", - "Speaker Info": " I completed my masters in Computer science and Information Security after getting fascinated by the security and cryptography field. I have a demonstrated history of working in the computer and network security industry (RSA Security) where I had worked for more than a year. I worked as a senior fullstack developer for a start-up called CoWrks. In the meantime, I got involved in the blockchain and decentralized application. I started devoting my entire time to blockchain and I'm currently writing a research book on the blockchain technology called Foundations of Blockchain", - "Speaker Links": " My Linkedin profile. Few of my opensource contributions. My semi active social profile. Check out my detailed bio at koshikraj.com", + { + "Description": "The hardest part of building a text classifier is finding labelled data to train the model. The next hardest part is making sure that data is fair and representative. In this talk we will discuss some approaches to rapidly generating corpora suitable for supervised training from public data and with open-source tools. This talk will include some practical tips as well as some less-obvious pitfalls, and is suitable for both novices and more experienced Natural Language Processing Practitioners. At the end of the talk you will be able to give a convincing answer to the eternal question: How do I build a text classifier for a product that doesn't exist yet? Co-presented with Alex O'Conno", + "Last Updated": "06 Jul, 2018", + "Section": "Data science", + "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. He is currently employed as a Machine Learning Engineer with Pivotus where he works on problems in the Natural Language Processing space. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", + "Speaker Links": " My talk at PyCon APAC 2018 An attendee's review of my talk", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Alizishaan Khatri (~alizishaan)", + "created_on": "06 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/something-for-nothing-boostrapping-text-classification~e3GOe/", + "title": "Something for Nothing: Boostrapping Text Classification" + }, + { + "Description": "At Sumo logic which is entirely cloud-based, one component of it resides out of the cloud and rests in the hands of users, in their own infrastructure. This component is sumo's installed collector. This is an installable package for which various forms of binaries get generated in form of rpm, deb, tar, sh, exe and docker images. These packages, along with a plethora of functionalities of the installed collector, need a test bed which not only gives the user freedom to select which tests to run but also which kind of OS the packages might be installed at. We have created a testbed which is multi-platform and runs on the back of AWS cloud infra. The automation testbed has been designed such that we get to write code in a platform agnostic manner, hence the same set of tests can be run in Windows, Debian or RHEL systems. The testbed helps us with managing various versions of installed collectors and help us with verifying our upgrades and various flows across them. We use Ansible for our box setups, of various Linux and windows types, and pytest to write various test scenarios, these tests verify various functionalities of collector along with the installer themselves. Using pytest we can leverage huge armada of python libraries available such as ansible libraries, fabric, sumo's own search, metrics libraries. This kind of test-bed has uniquely brought down our 2 weeks of tests cycles to now less than 3 days and gives us immense confidence in delivering projects at a much rapid pace", + "Last Updated": "06 Jul, 2018", + "Prerequisites": "A beginner's knowledge of ansible and pytest is all people will need to know of", + "Section": "Developer tools and Automation", + "Speaker Info": "Vivek Gupta , Lead QE - platform, Sumologic Vivek has been working with python through most of his career with experience of 7 years in companies like Adobe and Quad Analytix previous to Sumologic. Responsible for Sumologic's entire platform testing, his team works on a wide scope of challenges related to their installers, hosted collectors and their core services. Gourav Garg , QE - platform, Sumologic Gourav has an experience of 1 year and was hired straight out of college. He is responsible for the collection team QE activities along with quite a few QE Jenkins activities at Sumo. He takes care of the entire range of installed collectors as well as hosted collectors", "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Koshik Raj (~koshikraj)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-decentralized-smart-contracts-using-python~egXra/", - "title": "Creating decentralized smart contracts using Python" + "Type": "Talks", + "author": "vivek gupta (~vivek73)", + "created_on": "06 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/multiplatform-automation-test-bed-using-ansible-and-pytest~b4JVe/", + "title": "Multiplatform automation test bed using ansible and pytest" + }, + { + "Content URLs": "The content of the talk will be shared after the session in form of Github Repository", + "Description": "Named Entity Recognition is the task of extracting named entities like Person, Place etc from the text. It is an important step in extracting information from unstructured text data.\n I will explore various approaches for entity extraction using both existing libraries and also implementing state of the art approaches from scratch Agenda for the Talk: Introducing Named Entity Recognition Standard Named Entity using NLTK and Spacy Training Custom Entity Tagger using Spacy or Rasa Standard Algorithms for NER Conditional Random Field (CRF) Deep Learning for NER using LSTM in Keras Structured Deep Learning for NER using LSTM-CRF End-to-End NER via Bi-directional LSTM-CNN-CRF", + "Last Updated": "06 Jul, 2018", + "Prerequisites": "A Basic Knowledge of Python, Machine Learning and Natural Language Processing", + "Section": "Data science", + "Speaker Info": "Subramanya T A is Senior Data Scientist at Sentienz. He heads the Data Science team at Sentienz", + "Speaker Links": "LinkedIn Profile: \n https://www.linkedin.com/in/subramanya-t-a-7306a729/ Sentienz Website:\n http://www.sentienz.com", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "T. A. Subramanya Paddillaya (~t._a._subramanya)", + "created_on": "06 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/named-entity-recognition-in-python~e5gKb/", + "title": "Named Entity Recognition in Python" + }, + { + "Description": "How many times have you banged your head on the wall while using Javascript to build a page showcasing your shiny new Python project? Wouldn't it be great if your blog readers could run and play with the code right away? Fancy running Jupyter-like notebooks entirely in the browser without any server? This talk will get you a headstart into running Python directly in the browser. Agenda Introduction (2 mins) About me Why the Browser is an important stack to target? Three major approaches (20 mins) We will be peeking at the official demo and docs for these projects and dig deeper on how they work. Brief details below : Transpilation - Python code is converted to Javascript before the page is loaded. Examples include PyScript and Transcrypt Python implementation in Javascript - Python code conversion to JS takes place in the browser itself Examples include Brython , Skulpt and Batavia Brython converts Python code into JS in the browser with access to the DOM elements and events The way Batavia works is marvelous! It takes the bytecode for the Python program generated and interprets the Python bytecode as a running program in the browser realtime using a Javascript implementation of the Python VM. Web Assembly - Converting full implementations of Python to run on the web Examples include PyPyJS and Pyodide PyPyJS as the name suggests is the entire PyPy implementation compiled to Javascript. It is PyPy compiled for the web via emscripten, with a custom JIT backend that emits asm.js code at runtime. Pyodide takes this to a different level. It takes the entire Python scientific stack and compiles it to run on the browser using Web Assembly. That means every data library you love - numpy, pandas, matplotlib will run directly on the browser - no installation needed! Conclusion (5 mins) Learnings about Python internals This area is still in its infancy - what to look forward to?", + "Last Updated": "07 Jul, 2018", + "Prerequisites": "General overview of how Python works under the hood - What happens when you run a Python file using CPython, what Python bytecode is etc", + "Section": "Core python and Standard library", + "Speaker Info": "Currently working as a Freelance Python Developer based in Kochi. Originally did Bachelors in Mechanical Engineering from CUSAT.\nI have completed consulting projects in ML and AI with multiple startups and companies. My work on CNNs was the winning solution for IBM\u2019s Cognitive Cup challenge in 2016 and gave a talk on the same at the Super Computing conference SC16 at Salt Lake City, Utah : Slides Previously I was a Technology Innovation Fellow with Kerala Startup Mission where I started a non-profit student community TinkerHub, that has a focus on creating community spaces across colleges for learning the latest technologies. I've been dabbling around with browser technologies since my college days since 2011 being a Mozilla volunteer which got me interested in finding ways to run Python in the browser", + "Speaker Links": "LinkedIn : https://www.linkedin.com/in/praveensridhar/ Previous talks : Anthill Inside talk on Explainability in AI SpeakerDeck", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Praveen Sridhar (~psbots)", + "created_on": "07 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-in-the-browser-run-run-run~b6jVb/", + "title": "Python in the Browser - Run! Run! Run!" }, - "154": { - "Content URLs": " https://github.com/rahulkumaran/Telegram-Syntaxdb-bot There will be some slides that I'll prepare too but most of it is going to be an explanation from the GitHub repo and my talk https://github.com/python-telegram-bot/python-telegram-bot https://syntaxdb.com https://syntaxdb.com/api/v1 https://core.telegram.org/api", - "Description": "In this particular topic, I'll basically be telling people about how easy it is to create a Telegram Bot. The reason I'm interested in taking this up is because there are people who develop beautiful things and might want to let people to use it even on a mobile interface. The problem is not everyone's good with app development. So in such cases, deploying the beautiful things in the form of a bot would be a great idea. Bots can be of 2 types : Conversational Command based I'll be taking up the command based bot to help people get a feeling of this topic. Also, through the example I'll be giving, I'll try to make people understand as to what APIs are and how to use existing one. Later I'll show them how to create your own Python APIs because APIs make lives easier for programmers and it's always a good practise to know how to create an API as you never know when someone else might need it. CONTENTS AND ORDER OF THE TALK I'll be starting off with an introduction about myself and then I'll move on to what are bots. I'll then be explaining about why we could probably use these bots on Telegram, Discord, Slack and so on. Thereafter I'll be talking about the Telegram API for Python to help you interact with the bot and telling you how to use it. Before this, I'll show them how to prepare a bot on Telegram and get the Token. After this, I'll be talking about the importance of an API and utilizing existing ones as it makes your job much simpler. Slowly, I'll shift my focus on to how to build an API. I'll be explaining this using an example. Then using the Telegram Bot API and the API we build for Syntaxdb.com, we'll be creating a Telegram bot. Lastly, I'll summarise and entire talk and will take up a couple of questions. The entire talk will be based on a GitHub repository. The code links will be given to everyone for future reference", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Usage of libraries in Python", - "Section": "Others", - "Speaker Info": "The speaker, in this case is me, Rahul Arulkumaran . I'm an engineering undergrad currently going into my 3rd year. I'm also the Founder of the startup Free Flow . We still haven't registered it yet though. I started learning how to code when I came into engineering and Python was the first language I learnt. I never really developed anything until last year. It was after creating my first application that I got the interest to develop more using Python. From then to now, I've learnt a lot. I might not be an expert but yes, for my age, I think I'm better than most others. I'm also the President of the Computer Science Club, Enigma in my college Mahindra Ecole Centrale . I'm a Python developer and an open source enthusiast . I also am a Contributing and Managing member of PSF . I work on a lot of open source projects I love learning anything and everything related to coding. I'm also a Machine Learning and Data Science enthusiast ", - "Speaker Links": " https://rahulkumaran.github.io https://github.com/rahulkumaran https://www.linkedin.com/in/rahul-arulkumaran-101a63127", + { + "Content URLs": "Find me on Quora My WordPress blog My LinkedI", + "Description": "Computers can tell us whether we\u2019re happy, sad, angry or any of the several emotions we feel. Computers can understand what we\u2019re saying and answer back. How does all this magic happen?\nThis concept of teaching a program to analyze speech and understand it is called speech recognition. I\u2019ll talk about speech recognition and its various nuances, and how it is handled using Python. I\u2019ll also talk about various branches of speech recognition such as speech emotion recognition and text generation based on speech data, and speech recognition implementations on hardware as well. Here is a basic summary of what all I will cover: Speech recognition: what is it, why is it required - concepts like spectral analysis, MFCCs (Mel Frequency Cepstral Coefficients), Fourier transforms, signal processing etc. How Python can make speech recognition easier Branches and new areas of speech recognition: speech emotion recognition, sentiment analysis etc., work done in these fields in the past few decades How speech recognition models are built: acoustic and language models etc. Resources like blogs, libraries, toolkits etc. for studying and getting started with speech recognition models in Python Basic workflow and tips on how to create your first speech recognition model using Python A brief on various repositories of speech databases, how they can be accessed and prepared for input to speech models Speech recognition models implemented on FPGA (hardware), some seminal (and thoroughly comprehensive) research papers to read on the latest work in the field Other media such as video data and face emotion recognition, resources for studying them up further Applications and future scope, closing remarks I will cover the basics of how speech is read, processed and quantified, concepts like the Fourier Transform and spectral analysis, the various Python libraries and resources that exist for the same, and how one can build their own speech recognition system easily. Perhaps an Alexa 2.0", + "Last Updated": "08 Jul, 2018", + "Prerequisites": "Basic knowledge of Python and data science should suffice", + "Section": "Data science", + "Speaker Info": "I am a third year undergrad at Delhi Technological University. I am passionately fond of data science and machine learning, and have worked on several projects and authored research papers on the same. My research area particularly centers around ensemble learning and methods, and I've started taking an interest in speech recognition systems in recent months. I have worked with professors across several universities, and am always up for discussing Python, machine learning and data science with anyone", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-and-working-with-apis-to-develop-a-telegram-bot~dwgXd/", - "title": "Creating and working with APIs to develop a Telegram Bot" + "author": "Anjalib123", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speech-recognition-using-python-how-a-computer-can-tell-if-youre-angry~e7kye/", + "title": "Speech recognition using Python: how a computer can tell if you're angry" }, - "155": { - "Content URLs": "(Slides to be uploaded soon", - "Description": "In computer vision, object detection is scanning and searching for an object in an image or a video (which is just sequence of images). Whereas, object tracking is like you are spying on someone and following it. Done in motion images like in animated gifs or videos, we want to track how an object is moving, where is it going, or its speed. Although it has been studied for dozens of years, object detection and tracking remains an open research problem . The difficulty level of this problem highly depends on how you define the object to be detected and tracked. If only a few visual features, such as a specific color, are used as representation of an object, it is fairly easy to identify all pixels with same color as the object. On the other extremity, the face of a specific person, which full of perceptual details and interfering information such as different poses and illumination, is very hard to be accurately detected, recognized and tracked. Thus, I believe it is important to address such challenges via a comparative study of object tracking and object detection in python. Here, I aim to present my own experience in tackling the problems while I tested different algorithms for the same", - "Last Updated": "19 May, 2018", - "Prerequisites": "Basic understanding of pytho", + { + "Description": "Can we make any machine talk or give speech, naturally like any human ? Can my digital personal assistant like Siri, Alexa etc mimic my voice or give response in my own voice ? Generating human like natural voice has been a topic of research for a long time and a quite challenging task. But recent development in field of Speech Synthesis using advance deep learning technologies has made it achievable. Speech Synthesis has been integral part of any voice driven application. Although we have been able to generate good quality voice using standard method but in reality the generated voice is still too robotic ,emotionless and far away from the actual human voice. In the recent AI development in this field has made it possible to generate expressive human level voice. There are many recent papers like wavenet ,Tacatron and deep voice which do well upon precisely generating actual human voice and even mimic any person voice. In this talk , I will cover literature of voice synthesis and how we can generate human level voice without doing phd in speech processing. Key Components of talk : 1. Understand the basic literature of speech synthesis 2. Components of speech synthesis engine. 3. How to create own voice dataset. 4. Building basic text to speech engine using Tacotron2. 5. Application of real time speech synthesis", + "Last Updated": "08 Jul, 2018", + "Prerequisites": " Basic knowledge of python and jupyter notebook. Familiarity with machine learning components. Basic knowledge of linear algebra, probability distribution and calculus. Knowledge of speech processing is bonus .", "Section": "Data science", - "Speaker Info": "Anand Zutshi is currently pursuing his undergraduate B.E. degree from Netaji Subhas Institute Of Technology, Delhi. He has experience in developing and testing basic as well as advanced algorithms in C, C++. He has experience in developing a Learning Management System which uses dynamically trained neural network for scoring its users, and a LDA based tagging in its queries. He has in depth knowledge of Natural Language Processing, mainly with emphasis on word sense disambiguation and language models. His recent work of interest primarily focusses on object detection and object tracking in Python and sound classification and recognition. Currently, he is working on testing a biometric database management system along with predicting self and non-self processes in Operating system using Neural Networks", - "Speaker Links": "https://github.com/zutshianan", + "Speaker Info": "Myself Rishikesh ! I am working at Humonics Global Pvt. Ltd as Data Scientist. Apart from my job I am actively contributing to open source projects and speaker of many data science communities like PyData Delhi, Delhi Kaggle Group etc. \nMy area of expertise are Speech processing, Data science, Deep learning and statistical modeling ", + "Speaker Links": "Linkedin Githu", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Rishikesh kumar (~rishikesh)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speech-synthesis-engine-for-generating-human-like-natural-voice~e9mBe/", + "title": "Speech Synthesis engine for generating human like natural voice" + }, + { + "Description": "Is there a better time to be a developer! Thanks to Cloud Computing, deploying applications is much more comfortable than it used to be. Serverless computing is an abstraction layer in the cloud. It does not mean that there are no servers, but instead, underlying infrastructure (VM, storage, containers, etc.), as well as the operating system, is abstracted away from the developer. Applications are run in compute containers that are event triggered. Developers have to create functions and depend on the infrastructure to allocate the proper resources to execute the task. Manage the load by creating copies of the functions and scale to meet the demand. OpenFaaS (Functions as a Service) is a framework for building serverless functions with Docker Swarm or Kubernetes which has fantastic support for metrics. We can package/deploy any simple API / service as a function. At a high level in this session: We will discuss and implement a live python function via template and deploy this python functions to Docker Swarm & Kubernetes. We will design and host a page which is broken into many functions. We will touch up the architecture of OpenFaaS and how python community can contribute to OpenFaaS Store We will discuss how to use K8's and it's Operator to push python function using OpenFaa", + "Last Updated": "08 Jul, 2018", + "Section": "Developer tools and Automation", + "Speaker Info": "Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", + "Speaker Links": "https://www.linkedin.com/in/vivsridh https://twitter.com/vivek_sridhar https://github.com/vivsridh4 https://hasgeek.tv/rootconf/2018-day-2/1509-distributed-tracing-with-jaeger-at-scale https://hasgeek.tv/rootconf/cloud-sever-management-delhi/1435-auto-remediation-at-scale-using-watchers-vivek-sridha", "Target Audience": "Beginner", "Type": "Talks", - "author": "anand zutshi (~anand09)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-tracking-vs-object-detection-a-comparative-analysis~avJna/", - "title": "Object tracking vs Object detection- a comparative analysis" + "author": "Vivek Sridhar (~vivek861)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-push-deploy-serverless-python-function-with-openfaas-framework-on-kubernetes~e0Byb/", + "title": "Build, Push & Deploy serverless Python function with OpenFaaS Framework on Kubernetes" }, - "156": { - "Content URLs": " https://pytorch.org/docs/stable/index.html Slides (to be uploaded soon)", - "Description": "Talk Abstract This talk aims to introduce Facebook's Deep Learning library - PyTorch. PyTorch is increasing becoming popular due to it's powerful features and shallow learning curve, making it accessible and easy to use to a larger community. This talk discusses about the 'Autograd' package, which is central to all neural networks in PyTorch. It also entails details about the different features and functionalities of PyTorch as well as equip the audience on how to create simple and complex Neural Networks in PyTorch. PyTorch helps to create dynamic computation graphs that allow you to change how the network behaves on the fly unlike static computation graphs. It offers modularity which enhances the ability to debug or see within the network. Outline of the Talk The talk will be broadly divided into 3 broad parts. Part 1 will be an Introduction to PyTorch. This part will focus on the use and need for PyTorch as a deep learning framework. This will be followed by instructions on how to setup PyTorch and a look at the basic building blocks behind the framework. Part 2 will dive more into the features of PyTorch, mainly it's AutoGrad package which lies at the heart of all Neural Networks created in PyTorch and PyTorch's ability to create dynamic computational graphs as opposed to the static computational graphs offered by some of it's counterparts (such as TensorFlow and Caffe). Part 3 will be a more 'hands on' part where the talk will focus on how to create and build simple as well as complex neural networks (such as Convolutional Neural Networks) with the framework", - "Last Updated": "19 May, 2018", - "Prerequisites": " A basic understanding of how Neural Networks work would be beneficial. Some knowledge about Numpy.", + { + "Content URLs": "To be added soon", + "Description": "Human psychology has remained and continues to remain one of the most challenging areas of research as it aims to understand individual\u2019s behavior and mind, including conscious and unconscious phenomena, as well as feeling and thought. The extent of impact social media has caused on the human mind is huge and perhaps, hard to imagine. Thanks to python and it's brilliant capabilities to process natural language, we can now understand how social media is affecting our lives from a psychological perspective and if it is capable of changing our behaviors, our expressions, our sleeping patterns, or even emotions. From social posts, we can draw interesting conclusions about both men and women if we can comprehend what are the topics they are most interested in, what time of the day are they most and least active etc. Core idea: Collect a dataset from Twitter (or any other social network) of the world's top 400 most influential women for the year 2013 and for the year 2018 Train an NLP model and use this model to classify the collected data under various categories like education, religion, etc. and identify if the post is a concern, compliment, complaint etc. Perform a year-wise trend analysis to identify the topics they are most interested in and parameters like the most/least active time of the day, the most active/least active day of the week the average time spent on twitter per week/month etc. Carry out behavioral analysis by evaluating how the ways of expression, activity levels etc. have changed on social media over the last five years and what might have been the possible reasons for the same Structure: 5-10 mins \u2013 Introduction and discussion ( algorithms and concepts being used ) 10-20 mins \u2013 Code walkthrough followed by discussions on the results obtained (Please refer the core idea section for more details) Remaining time \u2013 Q/A or general discussion Contents: An introduction to natural language processing - text normalization, n-grams, PoS tagging An introduction to deep learning - neural networks and neural language models (framework - keras) A brief discussion on the implementation of a sentiment classifier - Naive Bayes classifier/RNN classifier If time permits, test out a few tweets to understand the working of the classifier Conclusion - how can the results help identify opinions, attitudes, emotional states & future scope (of the project) Note: The entire talk will be a powerpoint based presentation along with illustrative code snippet", + "Last Updated": "08 Jul, 2018", + "Prerequisites": "Python - Beginner/Intermediate Machine Learning - Beginner NLP/Deep learning techniques - Beginner Keras/Tensorflow - Beginner Basic familiarity with the following libraries/tools: 1. numpy 2. pandas 3. matplotlib 4. jupyter noteboo", "Section": "Data science", - "Speaker Info": "I am Rahul Baboota, a 3rd Year Undergraduate in India studying Computer Science and Engineering. I have an avid interest in the domain of Data Science, Machine Learning and Deep Learning. I have worked at various Data Science and Machine Learning based startups and labs. In my freshmen year, I worked at a data journalism startup to create and analyze smart data stories. I was also a part of a project funded by the Government of India for the development of a social media based analytics tool for the analysis of healthcare and nutrition in India. I am currently working at the Center for Artificial Intelligence at IIITD in the Autonomous Vehicle Lab 'Swarath'", - "Speaker Links": " https://www.linkedin.com/in/rahulbaboota/ https://github.com/RahulBaboota", + "Speaker Info": "The speaker of this talk is Reyha Verma . She is currently working as a data scientist at Sprinklr, Gurgaon. Since her organization is the world's best social media management platform, she spends most of her office and her personal time juggling between new, efficient deep learning models and tons of social media data. She is an open-source enthusiast who has also previously been a mentor with Zulip, an open-source python based chat application for FOSS Outreachy program 2016 and has undertaken research projects at National Sun Yat-Sen University, Taiwan and Bhabha Atomic Research Center (BARC), Mumbai while pursuing her undergraduation at the National Institute of Technology, Srinagar", + "Speaker Links": "LinkedIn - https://www.linkedin.com/in/reyhav Github - https://github.com/reyha Twitter - https://twitter.com/reyhav", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "reyha (~reyha)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decode-human-behavior-through-code-a-counter-intuitive-approach~b8lgb/", + "title": "Decode human behavior through code: A counter-intuitive approach" + }, + { + "Content URLs": "1.Understanding Convolutional Neural Networks - CS231n Stanford-http://cs231n.stanford.edu/\n2.Any Deep Learning Library preferably Tensorflo", + "Description": "This talk will cover understanding limitations of Convolutional NN in detecting images. \nAfter understanding this limitation, I will introduce the concept of capsules.\nThis talk is highly inspired from the paper from Geoff hinton- Dynamic routing betwen Capsules-https://arxiv.org/pdf/1710.09829.pdf\nI will try to explain the process of training a multi layer capsule system on MNIST and comparing it with a convolutional net at recognizing highly overlapping images.\nI will use Tensorflow or Keras to show my demo Jupyter notebook.\nI will also discuss the limitations of capsules", + "Last Updated": "08 Jul, 2018", + "Prerequisites": "1.Linear Algebra\n2.Probability and Statistics\n3.Any Deep Learning library (Tensorflow/pytorch/Keras)\n4.Deep Learning layers- Fully connected and Convolutional layer", + "Section": "Data science", + "Speaker Info": "Hi, I am Swapan Jain. After graduating in Computer Science from Delhi Technological University, I self studied AI by reading books,papers and taking courses online. I am a prospective graduate student from fall 2019", + "Speaker Links": "I currently do not have open source contributions, but I will begin the blog from August.\nmy twitter handle is @swapanj162. I will update about my blog or any project on my twitter", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "SWAPAN JAIN (~swapan)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/capsule-networks-overcoming-limitations-of-convolutional-neural-networks~egPGa/", + "title": "Capsule Networks - overcoming limitations of Convolutional Neural Networks" + }, + { + "Content URLs": "Contents will be updated here: https://github.com/dipakkr/pycon-2018 You can also find the presentation here after the session", + "Description": "Computer vision enables the machine to see and analyze objects like humans do. Despite the significant recent advancement in computer vision, implementing it efficiently at a scale presents a serious challenge. Computer Vision deal with techniques like Object Recognition, Object Detection, Face Recognition, segmentation and many more. \nThe best example of this would be a Self-driving car. In this session, we will discuss, how to get started with computer vision using OpenCV. OpenCV is a computer vision library which provides an implementation of the various algorithm on a single call. However, It takes a lot of time and a good understanding of Convolutional Neural Network to build a good computer vision technique. Let\u2019s Start !!!!!! We will also see few demos DEMO - Image Filtering Object Detection Image Recognition", + "Last Updated": "08 Jul, 2018", + "Prerequisites": " Beginner or Intermediate in Python Basic numpy operation Love for Computer Vision and Python", + "Section": "Data science", + "Speaker Info": "a Researcher , Backend Developer , and Machine Learning Enthusiast . I am currently working as Deep Learning Research Intern at MNIT Jaipur . You can find out more about him at : https://github.com/dipakkr https://www.linkedin.com/in/dipakkr/ https://medium.com/@dipakk", "Target Audience": "Beginner", "Type": "Talks", - "author": "rahul baboota (~rahul93)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/throwing-light-on-pytorch~er7La/", - "title": "Throwing Light on PyTorch" + "author": "Deepak Kumar (~dipakkr)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-with-computer-vision-using-opencv~ejPPb/", + "title": "Getting Started with Computer Vision using OpenCV" }, - "157": { - "Content URLs": "This talk is going to be based on a series of blog posts I have written about the same topic - Python Project Workflows - Part 1 Python Project Workflows - Part 2 (Pipenv) Python Project Workflows - Part 3 (pylint)", - "Description": " Have conflicting dependencies (unpleasantly) surprised you? (Darn: It worked on my laptop!) Do deterministic builds matter? What about those run-time errors, which were a typo while accessing an attribute of a class? Has the codebase already started smelling a bit? Unit tests and what about Dockerization? Typically, when your Python project grows beyond a few modules and your team size is more than a couple of developers, having the right tools built into your project development workflow saves one from a lot of surprises (and perhaps late night calls). In this talk, we start with challenges typically seen in Python Projects and look at ways of overcoming them, so that the velocity of code deployment increases. Specifically we are going to be looking at tools that are out there that allow you to - Properly track dependencies ( pip , virtualenv and the new Pipenv ) Have a separate Dev and Production environment - so that dependencies in Dev environment don't spill into Production environment. Ensure that the builds are deterministic (across developer/build machines and time.) Enforce certain coding guidelines and capture the potential 'run-time' errors right during the development ( pylint ) and Eventually Dockerize your application.", - "Last Updated": "19 May, 2018", - "Prerequisites": "It's an intermediate level talk where you have already done some Python development and are at a point where you want to package, distribute or deploy your pet Project. If you are a beginner in Python, but have been involved in build/release of packages in any other languages, likely this talk is for you. If you do an equivalent of sudo pip install or sudo apt-get install when you want to download and use package foo , chances are you will benefit from this talk quite a bit", - "Section": "Developer tools and Automation", - "Speaker Info": "Running a Consulting Company 'hyphenOs Software Labs' in Pune, India. Python/Go programmer - Mostly for things that pay the bills and ideas that I want to try out. Datacenter Networking Enthusiast (hacking a yet another Container Networking technology, borrowing ideas from different Projects) Eternally grateful to whoever wrote tcpdump and the new Wireshark . Number of problems solved using these tools could run into triple digits. Hates trailing white spaces in a file.", - "Speaker Links": " Stack Overflow Github LinkedIn", + { + "Content URLs": "Functional Programming Blog: Functional Programming 101 Took inspiration from Mary Rose Cook and her blog which moved me to write \nFunctional Cod", + "Description": "Introduction This is an intermediate level talk, that\u2019ll help the audience appreciate the Functional Programming Paradigm and how it can be helpful in the day to day scripts that we write.\nIt\u2019ll also touch upon how the concept of functional programming can help elevate the thought process. What can folks expect? To learn what the functional programming paradigm is. To develop the thought process of thinking \u201cfunctionally.\u201d How python can be used to write functional code How day to day work can be made quick and easy The focus of the talk What is functional programming? - 10 mins This segment comprises of exploring what first class objects are and how we\u2019ve been conditioned to think that just variables can be taken as first class objects.\nThen we move on to explore how even functions can be considered first class objects, and what prime features need be followed to be able to say that functions are first class objects. What are first class objects? - 5 mins This segment explains what first class objects actually are and gives a really brief introduction on what makes variables or functions be treated as first class objects. \nThis also include a live coding section, explaining how functions can be: Assigned to a variable Passed as a parameter Returned from another function How does Python fit in? - 10 mins This section showcases the different utilities python inherently provides to support functional programming. It explains how map, filter and reduce, fit in and used in our daily habit of writing code. This also will be accompanied by live code examples and scenarios that we face regularly. We dive a little into partials and look at the tip of the iceberg called decorators. The Whys and Wherefores of Functional Programming - 5 mins This is a segment about various real life experiences; situations where functional programming can be the right tool and where this should be a total no, no. \nLike they say \u201cRight horses for the right courses\u201d, this segment will cover where not to use functional programming and when this debate shouldn\u2019t be brought up. This segment will also cover what is the best place to bring in functional programming and its benefits", + "Last Updated": "08 Jul, 2018", + "Prerequisites": "You should have A basic Knowledge of Python Written about 1000 lines in Python A curiosity to learn more and get better ", + "Section": "Others", + "Speaker Info": "Farhaan is a Software Developer at Clootrack , a Bangalore base startup. He also contributes to FOSS projects and is lucky enough to have few documentation patch in Core Python. He used to heavily contribute to Pagure and still trying to make time to do the same. He actively maintains a blog and indulges in online discussion on twitter. He mentors students to contribute to Open Source Projects, he is also actively involved with Dgplug and is always up on IRC to have a quick discussion", + "Speaker Links": "Website: farhaan.me Functional Programming Blog: Functional Programming 101 Personal Blog Twitter: fhackdroi", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Abhijit Gadgil (~gabhijit)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-project-workflows-continuous-deployment-friendly~bq8ya/", - "title": "Python Project Workflows - Continuous Deployment Friendly" + "author": "Farhaan Bukhsh (~farhaanbukhsh)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-functional-programming-what-when-and-how~bkPNd/", + "title": "Python: Functional Programming - What, When and How?" }, - "158": { - "Content URLs": ">>> import thi", - "Description": "Tim Peters preached and we memorized that Explicit is better than implicit, but how many understood the deeper meaning enough to imbibe the essence of the zen? In this 20 min talk, we shall go through the zen and look at live examples where the golden words make a programmer's life easy", - "Last Updated": "19 May, 2018", - "Prerequisites": "Familiarity with the syntax of Python", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has spent countless hours wading through utterly un-pythonic, non-modular codebases that contain > 8000 lines in one file and >500 in one function, with nested try-except statements and has almost mastered the skill of keeping his calm and understanding even that", - "Speaker Links": "https://anuvrat.i", + { + "Content URLs": " Project source code: https://github.com/sunainapai/makesite Additional material such as slides will be shared after the session in a GitHub repository", + "Description": "The session is about a static site generator named makesite.py that is written in less than 125 lines of code. It is a single Python module that contains everything necessary to develop a static site or blog from scratch. There is no need to read any documentation to understand how it works. There is no need to learn how to write configuration files to produce some desired effect. With makesite.py : The code is the documentation. The code is the configuration. The talk would focus on: A brief code walkthrough of the project that shows how a simple static site generator can be built from scratch without a lot of effort. How this project can be used for your static websites or blogs. Agenda First 5 minutes: Introduction and background: whoami ? What do I do? Prior experience in Python. Problem to be solved: a static site generator written in shell script to be rewritten in a sane language. A new project idea: Write some Python functions to render my static site generator. Scope of the project. Next 15 minutes: Code walkthrough (<= 125 lines of code). A particularly nice pull request from another developer. How to use the project for your own static websites or blogs. Last 5 minutes: Announcing the project on Hacker News and reaction from Hacker News community. Lessons learnt from the experience. Role of the community as a motivator for small projects. What next?", + "Last Updated": "08 Jul, 2018", + "Prerequisites": " Basic knowledge of Python", + "Section": "Web development", + "Speaker Info": "Sunaina Pai is a software developer from Bangalore. She works on big data technologies during the day. In the evening, she dabbles in Python and Lisp to explore the beauty in programming", + "Speaker Links": " LinkedIn - https://www.linkedin.com/in/sunainapai/ GitHub - https://github.com/sunainapai/ Blog - https://sunainapai.in/", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Sunaina Pai (~sunainapai)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/makesitepy-a-simple-lightweight-and-magic-free-static-siteblog-generator-for-python-developers~elPge/", + "title": "makesite.py - A simple, lightweight, and magic-free static site/blog generator for Python developers" + }, + { + "Content URLs": "http://prezi.com/89s2vr6bmar0/?utm_campaign=share&utm_medium=cop", + "Description": "I will be discussing how the use of Python in Africa has grown significantly since 2010 and how, as a result new innovation centers like the High Performance Center in Zimbabwe are beginning to build an industry using it", + "Last Updated": "04 Jul, 2018", + "Prerequisites": "no perquisites require", + "Section": "Others", + "Speaker Info": "Marlene Mhangami is the first African to have been voted onto the board of directors of the Python Software Foundation, the group organization behind the popular computer programming language Python. She is the Chair of PyCon Africa and heads up the Google's Women Techmakers Harare. \nMarlene is also the co-founder of ZimboPy an organization getting Zimbabwean girls excited about code. The organization has been working with girls around Harare to teach them Python programming and is excited about their progress. They also frequently host mentorship weeks and learning programs with local Universities including HIT, the UZ and CUT. Finally, Marlene is also the co-founder of the Purple Lipstick Trust a Zimbabwean non-profit organization that empowers young women to achieve their goals. The organization creates social media content and events that help girls make the best decisions about their lives.\nShe is excited about seeing technology and science used for social good. Marlene is interested in advocating for, and seeing software developer communities grow to create the best environments for innovation to happen! Minority representation in tech spaces is also something she is passionate about and hopes to be part of increasing", + "Speaker Links": "www.linkedin.com/in/marlene-mhangami-90a740130\ntwitter: @marlene_zw or @zimbop", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Marlene Mhangami (~marlene)", + "created_on": "04 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-growth-of-the-python-community-in-africa-and-how-zimbabwe-is-building-one-of-the-biggest-artificial-intelligence-labs-in-the-world~bWRQa/", + "title": "The Growth of the Python Community in Africa and How Zimbabwe is Building One of the Biggest Artificial Intelligence Labs in the World" + }, + { + "Description": "A/B testing is widely used to compare 2 alternatives of doing something in order to find out the best alternative. Typical A/B testing involves statistical hypothesis testing which is not intuitive. On the other hand, Bayesian methods are much more intuitive and are based on less assumptions. This talk aims to give a brief on how to do an A/B test with Bayesian methods using Python", + "Last Updated": "08 Jul, 2018", + "Prerequisites": " Basic understanding of Python Basic understanding of probability", + "Section": "Data science", + "Speaker Info": "Vaibhav Pawar is the head of analytics at Loylty Rewardz. He has 10+ years of experience in using data science to solve business problems across industries like banking, retail, airlines, insurance etc. in the areas of marketing, product, digital and consumer loyalty analytics. He has deep understanding of machine learning techniques and has hands-on experience in automating and deploying ML solutions at scale. He graduated from IIT Bombay in 2008. His master's thesis was in the field of Bayesian networks", + "Speaker Links": "https://www.linkedin.com/in/vaibhav-pawar-588391a", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-python-with-real-life-examples~epVyb/", - "title": "The Zen Of Python: with real life examples" + "author": "Vaibhav Pawar (~vaibhav41)", + "created_on": "08 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bayesian-ab-testing-using-python~bmP9a/", + "title": "Bayesian A/B testing using Python" }, - "159": { - "Content URLs": "Slides: https://docs.google.com/presentation/d/1aE0QmLDffyGRvChqhxaSUWEtBkDqZH5NR3in5FBOPlc/edit?usp=sharing Most of the snippets and concepts to be discussed are taken from various resources I came across during my 6 months long research about Python. I have collected such snippets in a project called \"What the f*ck Python!\". Here's the source: https://github.com/satwikkansal/wtfpytho", - "Description": "Do you know that, 'a'[0][0][0][0][0] is a semantically valid statement in Python. print(r\"\\ some string\") is a valid statement, but print(r\"\\ some string \\\") raises a SyntaxError . print('wtfpython''') is valid but print(\"wtfpython\"\"\") raises SyntaxError . Do you know why, >>> a = \"some_string\"\n>>> id(a)\n140420665652016\n>>> id(\"some\" + \"_\" + \"string\")\n140420665652016 the id of both the objects in above snippet is same? And do you know why, >>> timeit.timeit(\"s1 = s1 + s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.25748300552368164\n# using \"+=\", three strings:\n>>> timeit.timeit(\"s1 += s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.012188911437988281 s1 = s1 + s2 + s3 is much slower than s1 += s2 + s3 . And finally, >>> 'a' * 20 is 'aaaaaaaaaaaaaaaaaaaa'\nTrue\n>>> 'a' * 21 is 'aaaaaaaaaaaaaaaaaaaaa'\nFalse\n\n# one last attack!\n>>> a = \"wtf\"\n>>> b = \"wtf\"\n>>> a is b\nTrue\n\n>>> a = \"wtf!\"\n>>> b = \"wtf!\"\n>>> a is b\nFalse\n\n>>> a, b = \"wtf!\", \"wtf!\"\n>>> a is b\nTrue Do you know the reason behind all the above-discussed facts and snippets? Some of them are really puzzling, right? I felt the same when I first came across all these intricacies. But don't worry, such behaviors, are mostly the consequences of strings being [immutable] [sequences] in Python. In this talk we'll be going through the concepts behind such snippets in detail, so that next time when you see such examples, the answer seems natural to you. Finally, we'll try to answer some interesting questions like, How does string concatenation work? What's the best way of building large strings in Python? (It may actually depend on your use-case) What happens when you multiply a string by a boolean? How strings in Python differ from strings in other languages like JavaScript, C++? and many more", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic familiarity with programming. Prior experience with Python would make the talk more interesting for the attendee", - "Section": "Core python and Standard library", - "Speaker Info": "I'm a Software Developer experienced with Decentralized Applications and Data Science. In my leisure time, I love doing pointless things with programming. Currently on a quest to learn as much as I could about Computer Science. And lastly, I prefer all things Python! (A humble brag ", - "Speaker Links": "Website | Github | Archives Past Speaking Experience PyCon India 2017 (Speaker for a DevSprint ) EuroPython 2017 ( Invited as a Speaker for a workshop , unable to attend though) IWD-Delhi 2018 ( Speaker ) OSS DTU (Instructor and moderator)", + { + "Content URLs": "Participants should know about the classification of text using ML and little knowledge about name entity recognization", + "Description": "So, there will be a simple reminder chatbot made by using a machine learning algorithms. There will name entity recognization and classification algorithms combined to have a chatbot work", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "tensorflow\nkera", + "Section": "Data science", + "Speaker Info": "I am AI enthusiasts. Love to make an end to end AI products", + "Speaker Links": "I am a chatbot developer. https://github.com/sam-a", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Satwik Kansal (~satwik)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/do-you-really-think-you-know-strings-in-python~boJLa/", - "title": "Do you really think you know strings in Python?" + "author": "Sambit Sekhar (~sambit74)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/making-of-chatbot-without-using-any-platform~enPWb/", + "title": "Making of chatbot without using any Platform" }, - "160": { - "Content URLs": " https://docs.julialang.org/en/release-0.4/ https://julialang.org/ Ppt (soon)", - "Description": "Julia Programming Language The Julia programming language is proving to be a new paradigm shift in the data science community due to it's easy to pick up syntax like python but and execution speed equivalent to C , this is possible due to flexible types and JIT compiler. The speed and user-friendliness are only some of its good parts. This talk delves deeper into understanding, how can Julia be the next language on your learning list. Outcomes of the talk What is Julia? How can I get it into my daily workflow What Julia offers that Python does not Understanding benefits of shifting to Julia How can a python-ista shift to Julia", - "Last Updated": "18 May, 2018", - "Prerequisites": " Laptop with Julia up and running", + { + "Content URLs": "Pyqtlet: A library that integrates Leaflet into PyQt Source Code on Github Code for example applications using Pyqtle", + "Description": "Qt is a popular GUI framework used across industries for many different purposes. PyQt is the python wrapper around Qt , and thus it has access to all of the same features. Interestingly, Qt implements the code of Chromium Web Engine, which gives you all the power of a browser, and thus the functionality of any JavaScript library. For the purpose of this talk, we will discuss how to integrate LeafletJS ( a JS library for maps ) into PyQt , thus allowing apps written in native python to have beautiful interactive maps. Then we will go into further details of how to add these maps into simple apps. Finally, we will talk about how to integrate other JavaScript libraries into Python, and all the benefits this can bring", + "Last Updated": "09 Jul, 2018", + "Prerequisites": " A familiarity with Front End Development concepts Beginner level JavaScript Experience with any GUI framework", "Section": "Others", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a recently born Julia-n, I do a lot of code in Julia and move back and forth from Julia to Python to C. I'm a deep learning practitioner and loves Astronomy. I recently got selected into Google Summer of Code under OpenAstronomy org and my project's fundamental language is Julia. I'm a computer science by day and dancer by night. Currently, I'm fiddling with Julia and it's awesomeness and I'll offer you nothing less than awesome", - "Speaker Links": " http://prsr.me https://linkedin.com/in/prakharcode https://github.com/prakharcode", - "Target Audience": "Beginner", + "Speaker Info": "I am a developer at a Banagalore based start-up called Skylark Drones. As one of the few developers in the team, I get to don many hats across domains. I create POC web applications, work on internal tools dealing with GIS, automate processes involving large volumes of data flow and write code that runs on the drone itself. And that's just a typical week. I have been working in Python for over 2 years, and love it. The Zen of Python is essentially my life philosophy and I enjoy the simplicity and expressiveness that the language grants. My interests include: Biryani, Ultimate Frisbee and Hating on JavaScript", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/julia-an-upgrade-to-python-programming-language~enJpe/", - "title": "Julia. An upgrade to Python Programming Language" + "author": "Samarth Hattangady (~samhattangady)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/integrating-js-libraries-into-pyqt~boPBd/", + "title": "Integrating JS libraries into PyQt" }, - "161": { - "Content URLs": "Coming up soon (related to this workshop", - "Description": "Convolution Networks - Framework = Vision in vanilla python. This workshop aims at providing the attendees an experience of implementing convolution neural from scratch without any big framework working in the backend supplementing the need for computation. This would give the attendees an overall understanding of what are Convolution Neural Networks and why do they work so exceedingly well! One does not simply code in vanilla python. What can you expect from this workshop! You'll understand what are convolution neural networks Why they work so well on image data? All the different implementation of Convolution network and how they improve the vanilla network What are the best ways to implement convolution network on a given data What this workshop is not! Just another workshop telling you to use frameworks Maths will not be looked over. (It's important) This workshop is not any other university lecture where you'll not understand anything. I find this image to be so apt given all the abstraction provided by frameworks", - "Last Updated": "18 May, 2018", - "Prerequisites": " Command over Python Familiarity with Numpy and basic math packages Intermediate Mathematics Familiarity with algorithms common in machine learning", - "Section": "Data science", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a deep learning enthusiast who loves mathematics and astronomy. I've been exploring machine learning/deep learning for about 2 years now and fiddling with the basic mathematics and scratch implementations always excite me. I'm currently mentor of deep learning in a Delhi based startup Greatech Soft Solutions and interning at Startup labs and a Google Summer of Code '18 student under the organization OpenAstronomy", - "Speaker Links": " http://prsr.me https://www.linkedin.com/in/prakharcode https://github.com/prakharcode", + { + "Description": "Blockchain is one of the most revolutionary technologies of our times, which is still maturing and with immense potentials yet to be realised. In essence, it is a distributed public database of records which opens rooms for cryptocurrencies and smart contracts to be built on top of it. While the internet is abuzz with blockchain, the concept is difficult to comprehend in its entirety. It lies at an intersection Game Theory, Cryptography, Network and Data Transmission, Economic and Monetary Value, and Trust Systems. It becomes difficult to wrap one's head around each of these domains and get a 360 view of the subject. The workshop tries to help the audience build a comprehensive understanding of the subject, with Python being the programming language. The attendees will leave with a complete picture of the moving pieces of the jigsaw puzzle that blockchain is, and by the end of it will be able to build their own blockchain, cryptocurrency and a smart contract POC on ethereum. The workshop is divided into three parts : Context Building - 45 mins Blockchain fundamentals and principles - 90 mins Coding a smart contract in Vyper (pythonic solidity) - 30 mins 1. Context Building : Basic of Game Theory - Introduction and the Iterated prisoner's dilemma (IPD), creating matches and tournaments using Axelrod python library Cipher encryption and decryption in python Demonstration of network fundamentals and internet data handling Evolution of money and trust systems and why bitcoin is not a mainstream currency When blockchain should be avoided Why decentralisation matters 2. Blockchain with Python: Understanding mining, incentives, payment records, and ownership Programming a basic prototype of a blockchain Adding a proof of work to our prototype Putting our prototype on a database Doing transactions on unique addresses Adding decentralisation to our prototype by distributing it over a network 3. Coding a smart contract with Vyper Understanding what a smart contract is Programming one with Vyper on Ethereum", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "Intermediate understanding of Pytho", + "Section": "Others", + "Speaker Info": "Saket is founder-techie at Sosio . Sosio caters to the large-scale data needs of enterprises in payments, supply-chain, Ad-Tech, and non-profits. He has been programming in Python for over 10 years and has been semi-active in tech-conferences attending and delivering talks across the globe. In his personal capacity, he has introduced Python to more than 500 individuals and conducted training sessions at corporate houses like Oracle. In his previous life, he spent a good chunk of his time optimising computational mechanics algorithms. He is implementing blockchain with one of his supply-chain partners and would like to share his learning experience in the workshop", + "Speaker Links": "LinkedIn Twitter Github SpeakerDeck Medium Instagram", "Target Audience": "Intermediate", "Type": "Workshops", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/convolution-neural-networks-without-any-frameworks~bmX3a/", - "title": "Convolution Neural Networks without any frameworks" - }, - "162": { - "Description": "Sometimes it can be a laborious task for developers to build android apps using Java. Though Java supports Android apps in a powerful way but it also increases the code complexity for a high end app. Now, if you are a python enthusiast and also want to develop Android apps then Kivy comes to your rescue. Kivy is an open source python library for rapid development of cross platform apps. Using the Kv design language and the Kivy framework for Python, you can build amazing interactive multi-touch apps in just a matter of minutes. Kivy framework solves the complexity problem any android developer face while writing complex codes. It also serves the advantage of being cross platform which saves a great amount of time for any app developer. If you love Python, you will also love Kivy", - "Last Updated": "18 May, 2018", - "Prerequisites": "Python Basic Knowledge of Androi", + "author": "Saket Bhushan (~saket)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-and-smart-contracts-from-first-principle-in-python~epPpe/", + "title": "Blockchain and Smart Contracts from First Principle in Python" + }, + { + "Description": "Do you or your team write lots of services? Do you worry about the less glamorous bits about maintaining your service? Is your company growing aggressively and adding code in lots of different programming languages? Are you tired of writing HTTP clients for all your services in every programming language? Do you build your APIs with Python and then write HTTP client code in Java for your mobile apps? Do you want to deprecate your old API but are worried all your clients won't be able to keep up? - Then this is the talk for you. Did you know that you're not the only one who has these problems? Companies big and small struggle with these but most of them seem to have settled on how to approach them. In this talk we'll look at how we can structure our data for compatibility with our present and future clients using Protocol Buffers. We'll also learn how to communicate this data effectively to our clients using GRPC, with almost no effort spent on serialisation/deserialisation. We will also see how we can write services that can be consumed by non-Python clients and how we can consume services written in languages other than Python but without having to learn a new language or a clunky framework. The goal is to build a service that is easy to write, easy to consume and scales very efficiently as the problem grows. In short, we'll learn to do more with less. This will be a demo-driven talk with few slides. We will look at and write real Python code that gets things done", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "Basic understanding of REST over JSON would be helpful, but is not necessary. We will cover the basics at the beginning of the talk. Basic understanding of Python classes would also be helpful, but is also not necessary. No other pre-requisites", "Section": "Web development", - "Speaker Info": "The speaker goes by the name amanraj209 all over the web. I've been interested in learning new technologies since high school and I've been developing apps using Python, Javascript, Java, Go since the last 3 years. I've also done some small projects in Machine Learning. Being a developer gives me a great sense of feel to build apps for the users and contribute to the community. It has always been my passion to dive into the technology and contribute to the community something useful", - "Speaker Links": "Github: https://github.com/amanraj209 LinkedIn: https://www.linkedin.com/in/amanraj209 Facebook: https://www.facebook.com/amanraj20", + "Speaker Info": "Hi, I've spent almost all my adult life building distributed systems and understanding how they work. I've worked on interesting problems almost exclusively in a polyglot environment and this often reflects in the code I write or my approach to dealing with problems. I've debugged strongly consistent* key-value stores, run container orchestration systems at scale and broken my foot once from falling down a stairwell. I work with Grofers trying to make developers more productive and infrastructure more reliable. I look forward to seeing you at PyCon Indi", + "Speaker Links": " https://kasisnu.com https://www.linkedin.com/in/kasisnu", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Kasisnu Singh (~kasisnu21)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/protocol-buffers-and-grpc-building-friendly-services~bq90b/", + "title": "Protocol buffers and GRPC - Building friendly services" + }, + { + "Description": "Submitting a proposal for to deliver a talk on \u2018EEG based Cognitive Brain Mapping using Python\u2019 under the broad area of signal processing. An intensive and in-depth theoretical and practical aspects in EEG signal processing for different research applications will be discussed. The development of a brain computer interface using EEG for control applications shall be explained with relevant research results. The demonstration to control the interfaced hardware using acquired brain signals via EEG shall be provided. The talk is intended for beginners in EEG signal processing but intermediate users will find it informative as well. Cognitive neuroscience is being widely explored these days to develop more interactive brain computer interfaces (BCI) particularly for device control applications. Neural driven BCIs are gaining importance while providing assistance especially to paralytic/ physically locked-in patients in order to restore a useful life. An attempt shall be made to explain that how a cognitive activity of human subjects and associated neural activation captured via electroencephalography (EEG) vcan be translated into action. A framework to develop an automated control application environment using Python shall be discussed in detail . The analysis of a multichannel EEG dataset acquired from human subjects shall be explained and discussed in Python environment to extract the relevant features to develop possible control applications via hardware interfacing through Arduino. The proposed methodology can be utilized to offer patients with severe motor neuron disorders an alternative means of communication and control over their environment via applications for neurorehabilitation of motor and cognitive functions", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "Biomedical signal processing\nBasic Pytho", + "Section": "Others", + "Speaker Info": "Rashima Mahajan (PhD ECE)\nAssociate Professor\nFaculty of Engg and Technology\nManav Rachna International Institute of Research and Studies, Faridaba", "Target Audience": "Beginner", "Type": "Talks", - "author": "Aman Raj (~amanraj209)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/developing-android-apps-using-kivy~el61b/", - "title": "Developing Android apps using Kivy" + "author": "rashima", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/eeg-based-cognitive-brain-mapping-using-python~er64e/", + "title": "EEG Based Cognitive Brain Mapping using Python" }, - "163": { - "Content URLs": "Shall be updated soon", - "Description": "You have got this super awesome REST API served through Django/DRF based project and suddenly these requirements come in: We need to have a local support for Chinese language! In case, you've not written your application with localization and internationalization in mind, then \"Boy! You're in danger! You should better start praying to almighty to give you strength and endurance to support yet another language in your app\". In this talk, we'll see how do we support localization and serve our app in different languages, based on what language the client wants to communicate in. As a backend, we should be language agnostic and allow all clients to communicate with us in one of the languages we support. We'll see how to support translation for static data (using makemessages / compilemessages) and dynamic data, using various third-party services such as django-translations and transifex. Here, static data is translations for all the fields, error messages etc. that the app already has and dynamic data is the custom data input by the user in the app. This would enable you to have your admin panel, as well as RESTful APIs, served in different languages", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic knowledge of Python and Django", - "Section": "Web development", - "Speaker Info": "Why do you want this person to speak? Sanyam is a self-taught programmer with a \"can-do\" attitude who developed his interest in Computer Science and Software Development over the years. He mostly goes by CuriousLearner all over the web and you might run into him at various Python Conferences and local meetups. In his free time he contributes to FOSS. Some of his noticeable contributions are in Gecko Engine from Mozilla and CPython. You can read about his latest hacking CPython and other projects at http://www.SanyamKhurana.com/blog & http://medium.com/@CuriousLearner Highlights : Goes by CuriousLearner all over the web. Bug Triager and contributor to CPython (bugs.python.org) GSoC 2018 Mentor for Debian RGSoC 2016 Mentor Mozilla Reps Mentor and contributor to Mozilla's GeckoEngine, Add-ons ecosystem, and other few projects. Core-organizer for PyCon India 2016 & PyCon India 2017 Volunteer for PyCon India 2015.", - "Speaker Links": "Blog: http://www.SanyamKhurana.com/blog Website: http://www.SanyamKhurana.com Github: https://github.com/CuriousLearne", + { + "Content URLs": "https://speakerdeck.com/siliconsenthil/how-we-built-heroku-like-paas-over-aws-with-just-pytho", + "Description": "We wanted an easier way of creating and deploying microservices implemented in different tech stacks. We wanted it as simple as PaaS platforms like Heroku. On the other hand, we did not want to miss the high level of customizability with IaaS like AWS. So, we blended the benefits of these two. i.e. utmost convenience with high-level of customizability. Instead of taking the route of Puppet, Chef, Ansible etc. , we built a CLI tool in Python that enables our developers to create & deploy service with a single command. We call this cloudlift :). It's been more than a year since we started using it and it's been fantastic. You will learn about our journey of building and using cloudlift", + "Last Updated": "09 Jul, 2018", + "Prerequisites": " Python Basics of AWS ecosystem", + "Section": "Developer tools and Automation", + "Speaker Info": "Converting human aspirations into reality via software has been my fascination and my job. \nHave been a programmer for more than a decade and leading teams for a while now. \nWorked at ThoughtWorks for 8 years. Currently, I lead the engineering team at Simpl. Have lead projects that are diverse in terms of tech stack and scale. Worked for enterprises and startups.\nInterested in talking about on design, technologies, the philosophical angle of tech etc.\nBelieve software building is a unique combination of science, art, and collaboration", + "Speaker Links": "http://siliconsenthil.i", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Senthil Velu Sundaram (~senthil13)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-we-built-heroku-like-paas-over-aws-with-just-python~avk0b/", + "title": "How we built Heroku-like PaaS over AWS with just Python" + }, + { + "Description": "Python 3.5 RC introduced type hints in the standard library, since then a lot of projects use Python hints in the code. The large open Python source projects like Zulip use it. For past one year, at work, I have been using Python type hints in the data pipelines and neural networks. The talk is based on the experience. In this talk, I'll cover the following topics. Code before and after using type hints. Advantages of using type hints Pain points of using type hints Developers view of using type hints Second thoughts of using type hints", + "Last Updated": "09 Jul, 2018", + "Prerequisites": " You should possess familiarity with Python, and grasp of the type system.", + "Section": "Core python and Standard library", + "Speaker Info": "I'm kracekumar, working as software engineer for past seven years. My experience has been around building web applications, data pipelines, and automating servers. Currently, I work as a Software Engineer at minds.ai", + "Speaker Links": " GitHub", "Target Audience": "Beginner", "Type": "Talks", - "author": "Sanyam Khurana (~CuriousLearner)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-multilingual-superhero-in-django~bkMve/", - "title": "Becoming a Multilingual SuperHero in Django" + "author": "Kracekumar Ramaraju (~kracekumar)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/experience-with-python-type-hints~dwl1e/", + "title": "Experience with Python type hints" }, - "164": { - "Content URLs": " http://haridas.in https://github.com/haridas", - "Description": "Data-science mainly involves understanding your data and identify suitable models based on the data. Mastering the standard tools like pandas and seaborn will be key to gain insights about ML problems. This tutorial coverers, Basics of pandas and seaborn Different plotting patterns using seaborn for your data. Plotting Single and bivariate distributions, categorical plots with distribution. Understand two variable behaviour using regression plots. One usecase:- How I decided to buy a petrol car instead of diesel car by analysing my fuel spending.", - "Last Updated": "17 May, 2018", - "Prerequisites": "Lapatop with following packages installed. pip install seaborn pand", + { + "Description": "Most of us use micro-services for all the goodness that they bring in. But there are some pain points too, to be addressed while using multiple micro-services. One of the them is testing. With all the micro-services as moving parts, how does one ensure that the whole app is coherent and well tested ? Is it enough if all the unit tests pass in each micro-service code base ? What else do we need to be confident in order to ship the code like a boss ? Outline of the talk Challenges in testing micro-services Consumer driven contract (CDC) tests - what are they, how they work ? How Pact works and what are the available tools in Python ? How are CDC tests simpler than integration tests ? Best practices in maintaining the pact file Demo: how to write CDC tests with Pact for a simple micro service", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "Awareness of micro-service environments or APIs would be helpful", + "Section": "Developer tools and Automation", + "Speaker Info": "Devi is an independent software consultant and trainer with an experience of more than 12 years in the industry. She has been working with PowerToFly as a lead developer/architect. She has given a couple of talks at PyCon India, RootConf before, which were well received. She has done M.Tech in Computational Science from IISc, before which she tried out teaching mathematics. She spends her free time enjoying with her 2 daughters and painting with water colors", + "Speaker Links": " https://www.linkedin.com/in/asldevi/ https://powertofly.com/talents/devia https://speakerdeck.com/asldevi/rest-apis-at-pycon-india-2015", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "asldevi (~asldevi)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/testing-micro-services-made-easy~axm3b/", + "title": "Testing micro-services made easy" + }, + { + "Content URLs": "The content of the talk will be shared after the session in form of Github Repository", + "Description": "Deep Learning has revolutionized areas like Speech recognition. Recently, deep learning approaches have obtained very high performance across many different NLP tasks.\nIn this workshop, we will see the application of deep learning to common NLP Tasks and implementation in python using Keras Library. Agenda for the Talk: An Introduction to Deep learning - MLP, CNN and RNN and its implementation in Keras Discussion of Common NLP Tasks Language Modelling with RNN Word Embeddings - Word2Vec and Glove Sentence Embeddings - WMD and Doc2Vec Embed, Encode, Attend, Predict - Deep Learning formula for state of the art NLP Models Text Classification with 1D-CNN and LSTM Sentiment Analysis with Recursive Neural Network and Tree-LSTM Building Question Answering with Bi-Directional Attentional Flow Model Entity Extraction using Bi-LSTM and CN", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "A Basic Knowledge of Python, Machine Learning, Deep Learning and Natural Language Processing", "Section": "Data science", - "Speaker Info": "Haridas is a Principal Engineer in Pramati Technologies, part of Labs team. He has 8+ years of experience in multiple domains like, Web development, SOA, ML, Devops. He has been working extensively in different ML use-cases and applying them in real scenarios", - "Speaker Links": " http://haridas.in Twitter @haridas_n", + "Speaker Info": "Subramanya T A is Senior Data Scientist at Sentienz. He heads the Data Science team at Sentienz", + "Speaker Links": "LinkedIn Profile:\n https://www.linkedin.com/in/subramanya-t-a-7306a729/ Sentienz Website - http://www.sentienz.com", "Target Audience": "Intermediate", "Type": "Workshops", - "author": "haridas n (~haridas)", - "created_on": "17 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/find-patterns-in-your-data-using-seaborn-and-pandas~ejJ4e/", - "title": "Find patterns in your data using Seaborn and Pandas" - }, - "165": { - "Description": "DevOps is gaining momentum and we at Microsoft want our users to have great CI/CD story for any language targeting any platform. In this session, we will be talking about how easy is to get started on Cloud and DevOps for Python developer in this new generation of Microsoft We're going to start from scratch and before we're done we will use Visual Studio Team Services (VSTS) to setup Continuous Delivery for Python Applications on Cloud and demonstrate the DevOps strategy in action. The solution grows up to the most demanding needs of a modern software developers powered by VSTS. Whether you are starting new, bringing your own tool chain or inter-operating with existing tools and assets, you can accelerate your delivery of value with Azure and VSTS", - "Last Updated": "16 May, 2018", - "Prerequisites": "N", - "Section": "Developer tools and Automation", - "Speaker Info": "Alok Agrawal is Product Manager for Microsoft Visual Studio Team Services where he and his team are building next generation cloud based developer tools. He has been with Microsoft for over 7 years. Previously he has worked with Windows Application Compatibility and Azure Application team. Alok has Bachelor's degree in Computer Science and completed his business management from IIM Calcutta", - "Speaker Links": "http://www.imalokagrawal.com https://twitter.com/imalokagrawal https://github.com/imalokagrawa", + "author": "T. A. Subramanya Paddillaya (~t._a._subramanya)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/applying-deep-learning-for-nlp-using-python-workshop~dynEe/", + "title": "Applying Deep Learning for NLP using Python - Workshop" + }, + { + "Description": "Description \u201cTradition is not to preserve the ashes, but to pass on the flame\u201d. Running Python coding workshops in areas with unreliable internet access and with outdated hardware among the participants present a challenge for capacity building and knowledge sharing. Jupyterhub run in a local area network can bridge this gap and therefore make your workshops more resilient. Contents The talk will demonstrate how to set up and run a workshop successfully in an environment without internet access and the absence of uptodate hardware on real-life projects using Python, PySpark and Jupyterhub. Contentwise the session focuses on data science and the preprocessing of mobile phone metadata in order to extract features. The talk will include time for Q&A. Take aways What are the challenges running a coding workshop in adverse\n environments? How to set up a Jupyterhub in a local area network?", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "Interest in spreading your own knowledge to people beyond the usual suspects", + "Section": "Data science", + "Speaker Info": "We are a young university spinoff project of the department of statistics of the Freie Universit\u00e4t Berlin, Germany called \u2018knuper\u2019. We work with governments around the world by augmenting official statistics with mobile phone metadata and other big data sources", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Alok Agrawal (~imalokagrawal)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-plumber-building-deployment-pipeline-in-minutes~e03Nd/", - "title": "Becoming a Plumber: Building deployment pipeline in minutes" + "author": "knuper", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/coding-for-everyone-setting-up-coding-workshops-in-challenging-environments~azoZb/", + "title": "Coding for everyone - Setting up coding workshops in challenging environments" }, - "166": { - "Content URLs": "Workshop Content: https://github.com/openfaas/workshop OpenFaas Docs: https://docs.openfaas.com/ OpenFaas Website: https://www.openfaas.com", - "Description": "OpenFaaS makes Serverless Functions simple with any programming language through the use of Docker containers. The project can be hosted on any cloud, or on your own hardware - even your laptop. Learn how to build Serverless functions with OpenFaaS and Python in this self-paced workshop lead by the community behind the project. Start by deploying OpenFaaS to your laptops with Docker for Mac or Windows and then learn how to build, deploy and invoke serverless functions in Python. Topics will include: Managing dependencies with pip, dealing with API tokens through secure secrets, monitoring functions with Prometheus, invoking functions asynchronously and chaining functions together to create applications. We\u2019ll finish by building a GitHub bot that puts all of what we\u2019ve learnt together into a single application. The issue-bot will respond to issues raised by analysing the text and deciding whether to label them positive or for review. The workshop will have following labs: Prepare for OpenFaas Test things out Introduction to functions Go Deeper with functions Create a Gitbot HTML for your functions Asynchronous functions Advanced feature - Timeouts Advanced feature - Auto Scaling Advanced feature - Secrets", - "Last Updated": "16 May, 2018", - "Prerequisites": " Basic knowledge of Docker Functions will be written in Python, so prior programming or scripting experience is preferred. Requirements: Install the recommended code-editor / IDE VSCode MacOS, Windows 10 Pro/Enterprise, Ubuntu Linux For Windows install Git Bash Docker CE for Mac / Windows Edge edition Docker CE for Linux As a last resort if you have an incompatible PC you can run the workshop on https://labs.play-with-docker.com/ . ", + { + "Content URLs": " https://medium.com/@anandology/designing-restful-apis-671e091a2561 https://github.com/anandology/restful-apis/", + "Description": "APIs are all around. Everyone talks about RESTful APIs, but what does \u201cRESTful\u201d really mean? This hands-on workshop takes you through everything that you need to know to design great RESTful APIs. During the workshop, the participants will understand the key concepts behind RESTful APIs, critically examine some of the popular APIs, design an API from scratch and see how APIs evolve. We'll also take couple of popular APIs, rip them apart and design a better version of them. Participants will be divided into smaller groups to allow discussions and most of the time is spent thinking about the design. Please note that this is about designing APIs, and not about the tools. Participants will spend lot of time thinking about and designing API endpoints and request/response format, but will not write any code. OUTLINE Introduction to HTTP Internet vs. World-Wide-Web Key Concepts of Web URL, HyperText, HTTP Representational State Transfer (REST) What is REST? Thinking in Resources HTTP Methods Status Codes Resource Representation Examples of RESTful APIs Good and bad examples of RESTful APIs Designing an API version 0 - Naive CRUD API for blog posts. version 1 - blog api made RESTful version 2 - add support for tags version 3 - add support for comments version 4 - add suport for authors Authentication and Secutity Introduction to authentication patterns Study of Basic Auth, OAuth, access keys and JWT Adding authentication to the blog API Excercises Best Practices Pratical tips and tricks Versioning APIs Documenting APIs ", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "The workshop is targeted at web developers interested to build APIs. The participants are expected to have good understanding of how web works", "Section": "Web development", - "Speaker Info": "Vivek Singh: Currently working as Software Engineer - II at Akamai Technologies. Been an active contributor to OpenFaaS project. Loves to code in Python and Golang. Contributes to Open Source projects in free time. Vivek Sridhar: Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "My contributions: https://github.com/viveksyngh LinkedIn Profile: https://www.linkedin.com/in/viveksyngh/ Twitter: https://twitter.com/viveksyngh Website: https://www.viveksyngh.info Blog: https://www.viveksyngh.info/blog", - "Target Audience": "Beginner", + "Speaker Info": "Anand has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, rorodata , which he recently co-founded. He regularly conducts advanced programming courses through Pipal Academy . He is co-author of web.py , a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive", + "Speaker Links": " https://anandology.com/ https://pipal.in/trainers/anand https://github.com/anandology", + "Target Audience": "Intermediate", "Type": "Workshops", - "author": "Vivek Kumar Singh (~viveksyngh)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-serverless-with-openfaas-and-python~e9Xzd/", - "title": "Hands-On Serverless with OpenFaaS and Python" - }, - "167": { - "Description": "The human voice is becoming an increasingly important way of interacting with devices, but current state of the art solutions are proprietary and strive for user lock-in. Mozilla\u2019s DeepSpeech and Common Voice projects are there to change this. In contrast to classic STT approaches, DeepSpeech features a modern end-to-end deep learning solution. Based on Baidu's Deep Speech research paper, it trains a model by machine learning techniques. This model directly translates raw audio data into text - without any domain specific code in between. To train systems like DeepSpeech, an extremely large amount of voice data is required. Most of the data used by large companies isn\u2019t available to the majority of people. That's why Mozilla launched Common Voice, a project to help make voice recognition open to everyone", - "Last Updated": "16 May, 2018", + "author": "Anand Chitipothu (~anandology)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-restful-apis~aAx3e/", + "title": "Designing RESTful APIs" + }, + { + "Description": " Introduction to ensembling techniques About XGBoost Parameters and their tuning Application using python Latest updates", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "Basic knowledge of python and machine learnin", "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune, and a Mozilla TechSpeaker. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": "Mozilla Research machine learning home page: https://research.mozilla.org/machine-learning/ Speaker's LinedIn: https://www.linkedin.com/in/shaguftagurmukhdas/ Speaker's twitter: https://twitter.com/shaguftamethwa", + "Speaker Info": "Ina Jain is currently working as a Data Scientist in Pramati technologies and has 6+ years of industry experience", + "Speaker Links": "https://www.linkedin.com/in/inajain27", "Target Audience": "Beginner", "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mozillas-deepspeech-and-common-voice-projects~e7JBd/", - "title": "Mozilla's DeepSpeech and Common Voice projects" + "author": "ina jain (~ina)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/xgboost-tree-based-ensembling-technique-using-python~dBykb/", + "title": "XGBoost - Tree based ensembling technique using Python" }, - "168": { - "Description": "You only look once (YOLO) is a state-of-the-art, real-time object detection algorithm. The model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image. It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. This makes it extremely very fast. This talk teaches you to develop your own real-time object detection python application to detect and classify objects in images as well as videos in real-time, which you can use in your next self driving car", - "Last Updated": "16 May, 2018", - "Prerequisites": " Knowledge of basic Python and its syntax Idea/Overview of deep learning as a technology", - "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune. I'm currently working in HSBC Technology India, as a software developer. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": " LinkedIn Twitter Recent talk on WebVR", + { + "Content URLs": "Slides Ur", + "Description": "Ever wanted to play your favourite song on guitar quickly even when you don\u2019t know how to play guitar? Our Python based MIDI to guitar tabs Transcriber can help you do that: \u2022 Find your song in MIDI format (with .mid as file extension) \u2022 Let our Python Transcriber do its magic \u2022 Enjoy the tablatures Transcribing MIDI files directly to tablature creation ready JSON A lot of people take to learning the guitar every year. But most of them give up mid-way because of one or more of the following reasons: Guitar is a difficult instrument to learn People want to learn guitar by playing songs but are unable to do so right from the beginning Results are often not visible immediately depending on a person's existing knowledge of music and willingness to learn guitar Enter Python Though it seems to be quite easy to manually create and make the app read guitar tablatures for songs, the following challenges need to be addressed: Readiness of the output to support playback of a song along with tablatures - this essentially means storing the timing for each note/chord (when many notes are played together) in order to play the song exactly as it is The whole process would be incredibly time consuming In order to overcome these challenges, a simple yet efficient solution was derived - to convert a MIDI file directly into guitar tablatures. Python was chosen for implementation of the solution for the following reasons: Python has a very efficient and time saving file I/O mechanism and the current use case operates completely on MIDI files and the Transcriber outputs a JSON file, which in turn is served to the client. More libraries to read MIDI files and present them in an understandable manner than any other language and their ease of use. These libraries, when used in conjunction with each other offer all the features that Java's javax.sound.midi package offers. Availability of renowned libraries such as numpy and scipy for the algorithm to determine most optimal finger positions A plethora of options for using a server side framework to host the Transcriber as a service Since Python is an interpreted language, it is really useful for quick experimentation with tools like IPython unlike languages like Java in which complete programs need to be compiled beforehand. This saved us a lot of time. ...Where Credit is Due The solution could not be achieved without the use of the fantastic libraries used below for reading MIDI files: Mido by olemb Python Midi by vishnubob music21 by Prof. Michael Scott Cuthbert (MIT) The authors have our gratitude. How the Transcriber Works The high level working of the Transcriber is as follows: MIDI files are read and all the guitar parts in the song (commonly referred to as guitar tracks ) are extracted in the form of notes and chords An algorithm calculates the best possible finger placement on the guitar fretboard for these notes and chords A time driven JSON is generated for use by any platform that can parse JSON to do one or more of the following: Play the song Display guitar tabs in sync along with song playback Only display guitar tabs Why Use the Transcriber? Some work has already been done in this area and there are existing open source solutions like TuxGuitar and a few others. But the Transcriber here produces up to 70% better results than any of these solutions. By better , the following is meant: Transcriber generates more easily playable tablatures The tablatures also mimic up to 60% of most of the original tablatures", + "Last Updated": "09 Jul, 2018", + "Prerequisites": " Core python Ability to integrate and use third party libraries", + "Section": "Core python and Standard library", + "Speaker Info": " RIshabh Shah Rishabh has around 4 years of python programming experience, he has developed an array of applications of which one was this Transcriber. Inputs from real world guitar players have been quite useful while developing the Transcriber. He developed this transcriber with one of his colleagues Srinivas Kalyani\n 2. Srinivas Kalyani Srinivas has around 3 years of technical experience with nearly 1.5 years of experience in Python. He has worked primarily on Django and entered the world of Core Python while writing the Transcriber", + "Speaker Links": "A list of few of our blogs can be found as follows: Rishabh: A Guide On Building REST API\u2019s Using Python Frameworks Slash Down Your Hosting Costs By 95% On Google App Engine Finding Your Google App Engine Hosting Costs Too High? Here\u2019s How To Fix It Srinivas: Need A Web Scraper? Here\u2019s How To Build One Using SCRAPY AND XPATH", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-object-detection-coz-yolo~b6VNb/", - "title": "Real-time object detection coz YOLO!" + "author": "Rishabh Shah (~rishabh104)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learn-guitar-via-python-programming-midi-parsing~bDAyd/", + "title": "Learn Guitar Via Python Programming (MIDI Parsing)" }, - "169": { - "Content URLs": "https://github.com/sdonapar/data_analysis_pytho", - "Description": "Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data. Data Visualisation helps to get hidden insights quickly . Data Visualisation is key for summarising and communicating your insights. This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis and visualisation Following will be covered as part of this session How does data analysis fit in the life cycle of data science project Dealing with numpy arrays - quick overview Reading data using various formats and sources Data scrubbing/cleansing - dealing with missing values, data transformation Introduction to data visualisation and quick overview of libraries available Using visualisation to understand and communicate results Analysing one of the open source data set By the end of the session Audience will have very good understanding of how to apply numpy, pandas to analyse, visualise understand and communicate the results Scrub/Cleanse the data and prepare data set required for machine learning", - "Last Updated": "16 May, 2018", - "Prerequisites": "Hands on exposure with basic python programming language Software requirements: Please install Anaconda ( https://www.anaconda.com/download/) with Python 3.6 Download the git hub repo - https://github.com/sdonapar/data_analysis_pythonwe would be using jupyter notebooks for this worksho", - "Section": "Data science", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company. I have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar linkedin profile - https://www.linkedin.com/in/sasidonaparthi twitter handle - @sdonapa", + { + "Content URLs": "You can view my blogs 1. Women and Data Science 2. Quantization and need for TPUs 3. Application of signal processing in machine learning You can view my various slides her", + "Description": "Imagine a play in a small theatre, where you are a producer sitting with the audience. Let us suppose the actors are weights and there are rows and rows of TPUs/GPUs behind. The director has assured you that they have rehearsed the play about 10 times, now all you do is pray that the performance goes well\nImagine you have 100 different tasks to be performed backstage, but the theatre given to you is really tiny. How will you manage? The answer is by optimizing the tasks. Divide tasks between individuals in such a way that you require less time and space. But how do you manage that with a neural network? How does quantization affect neural computations? When you are dealing with a large amount of data, one has to keep in mind the ever-changing values that one might obtain. Especially, signal data with large SNR (Signal to Noise Ratio) in them, which causes different sets of data to be produced. The best way to deal with such signal data is to apply truncation or rounding off such values, typically making it a many-to-few mapping. This mapping happens from 32-bit(at training) to 8-bit(at inference). On the other hand, traditional Internet of Things (IoT) infrastructures has two main parts \u2013 the edge and the cloud. The edge is the part of the system that is closest to the source of data. It includes sensors, sensing infrastructures, machines, and the object being sensed. The edge actively works to sense, store, and send that data to the cloud. So how does quantization help with edge computing? Does it have the potential of changing how we run models on the cloud? TALK AGENDA Introduction: 5 mins A Beginner's Guide to Quantization: 5 mins Understanding Quantization in TPUs: 10 mins Demo: Implementation of Quantization in Edge computing: 10 mins", + "Last Updated": "09 Jul, 2018", + "Prerequisites": " Knowledge on Tensor Processing Unit . Knowledge of IoT and Edge Computing Knowledge of Deep Learning", + "Section": "Embedded python", + "Speaker Info": "I am a fresher from SRM Institute of Science and Technology. I understand that engineering is not everyone's cup of tea and that everyone has a different perception of it. During my second year of study, I realized that for me education was something that was present beyond books and into practical applications. So I collaborated with a few other mates in college and started this place called the Next Tech Lab which was involved in cutting-edge innovation and novel research ideas. As a few of my achievements that the lab made me achieve included winning the Smart India Hackathon 2017 as the first prize under Ministry of Steel for using machine learning to detect power theft in India. Recently I was invited to the WiPDA conference in Xi'an China for presenting my work in GaN modeling of devices using machine learning, a collaboration with the University of Cambridge. I have around 3 IEEE Xplore Paper s (https://ieeexplore.ieee.org/document/8293259/)and 1 Elsevier papers for my contribution to electrical and machine learning fields As a lab, we have done so much more to protect gender diversity even among the strength of 200 members keeping a ratio of 50:50. We were portrayed for accomplishments by the News 18 in a short video. Over the past 6 months, I have had the opportunity to work and intern at Saama Technologies where I research on Machine Learning in order to accelerate clinical trials. A part of this work has exposed me to how models are necessary to be optimized across all devices big or small", + "Speaker Links": "My various talks in meetups in chennai 1) A Glance into Image Recognition of Cursive Text using OCR . 2) A Beginner's Guide to Machine Learning-Women Who Code Chenna", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "archana iyer (~archana52)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quantiziting-of-neural-networks-for-edge-computing~eEBYa/", + "title": "Quantiziting of Neural Networks for Edge Computing" + }, + { + "Content URLs": "Rough draft of slide", + "Description": " tl;dr : As data becomes increasingly extensive, it becomes important to move your models away from the cloud to where your data is being generated to reduce latency, increase security and save internet bandwidth. This talk will be about how you can run trained TensorFlow models on Edge devices and how you can use Edge Computing accelerators like the Neural Compute Stick to make your models run even faster. Long Version There are a lot of very compelling reasons for shifting computations away from the edge and into the cloud, with the most important being latency issues. Here, latency refers to the time it might take to send data to a server and then receive the response. The few seconds of delay caused by this might not be a problem for your smart home applications, but when in an industry, those few precious seconds, or even microseconds can cause a machine to breakdown or even take lives. Furthermore, many industrial processes might be happening in places where running an internet line may not be possible: a mine, for example. And even if having an internet connection is possible, most companies are hesitant to send data over an internet connection and risk exposing their data to hackers prompting them to keep their data in-house. Finally, if you have a lot of sensors, you will probably be streaming data in the order of gigabytes every hour. It does not make sense for companies to pay for the bandwidth to send that much data when most of it will be discarded anyways. Thus it is important to shift all that computation to where the data is being generated. This talk will be about how to move your existing TensorFlow models to Edge devices like Raspberry Pi's. The talk will also introduce other Edge Computing hardware like the Neural Compute Stick to make your models run even faster on Raspberry Pi. Why Attend this talk This talk will give the audience an understanding of Edge devices and Edge Computing. You will also learn the best practices to deploying models on the Edge. The live demo's will also give the audience an idea about how to run TensorFlow models on embedded devices. Topics covered: Edge Computing and Raspberry Pi - 5 Minutes TensorFlow Models - 5 minutes Demo on how to run models on the Edge - 10 minutes Demo with Benchmarking tests - 5 minutes Q/A - 5 minutes", + "Last Updated": "09 Jul, 2018", + "Prerequisites": " Python 3.5 TensorFlow 1.7", + "Section": "Embedded python", + "Speaker Info": "I have been working in the field of ML for the last year. I am currently working as a Deep Learning Research Engineering Intern at Saama Technologies, where I am using TensorFlow to reduce the time taken for clinical trials and help get patients medicines quickly. My primary work was with the University of Cambridge. There I used TensorFlow to create a model that can optimize the design of Gallium Nitride circuits. This work was published in one of the world's largest conferences on Power Electronics - WiPDA . In my second year of UG studies, I realized that engineers should have more practical knowledge. I started a student-run cross-disciplinary research lab called Next Tech Lab . As a part of the lab, I won the Smart India Hackathon for creating an app that could be used to detect electricity power theft . I have also published many research papers in IEEE and Elsevier . I am also an active member of the Indian Deep Learning Community . I also write articles such as this one: convolutional filter types and Data Correlation and Machine Learning . I believe in spreading knowledge and teaching others about Machine Learning", + "Speaker Links": " Links to slides for my talks - here Links to talks and github- here Website - csoham Medium articles - here LinkedIn Saama blog", "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-visualisation-using-python~e50Xd/", - "title": "Data Analysis & Visualisation using Python" + "Type": "Talks", + "author": "Soham Chatterjee (~soham48)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/running-tensorflow-models-on-a-35-device~dGELa/", + "title": "Running Tensorflow models on a $35 Device" }, - "170": { - "Description": " Understanding Neural Networking using NumPy Implementing CNN using Keras & understanding foundations Using Pretrained models. Transfer training for doing dog breed identification", - "Last Updated": "15 May, 2018", - "Prerequisites": " Python Basics NumPy Machine Learning Basics", - "Section": "Data science", - "Speaker Info": " 10 + Industry Experience. Machine Learning & Deep Learning Trainer/Consultant for more than 20 companies https://www.linkedin.com/in/awantik/ Co-Founder EdYoda & Zekelabs", - "Speaker Links": "https://www.linkedin.com/in/awantik", + { + "Description": "If you\u2019ve been using python for any length of time, you know it as this versatile tool that can be used to build almost anything, and in a very friendly way. But Python use in the large codebase arena is very different from Python for a small service. What if you knew that that shift was due? What if you knew that the next project you started was definitely going to be collaborated on by a hundred developers? Let\u2019s look at these differences and prepare ourselves and our codebases for that shift. We\u2019ll learn how: Maintaining large codebases isn\u2019t free, and how the Python ecosystem\n supports you in your efforts. Testing a large application isn\u2019t easy, and how to use the latest and\n greatest testing methods to make sure your code does what you expect\n it to. Immutable data structures aren\u2019t just easier for humans to process,\n but also for machines to validate. Python has learnt from its neighbouring languages, and now has a type\n system that is here to help.", + "Last Updated": "09 Jul, 2018", + "Section": "Developer tools and Automation", + "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", + "Speaker Links": "LinkedIn githu", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Madhukar Mishra (~madhukar93)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/reliable-code-what-the-giants-have-taught-us~dJRJd/", + "title": "Reliable code: What the Giants have taught us" + }, + { + "Description": "Do you use isinstance() frequently and know there is a better way, but you just don\u2019t know how? Have you been bitten from using mutable arguments to functions? Python has an interesting data model as a dynamic language. This model shapes the programs you write and a good understanding of this goes a long way in writing effective code.\nThis talk covers the various approaches you could take to handle the behaviour of your objects from duck-typing to the new dataclasses introduced in Python 3.7 .\nWe will also take a deep dive into the Python data model itself and see how we can leverage it to give intuitive APIs to our libraries. All the benefits of having a thought out data model apply. Your code can be cleaner and easier to test. \"Bad programmers worry about the code. Good programmers worry about\n data structures and their relationships.\" - Linus Torvalds \"Show me your flowcharts and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won\u2019t usually need your flowcharts; they\u2019ll be obvious.\" - Fred Brooks", + "Last Updated": "09 Jul, 2018", + "Section": "Core python and Standard library", + "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", + "Speaker Links": "LinkedIn githu", "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Awantik Das (~awantik)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-using-python-from-scratch-image-classification~b4KJa/", - "title": "Deep Learning using Python from Scratch - Image Classification" + "Type": "Talks", + "author": "Madhukar Mishra (~madhukar93)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-type-system-building-an-effective-mental-model~aKRMe/", + "title": "Python Type System: Building an effective mental model" }, - "171": { - "Content URLs": "https://games.renpy.org/category/rpg https://www.renpy.org", - "Description": "Ren'Py is one of the most versatile and easy-to-use frameworks, written in Python, for the development of Visual Novels and smaller Role-playing games. The talk will explore the details about creating your own development environment for development of visual novels, writing a script and developing GUI, porting your game to Android and iOS and how you can get help for issues in development process. The talk will also explore some of the games which have been developed in Ren'Py like Katawa Shoujo, Doki Doki Literature Club, Imre's Curse: The Prologue etc. The talk will be an interactive one and have a very light and humorous note", - "Last Updated": "15 May, 2018", - "Prerequisites": "No prerequisites required. An open mind and familiarity with Python is all what is needed to attend the talk", + { + "Description": "Static code checking should be easy, but in practice, it\u2019s easy to be overwhelmed by the volume of tools available, and disappointed with the returns on time spent integrating. The world of static code analysis has evolved a great a deal and appears to be underutilised for Python. Here are some of the things we are going to cover: Linting - automate your code reviews Measuring test coverage - legacy code is that which is not tested Security checks - what can you get for free? Static type checking with a dose of gradual typing Dead code analysis - reduce the noise Setting up an effective CI pipeline - aiming for less process and more results Setting up productive developer environments - leverage code completion and type hints", + "Last Updated": "09 Jul, 2018", + "Section": "Developer tools and Automation", + "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", + "Speaker Links": "LinkedIn githu", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Madhukar Mishra (~madhukar93)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-static-code-checking-asymptotically-approaching-perfection~dLRXa/", + "title": "Python static code checking: Asymptotically approaching perfection" + }, + { + "Content URLs": "Slides: https://slides.com/yashmehrotra/distributed-tracing/ Github Repository to be added soo", + "Description": "This talk would be about our journey to successfully trace every request in our Python-based microservice Architecture. An outline of the talk: Why distributed tracing ? How distributed tracing works at a glance ? Distributed tracing using Python Insights you can gather from distributed tracing Performance Observability Easily debugging microservice failures", + "Last Updated": "09 Jul, 2018", + "Prerequisites": " Basic knowledge about python based web applications An idea about microservice architecture Unhappiness with existing inter-service debugging tools ", "Section": "Others", - "Speaker Info": "I am currently involved with Lernr Project, a startup based in Ahmedabad and have been working with Python for 3+ years, certified as a\nSoftware Carpentry Instructor and one of the organizers of Django Girls Bangalore. Contributor to Biopython, Galaxy Project, bioconda and conda-forge communities. My interests are in the field of Bioinformatics, High-Performance Computing and am working under Prof. V.K. Jayaraman in the field of Proteomics", - "Target Audience": "Beginner", + "Speaker Info": "This talk will be given by Yash Mehrotra. He is currently working at Grofers where he is a part of the Search Team. He has also interned at HackerEarth, AdWyze and is a former Mozilla Winter of Security Participant. He recently acquired a keen interested in distributed systems and loves to beat people at FIFA in his free time", + "Speaker Links": "Website: https://yashmehrotra.com/ Github: https://github.com/yashmehrotr", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Sourav Singh (~sourav)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/make-your-own-visual-novel-in-renpy~b2JAb/", - "title": "Make your own Visual Novel in Ren'Py" + "author": "Yash Mehrotra (~yash2)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/distributed-tracing-for-your-python-based-microservice-architecture~aM6Ob/", + "title": "Distributed Tracing for your Python-based microservice architecture" }, - "172": { - "Content URLs": " Talk at PyCon India 2017 Talk at PyCon Pune 2017 Talk at PyCon India 2013 Django on Steroids -- Slides Lessons from Scale: Django", - "Description": "Take it from someone who has introduced an exorbitantly high number of bugs in empty files for most of his life: debugging is hard indeed. But since the dawn of time, developers have been debugging code: there's no escaping that. Software testing, as the elders would tell you, is one of the greatest weapons in your arsenal against those bugs. It's easy to write tests. It helps you write more robust software. And it really helps you sleep at night: and your on-call ops team would love you! But testing is also deeply mystified, unfortunately. Beginners, and sometimes even seasoned developers, generally have a difficult time just to get started: so they eventually miss out on this easy way to attain peace of mind. This talks aims at removing all the mystery around software testing in Python, and give the attendees a head-start into the easiest way of writing tests for their code. As part of being a Python developer for the past 8 years and leading a team of developers building enterprise-grade software for the past 4 years, I've learnt immensely about the important role of software testing in building scalable, durable software; and also a better, pragmatic way of thinking about testing in Python. This talk aims at providing a distilled version of my learning to the audience: both beginners to Python, and seasoned Pythonistas. The talk would broadly cover these topics: A formal way of thinking about software testing / Why you should even bother about writing tests? Writing the simplest of tests in Python / Brief exploration of unittest and pytest Introduction to mocking in Python / In-depth exploration of mock and how to effectively use it for mocking any type of scenario in your code Writing tests for complex applications / working code examples from real life A few (opinionated) recommendations about testing Apart from providing to the audience an easy-to-grasp framework of thinking about software testing, this talk aims to teach by examples from real world. Complex and not so straightforward concepts would be explained with code samples and tests from production, so it's easy for the audience to truly grasp them. The talk also features anecdotes from my own experience in building software to give the audience better context", - "Last Updated": "15 May, 2018", - "Prerequisites": "This talk is intended for newcomers to Python (who might never have written a test yet), as well as experienced developers (who might not be writing tests effectively). There are no technical pre-requisites for this talk. The key takeaways would be patterns you can directly start using in writing tests for your own code", - "Section": "Developer tools and Automation", - "Speaker Info": "Sanket ( @sanketsaurav ) is co-founder and Chief of Geeks at DoSelect . He\u2019s 50% developer and 50% designer. He\u2019s been dabbling with computers since the age of 10, and had started his first venture at 18. He loves the Web and likes building cool stuff that matter. His languages of choice are Python, Go and JavaScript, and he\u2019s been building production apps using these for the past two years. He\u2019s also spoken at more than 50 events and hackathons across the country on open source technologies including Python, HTML5 and web applications in general. Sanket also contributes extensively to open-source, with contributions to projects like Django, Celery and Docker, and original Python modules like S3Tree and mimelib ", - "Speaker Links": " GitHub Website DoSelect", - "Target Audience": "Beginner", + { + "Description": "In recent times, we have seen a startling rise in data aggregation and reliance on machine learning models. This has grave consequences when our data is not protected and when model behaviour is deliberately modified. Differential Privacy is a privacy aware sampling technique that ensures that no one individuals property can be extracted from the model. Adversarial examples look similar to real images but are engineered in such a way that they result in nonsensical predictions from ml models. Recent research has shown that the issue of adversarial attacks on machine learning models could be solved by using differential privacy. This talk aims to introduce differential privacy, adversarial examples and introduce the audience to the vibrant python research community around these topics", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "An understanding of how neural networks wor", + "Section": "Data science", + "Speaker Info": "I'm Sadhana Srinivasan, I did my master's in Mathematics from BITS Pilani. I've been coding in python and working in machine learning for the past 3 years, having taught deep learning and machine learning courses at BITS. I interned at EY working on chatbots for analytics. I'm currently a research engineer at Saama Technologies working on AI based solutions for the healthcare industry", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Sadhana Srinivasan (~rotuna)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/differential-privacy-and-adversarial-examples~dNyDb/", + "title": "Differential Privacy and Adversarial Examples" + }, + { + "Content URLs": " https://speakerdeck.com/anandology/deploying-ml-apps-in-minutes https://github.com/rorodata/firefly https://github.com/rorodata/rorolite https://github.com/amitkaps/full-stack-data-science", + "Description": "Often, the most convenient way to deploy a machine model is an API. It allows accessing it from various programming environments and also decouples the development and deployment of the models from its use. However, building an good API is hard. It involves many nitty-gritties and many of them need to repeated everytime an API is built. Also, it is very important to have a client library so that the API can be easily accessed. If you every plan to use it from Javascript directly, then you need to worry about cross-origin-resource-sharing etc. All things add up and building APIs for machine very tedious. In this talk demonstrates how deploying machine learning models an APIs can be made fun by using right programming abstractions. The talk presents the couple of open-source libraries firefly and rorolite created to solve this very problem and also shares the experience of building cloud-based PaaS platform that addresses these issues", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "The participants should have understanding of machine learning models and APIs", + "Section": "Data science", + "Speaker Info": "Anand has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, rorodata , which he recently co-founded. He regularly conducts advanced programming courses through Pipal Academy . He is co-author of web.py, a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive", + "Speaker Links": " https://anandology.com Firefly documentation Rorolite documentation", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Sanket Saurav (~sanket)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-is-hard-testing-is-easy~e17qb/", - "title": "Debugging is hard, testing is easy!" + "author": "Anand Chitipothu (~anandology)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-as-a-service-how-to-deploy-ml-models-as-apis-without-going-nuts~aOzYe/", + "title": "Machine Learning as a Service: How to deploy ML Models as APIs without going nuts" }, - "173": { - "Content URLs": "I will soon share presentation, resources, and code soon on GitHub", - "Description": "Abstract Think of wireless internet, but has the wire somewhere. Serverless architecture still has the server behind :P. What serverless actually means that developer should focus on the code rather than thinking about the servers. As a technique, it removes most of the manel parts of an application, so you can actually spend your day coding. This means that you, developers, can quickly create apps that handle production-ready traffic. You do not have to actively manage scaling for your applications. You do not have to provision the server, or to pay for resources that are unused. The serverless movement started with the release of AWS Lambda, a Function-as-a-Service (FaaS) compute service. But serverless is much more than just FaaS Chatbots have been around for quite a long time. But why this sudden surge and interest in chatbots now? Well, there are various reasons. Unlike the earlier days, many AI and NLP capabilities are now available as consumable services. Also, serverless technologies make chatbots easier to build and scale. The question is, how is the backend served? Would you set up a dedicated server (or a cluster of servers)? That\u2019s costly, painful, and time-consuming! or You will deploy it to Heroku, which will eventually sleep (only happens in the free tier) if no one uses your chatbot. Imagine suddenly, traffic increased your chatbot is used by thousands of people at a time. When Heroku free tier is over, the application crashed or you exceeded memory limit. What would you do now? That\u2019s where serverless technology can help. Benefits of serverless No Administration - We can deploy our code without provisioning anything beforehand, or manage anything afterward. There is no concept of a fleet, an instance, or even an operating system. Scalability - One doesn't have to care about auto-scaling, No need to show alerts or write scripts to scale up and down. With serverless, we can handle quick bursts of traffic. Cost - Function-as-a-service (FaaS) compute and managed services charged based on actual usage rather than pre-provisioned capacity. This means one pay the amount we use, so if we use service for 10 sec then we pay for 10 sec. Faster Development - Now loop between having an idea and deploying to production is shortened because no one need to manage anything after deployment, smaller teams can ship more features. It's easier than ever to make your idea live. Easy Integration With Other Services Going serverless allows a seamless integration to various other cloud services from the same provider. For example, if you are using the AWS platform for chatbots, then you can use DynamoDB for the database, write programming logic as Lambda functions, and expose them through the API Gateway. Session key Takeaways The main question is how to write code which is serverless compliant. This is where this session will help you. This talk will help people to move a step ahead of the traditional way of writing code as some of you had already developed chatbot, I will share how can you can write the simple chatbot in python and can take leverage of serverless to deploy and publish. I will cover Serverless Framework principals AWS Lambda, Amazon Lex and API Gateway How to write a chatbot in python and create a Lambda function How to troubleshoot in a serverless world", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic knowledge of python and development in general", + { + "Content URLs": "Example of one of our outputs:", + "Description": "Have you ever wondered how snapchat filters work? In this talk we will give you a thorough explanation and demo of the famous face swap filter using OpenCV, dlib and NumPy. Talk Summary: We will do a line-by-line walkthrough of our code to extract facial landmarks of both images using methods like convex hull and delaunay triangulation. We then swap faces of the two input face images and blend them using the seamlessclone method. We will also go through various computer vision concepts required to understand the underlying mathematics. Outcome: After this talk you would be able to learn how to do the above mentioned tasks and some insights into a few OpenCV methods and we will also go over a little bit of numpy basics. Agenda: Introduction and live demo [5 min] Explanation of facial landmark detection methods [5 min] Overview of functions used in our code [5 min] Line by line walkthrough of the code [10 min] Questions from the audience [5 min", + "Last Updated": "09 Jul, 2018", + "Prerequisites": "Love for Python, Familiarity with Python3 synta", "Section": "Others", - "Speaker Info": "Vaibhav Singh is an undergrad final year student of BML Munjal University, Gurugram. He had worked with AWS services as a solution architect intern in Amazon and he is also open source enthusiast and contributed to many open source organization like Fossasia, coala, etc. He is now Google Summer Of Code intern with FOSSASIA. Previously, He was the finalist winner in Codeheat competition. I write mostly in python ;). I had written various small scripts to make my life easier :", - "Speaker Links": "Website GitHub Twitter Facebook Linkedin Mai", + "Speaker Info": "Sarvesh Shroff: I am currently a sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. I have won a national level robotics championship held at IIT-R. Miran Junaidi: I am MTH Junaidi, sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. Also gave a lightning talk at PyCon Taiwan 201", + "Speaker Links": "Sarvesh Shroff: GitHub LinkedIn Miran Junaidi: GitHub LinkedI", "Target Audience": "Beginner", "Type": "Talks", - "author": "Vaibhav Singh (~vaibhavsingh97)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-serverless-framework-build-a-chatbot~eZXgb/", - "title": "The Serverless Framework - Build a Chatbot" + "author": "Sarvesh Shroff (~sarvesh77)", + "created_on": "09 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-your-own-snapchat-filter-using-opencv~dPA1e/", + "title": "Creating your own Snapchat filter using OpenCV" }, - "174": { - "Content URLs": "Sensor Fusion Introduction\nhttps://youtu.be/C7JQ7Rpwn2k Sklearn Quick Tutorial\nhttp://scikit-learn.org/stable/tutorial/basic/tutorial.htm", - "Description": "Abstract The primary purpose of this talk to describe how we are using python and Sklearn to model and analyse time series sensor data. In particular, I will walk through how we use Python to process data from an IoT enabled sensor attached to a cricket bat, build machine learning models on the data, and use open source tools to deploy our models in the sensor device as a smart IoT application. Description With the steep increase in the number of smart-things connected to the internet, the amount of data that is being generated by such devices is increasing exponentially. However, much of that data is not useful and therefore filtering unuseful data is an important task. How do we filter the important part and remove the noise from sensor data streams to generate actionable insights? To demonstrate the problem we are placing a sensor device on a cricket bat. The IoT device is a miniaturised, wireless MEMS inertial measurement unit (IMU). The IMU incorporates three-axis sensing of bat acceleration and angular velocity with a low-power Bluetooth to transmit this data to a mobile. First, we gather event-based data rather than storing the entire stream. This again poses the question: how do we define an event? What makes an event unique from the surrounding \u2018non-event\u2019 context? These are some of the questions that need to be answered in order to define an event. Watching a cricket batter stand and prepare to swing, the human brain continuously filters its visual perception and is able to detect and differentiate a swing from the pre- and post-swing activity. We need to be able to automate that same process. Some data instances can be tagged while other can\u2019t be. This helps in training and evaluating machine learning models later. Secondly, After we have extracted time series data based on the instances, we can start analysing these event-based sets of data to understand the language of sensor data. For this, we are using Jupyter Lab to interactively work with data. How does an accelerometer data depict the real world physical motion? This step helps us find the relation between the real world actions and the sensor data set. Well, the extraction process will be prone to noises. The data comes in CSV files, python seems the right choice for us to read and analyse the data. Pandas and offer data frames that come handy to rapidly form and validate hypothesis interactively in Jupyter notebooks. Any analysis is incomplete without visualisation, that's where Matplotlib helps us understand the data better. We quickly test the machine learning models by using Sklearn, which has most of the standard algorithms already implemented. This keynote will describe some of the analysis (along with python code) to show how we have taken several steps right from forming the hypothesis to implementing a solution in the device level layer. All of this demonstrates how Python and its rich set of libraries are helpful in forming solutions to some of the product related features. Thirdly, we need to automate the task of classifying a particular instance from the stream. For this to happen, we can either feed a machine learning model or create a rule-based algorithm which can classify the events into buckets. Now every step has its own set of challenges, firstly the application we are working on involves using motion sensors attached to the back of a cricket bat. There are network constraints in the field. If a sportsperson wants to know real-time analytics from the device, the segregation needs to happen offline. We have to deploy the models on the miniature sensor devices because sometimes the players don\u2019t even carry their mobile phones to the playing area. Therefore our objective is to enable the devices to remain independent in running machine learning algorithms by themselves", - "Last Updated": "14 May, 2018", - "Prerequisites": "Participants should have an understanding of python basics", + { + "Description": "Monitoring and alerting are essential components of any system. As the number of services grow, monitoring all of them all the time becomes a mammoth task in itself. Hence, there's always a need for having an intelligent system to monitor other systems\u2019 behaviour and notify the appropriate stakeholders when an anomaly occurs.\nHere are some of the things I am going to cover: The need for effective anomaly detection in systems monitoring. System metrics that matter to you - CPU, memory, disk, etc Using StatsD and CollectD for data collection. Building a useful data pipeline Using PySpark for real time data processing Using NumPy and SciPy for business intelligence Implementing anomaly detection algorithms.", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Participants should have some basic knowledge of systems monitoring. Having used tools like New Relic, Grafana would be an added advantage. Basic knowledge of streaming data and Kafka would also be useful", "Section": "Data science", - "Speaker Info": "Sanjiv Soni is a data scientist at Str8bat, Bangalore. He currently an international fellow at University of San Francisco for Deep Learning Programme. Sanjiv has experience with Software and product ecosystem. He has interests in building software devised solutions to problems solved by humans", - "Speaker Links": "https://twitter.com/sanjivsoni7 https://www.linkedin.com/in/sanjiv-soni", - "Target Audience": "Intermediate", + "Speaker Info": "I am an Engineer at Grofers. Worn multiple hats throughout my career starting from Full-stack Engineering, to Backend, to Data, and now to Release Engineering. Co-founded crowdsource logistic platform DbyT. Worked as a Programmer Analyst at Virginia based RTS Labs and as a Salesforce Consultant for Richmond based MCIM. Worked with clients from Healthcare, Mission Critical, Datacenter management, Payments industries", + "Speaker Links": "https://medium.com/@sharmaNK/ https://www.linkedin.com/in/nand-kishore-sharma-49902219/ https://github.com/sharmaN", + "Target Audience": "Advanced", "Type": "Talks", - "author": "sanjiv soni (~sanjiv)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/swing-and-a-miss-deploying-machine-learning-models-for-iot-enabled-devices-using-python~bYXYa/", - "title": "Swing and a Miss: Deploying machine learning models for IoT enabled devices using Python" + "author": "nandkishore sharma (~nandkishore)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-system-monitoring-using-pyspark~aQB0b/", + "title": "Real time system monitoring using PySpark" }, - "175": { - "Content URLs": "https://atad.xyz\n[ Will share the GitHub repo during the talk with sample web crawlers ", - "Description": "Introducing to Web Scraping. A complete walkthrough the below items: Challenges in scraping websites and parsing the data, Introducing Scrapy, a widely used framework to extract data Dos & Don'ts Usage of Proxies & IP Rotation Crawling hundreds of websites, running and scaling them to huge volumes", - "Last Updated": "14 May, 2018", - "Prerequisites": "Laptop with Ubuntu or a similar OS. \nPython and MySql latest versions Basic understanding of Python and MySql\nGood to have knowledge in writing Xpaths and usage of proxie", - "Section": "Data science", - "Speaker Info": "I am Raja Emmela, \nI Run Headrun Technologies, Bangalore - helping clients in Data Scraping and Web Applications We are in this space for the last seven years, extracting data and parsing them. My experience helps do share the challenges we faced with domestic and NA & APAC clients while scraping websites and the don'ts in particular", - "Speaker Links": " LinkedIn Twitter Blog", + { + "Content URLs": "I will upload the Slides after the talk", + "Description": "In this talk I want to cover the following topics around Test Automation : Generating python REST API Client with swagger codegen. Automating the python REST API Client generation using swagger spec. Writing automated API Tests/Functional tests (which consume the API\n Client libraries) using pytest as a test runner. Dynamically installing the REST API client and executing the tests\n in the CI pipeline - Jenkins. Invoking the Tests and including them in product\n qualification via the CI Pipeline - Jenkins. ", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Familiarity to REST APIs. Familiar with Test Runner pytest - https://docs.pytest.org/en/latest/ Basics of CI - Jenkins - https://jenkins.io/", + "Section": "Developer tools and Automation", + "Speaker Info": "I am a software test automation engineer and a python lover", + "Speaker Links": "https://linkedin.com/in/hemamalini-rengarajan-55248a", "Target Audience": "Intermediate", "Type": "Talks", - "author": "rajaemmela", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-intro-to-web-scraping-dos-donts-and-the-challenges-in-scaling-it-to-huge-volumes~eXVVb/", - "title": "An intro to Web Scraping, dos & don'ts and the challenges in Scaling it to huge volumes" + "author": "HemamaliniRengarajan", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-rest-api-client-generation-and-test-execution-in-ci-pipeline~dRDOa/", + "title": "Automated REST API Client generation and Test execution in CI pipeline" }, - "176": { - "Content URLs": "https://github.com/devxp", - "Description": "My talk is related to my work on ZProc , a library for doing multiprocessing in python Its provides a high-level wrapper over zeroMQ, the distributed messaging library. I will provide a basic introduction to the ways we can natively implement concurrency/parallelism in our applications and how ZProc is a better way to do multi-tasking", - "Last Updated": "14 May, 2018", - "Prerequisites": " A good knowledge of basic python. Some knowledge about the python Process/Thread interface is appreciated If you ever had your hands on the zguide , I have a hunch you'll like this. ", + { + "Description": "SecureDrop is an open-source whistleblower submission system that media organizations can use to securely accept documents from and communicate with anonymous sources. It was originally created by the late Aaron Swartz and is currently managed by Freedom of the Press Foundation. In the modern age of Internet, keeping privacy in the online world has become a bigger battle ground. It became an even bigger challenge for the journalists, lawyers, and anyone else who is dealing with sensitive material. Whistleblowing and leaking have dominated news coverage in recent years. SecureDrop (a Python application) project provides a reasonably safe way for the journalists to receive tips/sensitive materials from anyone, and still safeguarding the sources and keeping the materials secured. SecureDrop also won The Award for Projects of Social Benefit from Free Software Foundation in 2016. This talk will be divided into three sections, why, how and what is in future. Introduction How is SecureDrop working in newsrooms? The top view of the technical stack (Flask application + rest of the stack) Tips for web developers thinking about privacy What are the biggest challenges and threats? What is in future? (SecureDrop workstation project: explaining the new PoC workstation using Python on QubesOS). As a project SecureDrop has many different parts running in different systems. This talk will provide an overview of the technical backgroud of the project, and will try to help the curious minds to go a step ahead to contribute or use the similar ideas in the other applications", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Non", + "Section": "Others", + "Speaker Info": "Kushal Das is a regular speaker in various conferences. He is a CPython core developer and director at The Python Software Foundation.\nHe is currently working on SecureDrop project full time as a staff member of the Freedom of the Press Foundation ", + "Speaker Links": " https://kushaldas.in https://github.com/kushaldas", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Kushal Das (~kushal)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/securedrop-the-open-source-whistleblower-submission-system~eVKva/", + "title": "SecureDrop, the Open Source whistleblower submission system" + }, + { + "Content URLs": "The slides accompanying the talk, along with all the examples may be found at RJ722/reducing-dead-code . Other useful links: RJ722/example-vulture displays an example on how we can integrate vulture with CI tests. vulture coala.io ", + "Description": "Maintaining a high level of code quality is important for any serious project. One aspect of this is ensuring that all code is actually used. There are many reasons for dead code ending up in a project. The most common is refactoring, but another is misspellings, which are only detected at runtime for dynamic languages. Finding and removing dead code allows to keep the code base clean and reduces bugs. This talk is focussed on how we can use Vulture to find dead code. It helps you find unused code in Python programs and it is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python's dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused. Nonetheless, Vulture can be a very helpful tool for higher code quality. One part of this talk is to discuss how to automate testing for dead code with Vulture. There are quite a few options available: Adding vulture to your continuous integration testing. A script using the Vulture API for custom tests. Identifying false positives and creating whitelists VultureBear : Integration with coala - a static code analysis tool. This talk is a revised version of a similar talk given at PyCon India 2017 (by the same speaker)", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " python and pip installed Optional requirements: coala coala-bears", "Section": "Developer tools and Automation", - "Speaker Info": "I'm 19 year old python programmer, picked up python when I was around 15. My adventures with multi-tasking applications started when I was 17, trying to build a concurrent youtube downloader. I am since, trying to find ways to make writing concurrent, multi-core applications simpler in python", + "Speaker Info": "Rahul Jha He is currently pursuing B.Tech. (ECE) from Zakir Husain College of Engg. & Technology, Aligarh Muslim University. He develops free and open source software. His key contributions in the Vulture community include the vulture API, and the whitelisting scripts . Apart from computers, he likes playing with Robot Cars and editing Wikipedia pages", + "Speaker Links": "You may find more about Rahul here: https://rj722.github.io https://github.com/RJ722 https://twitter.com/rahul722j You may contact him through: e-mail: rahul722j@gmail.com IRC: #vulture on freenode (nick: RJ722)", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Dev Aggarwal (~devxpy)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/zproc-process-on-steroids~bWBoa/", - "title": "ZProc - Process on steroids" + "author": "Rahul Jha (~RJ722)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/scavenge-dead-python-bits-with-vulture~bWXQd/", + "title": "Scavenge Dead Python bits with Vulture" }, - "177": { - "Description": "A lot of budding programmers use print() function or logging module to display the state of the program. However, it soon becomes untenable to reason about the program in a barrage of print statements. At that time, a debugger is a must. Debuggers are a better and structured way to inspect a program. A practical and basic understanding of debuggers will help in locating bugs easily and save developer's time and unnecessary frustration. In this talk, we are going to learn the terminology associated with debugging and explore the most commonly used commands of pdb", - "Last Updated": "14 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college students or people who just started programming in Python", + { + "Description": "You\u2019ve heard a lot about concurrency. Asyncio has been in the standard library for a while, and concurrency is picking up mindshare. Why does the world suddenly care so much about concurrency? How did people write concurrent code before asyncio? Do we still need multithreading, multiprocessing, Gevent, Tornado, etc now that asyncio is here? You\u2019ve also heard about the GIL. Supposedly, it doesn\u2019t let you write parallel programs - so why does Python have it? We\u2019ll also discuss the kinds of problems that can be solved faster with concurrency and the kinds of problems that definitely can\u2019t. Let's answer all these questions and more in this light, demo-driven talk", + "Last Updated": "10 Jul, 2018", "Section": "Core python and Standard library", - "Speaker Info": "I'm currently a Senior Web Developer and Curriculum Designer at Pesto Tech. I've programmed in Python and Flask since the last 3 years. Open source enthusiast, and frequent blogger", - "Speaker Links": "Medium - https://medium.com/@arfatsalman Twitter - https://twitter.com/salman_arfat GitHub - https://github.com/ArfatSalman LinkedIn - https://www.linkedin.com/in/arfatsalman", + "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", + "Speaker Links": "LinkedIn githu", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "Madhukar Mishra (~madhukar93)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-python-concurrency-story~eX25b/", + "title": "The Python concurrency story" + }, + { + "Content URLs": "Will update soo", + "Description": " playing makes learning fun. And how do you make learning mathematics fun? Obviously playing with mathematical abstractions. Early days people used to play with mathematical objects using pen and paper. But imagine playing with repetitive things using pen and paper. That will make it boring soon, won't it? in this talk I will show you how python can be used to make simple to advanced iterative mathematics fun. Yes you are reading it right. From shuffling of a deck, sequences of numbers, calculus these are few steps of our journey through iterative mathematics using python. I will be using basic python data structures , list comprehensions, and some functional programming aspects to demonstrate this. \n\u200c take aways from this talk - if you are a maths enthusiast , you will understand how to write python code to solve your problem. If you are a programmer you will understand how do you make use of simple python functionality to do recreations in mathematics.", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "School level mathematics and zeal for recreational mathematic", + "Section": "Core python and Standard library", + "Speaker Info": "Vikrant has over 12 years of experience in crafting software solutions. He conducts python trainings through pipal academy. He has worked on diverse areas like Computational Fluid Dynamics, mathematical algorithms for bioinformatics, network-based license servers etc. He has worked at Strand Life Sciences and DRDO. He has a Masters in Computational Science from Indian Institute of Science", "Target Audience": "Beginner", "Type": "Talks", - "author": "Arfat Salman (~ArfatSalman)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-basics-and-debugging-python-scripts-with-pdb~eVZoe/", - "title": "Debugging basics and debugging python scripts with pdb" + "author": "vikrantpatil", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/adventures-in-iterations~bYNMd/", + "title": "Adventures in iterations" }, - "178": { - "Description": "Millions of visitors visit business websites every day and each one of them takes different set of steps in order to seek the right information/product. Yet most of them leave disappointed or dejected for some reason and very few get to the right page within the website. In this kind of situation, it becomes difficult to find out if the visitor actually got the information that he was looking for? Also, the individual journeys of these visitors can\u2019t be compared to each other since every visitor has done different set of activities. So, how can we know more about these journeys and compare these visitors to each other?\nSequence Embedding is a powerful way that offers us the flexibility to not only compare any two distinct visitors entire journey in terms of similarity but also to predict the probability of visitor\u2019s conversion. Sequence embeddings essentially helps us to move away from using traditional features to make predictions and considers not only the order of the activities of a user but also the average time spent on each of the unique pages to translate into more robust features and used in Supervised Machine Learning across multiple use cases (next possible action prediction, converted vs non-converted, product classification)\u00a0.Using traditional Machine learning models on the advanced features like sequence embeddings, we can achieve tremendous results in terms of prediction accuracy but the real benefit lies in visualizing all these user journeys and observing how distinct are these paths from the ideal ones. This session will unfold the process creating sequence embeddings for each user\u2019s journey in python and use them to build machine learning classification model to predict visitor conversion along with comparing all the user journeys in terms of similarity score", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic understanding of Machine Learning ,\nPython Basic", + { + "Content URLs": "https://docs.google.com/presentation/d/19inq4BNUi3U74uIBz-nN7gSVOvtC9S4s-FBW0Im1gUg/edit?usp=sharin", + "Description": "Master data is at the heart of an efficient and effective modern business.Master data management (MDM) is the effort made by an organization to create one single master reference source for all critical business data, leading to fewer errors and less redundancy in business processes. The real challenge is the real world data is messy and it's difficult to make a decision out of this data. There are lot of records which can be duplicates or have the same entity references which leads to ambiguity and resource consumption. Entity resolution (ER) is the task of disambiguating records that correspond to real world entities across and within datasets. Problems associated with entity resolution are equally big\u200a\u2014\u200aas the volume and velocity of data grow, inference across networks and semantic relationships between entities becomes increasingly difficult. Data quality issues, schema variations, and idiosyncratic data collection traditions can all complicate these problems even further. When combined, such challenges amount to a substantial barrier to organizations\u2019 ability to fully understand their data, let alone make effective use of predictive analytics to optimize targeting, thresholding, and resource management. Dedupe it's a modern day python library for entity resolution, which works on machine learning algorithms to perform Deduplication and Record Linkage", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Basic Knowledge of Python and Basics of Machine Learning Classifiers like LR,KNN, DT etc.", "Section": "Data science", - "Speaker Info": "Co-Founder of DataScienceBridge and currently Sr. Data Scientist at SapientRazorfish core Data Science Team has around 8 years\u2019 experience in the industry, ranging from large scale IT enterprise business development to building complex Machine Learning models by applying state of the art techniques. He has completed his Master\u2019s in Business at Symbiosis International University and certified professional in Machine Learning from IIM-Calcutta.\nHis core expertise involves Machine Learning, Deep Learning, Recommendation Systems using python, spark and Tensorflow for various projects. He is president of Data Science meet up group at SapientRazorfish and conducts multiple webinars on Machine Learning. Along with that he is also a speaker and recently presented a talk at \u201cGreat Indian Developer Summit \u201c(GIDS 2018).\nIn his spare time, he likes to read, code and help aspiring Data Scientists", - "Speaker Links": "https://www.youtube.com/watch?v=Nbpz79v2y5", + "Speaker Info": "Vinay is working as a Data Scientist and he loves creating the Data Driven Applications and really love working with the messy data and cleaning it to implement Machine Learning Models to the new age applications. In his leisure time he blogs on Kanoki.org and writes articles on Data Science central.\nHe is an Electrical Engineer from an academic perspective and earned certificate in Data Mining from Indian Statistical Institute and currently pursuing his masters in Statistics. He has delivered talks in the past in PYCON - New Delhi and other conferences Internationally. Beside Data, he is a passionate cyclist and rides 100KM average in a week", + "Speaker Links": "personal Blog: https://kanoki.org/ Pycon-2016: https://www.youtube.com/watch?v=ADjRj6qPF7o&t=29s Selenium Conference 2016: https://www.youtube.com/watch?v=mS3dzczv1ZQ&t=9", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Pramod Singh (~pramodchahar)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sequence-embeddings-in-python-classification-user-journey-comparison~dRBwd/", - "title": "Sequence Embeddings in Python: Classification & User journey Comparison" + "author": "vinaybabu", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-mdm-entity-resolution-using-dedupe~eZNwe/", + "title": "Demystifying MDM & Entity Resolution using Dedupe" }, - "179": { - "Content URLs": "For workshop home here and here such as to get sample data, Jupyter notebooks, slides etc For workshop slides pls see her", - "Description": "Geospatial representation are so prevalent in day to day life, such as even in simple travel related conversation to maps, aerial/satellite images etc. In digital era, geospatial data is extensively produced and consumed in ever growing proportion. Python with its free and open source libraries are giving wide variety yet simple and effective set of tools to visualise and analyse geospatial data. The current workshop is directed for beginners of Python programming language, who have basic understanding on computing and data formats. The primary objective of the workshop is to introduce and give hands on training on selected list of FOSS libraries for geospatial analysis. The workshop as a do it yourself fashion tries to solve two real world problems in Geographical Information System (GIS) and its geospatial data sources. The workshop comprised of three components: Component 1 Python environment and work flow setup, an assisted task of setting up the Docker and Jupyter notebook setup. Setting up the Geographical Information System (GIS) environment with extended discussion. Setting up of GIS tools such as FOSS QGIS and Google earth. This component is comprised of four exercises. 1. Introduction to vector data, 2. Introduction to raster data, 3. binary and text file formats of geospatial data, 4. Introduction to tools of GIS, 5. Introduction to literal programming- Jupyter notebook Component 2 Find characteristics of road network(type of road network, length of the type) within a 1X1 km grid. The data source is Open Street Map (OSM) road network data on a city level (60X60km size). This operation is operationally simple such as measure a line feature but computationally intensive as the operation comprised of geometry within operation on dense road network seen in urban setup. Libraries such as Shapely, Fiona, Geopandas and rtree index will be used for the fast processing of this operation. This component comprised of three exercises 1. Find distance between two points 2. Find distance between two points constrained by another vector 3. Find distance between large number of points in for loop Component 3 Find cloud cover percentage over area of interest. The data source is Landsat satellite imagery. Searching cloud free Landsat images over an Area of Interest for a temporal extent of a year or more is manual and time consuming. Applying cloud cover detection algorithm could make this operation automatic. Libraries such as rasterio, Geopandas, Fiona, and libraries related to landsat algorithms will be used for this task. This component comprised of two exercises 1. Convert the imagery in geotiff into numpy arrays 2. Apply the algorithms to find the cloud cover Workshop Plan Introduction and setup- 30 minutes Component 1- 30 minutes Component 2- 45 minutes Component 3- 45 minutes", - "Last Updated": "12 May, 2018", - "Prerequisites": " Laptop 32bit/64 bit Workshop material is tested on 64 bit computer, it is said to be working in 32 bit, lets experiment! A copy of Docker container image from here , file from the link foss-pt-gsa_v3.tar.gz is 2.5 GB in size, will be using this container for DIY Local copy of Docker toolbox from here for windows 64 bit, for 32 bit Windows, follow this link , if any issue, don't worry, we have a session for setting up the docker! Local copy boot2docker.iso from here , we will be following old method of docker toolbox instead of docker native software for Windows.", + { + "Description": "We propose to build a deep neural network model that can learn to mimic the handwriting of an individual. Given an input text, the model will learn to synthesize the same but in the form of handwritten text", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Curiosity and willingness to learn something new. :)", "Section": "Data science", - "Speaker Info": "I am a research associate at UrbanEmissions.info . My doctoral study was related to interoperable management of data from air pollution monitors and atmospheric models. I used free and open source libraries of Python for the study, especially on geospatial data compilation, analysis and visualization. Freedom and customization of free and open source languages such as of R and Python were immense. After Conda python package manager came into existence, the world of Python was so easy and I started to use Python for most of computing", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Deepayan (~Deepayan137)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/teaching-machines-to-write~e1PVd/", + "title": "Teaching machines to write." + }, + { + "Description": "Many people are moving towards machine learning and artificial intelligence in python without even knowing the basics of the language.\nI would like to focus on the point of knowing the core basics of the language including its syntax and basic commands. After knowing the basics can only a person learn other details of the language. I would after explaining the basics like to focus on some standard libraries like numpy, pandas and matplolib and how they help in data visualisation", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Non", + "Section": "Core python and Standard library", + "Speaker Info": "I am Prabhleen Kaur Bindra, currently pursuing a bachelor's degree in computer science and engineering, from government college of engineering, Aurangabad. I moved towards python from the last 2 months as I developed my interest towards artificial intelligence especially machine learning. I am a novice to the python environment and do not know much details of it though. I would like to share my experience of python", + "Speaker Links": "https://www.linkedin.com/in/prabhleen-b-538ba210", "Target Audience": "Beginner", "Type": "Workshops", - "author": "nishadhka", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/free-and-open-source-libraries-of-python-for-geo-spatial-analysis-and-visualisationmaps-and-satellite-imageries~aQL5e/", - "title": "Free and Open Source libraries of Python for Geo spatial Analysis and Visualisation(Maps and Satellite imageries)" - }, - "180": { - "Content URLs": "https://github.com/bhagvank https://ingeniopythonis.wordpress.co", - "Description": "Video content management, AI, Blockchain and Virtual/Augmented reality technologies are changing the learning management platforms. Customer focused learning systems are emerging in enterprises. Enterprises are structuring their curriculum products to help solve the high value use cases of their customers. Members of the LMS system (python/ Django stack) can tailor their educational experience by choosing courses based on their learning styles. The courses are becoming more effective and helping members retain information. Platforms are differentiating by providing better, faster ways to find relevant content, whenever and wherever learners need it. Modern learning management platform is an end-to-end eLearning solution which has capabilities to create, distribute, edit and manage entire courses from start to finish independent of the content. Educational success and fulfilment are achieved through personalization and optimization of the learner\u2019s path through courses and gaining of competencies. This new class of learning technology vendors is making it possible to augment their systems with cloud-based applications which can be easily integrated with an enterprise-scale technology ecosystem. Enterprises are now tracking and analyzing learning experiences with incredible precision which can be used to improve ongoing program and business outcomes. Tracking and reporting comes in learner-oriented dashboards and reports built for the staff", - "Last Updated": "12 May, 2018", - "Prerequisites": "python, djang", + "author": "prabhleen bindra (~prabhleen)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-baiscs-and-some-standard-libraries~eplpe/", + "title": "Python baiscs and some standard libraries" + }, + { + "Description": "What is Language Model ? Language Model is basically a way to determines how likely a certain sentence is in the language. \"You are reading my LM write up now \" is more likely to be said than \u201cNow you are my LM reading write up\u201d , even though both sentences contain only correct English words; and the sentence \"I had ice-cream with a\" is more likely to end with \"spoon\" than with \"banana\" . LM helps impart this understanding of a language to machines. What\u2019s the need? \"Computers are incredibly fast, accurate and stupid; humans are incredibly slow, inaccurate and brilliant; together they are powerful beyond imagination.\" (Albert Einstein) Computers don\u2019t understand our language! All they are programmed to understand are very specific instructions. Languages we speak are much more complex than that; you can say one thing in multiple ways, for example \"where do I go for party tonight?\" and \"could you give me name of the best restaurant near me?\" -- this is called language variability. As if this was less burden to translate to computers, sometimes you say something that can have several meanings, like \"Look at the dog with one eye\" -- this is called language ambiguity. A human being usually understands the correct meaning in the context of the conversation. A computer... doesn't really. There are many amazing work already done in the field with Siri autocompleting what you forget to type or Google responding to your \u201cokay Google\u201d calls. This said, there still exists immense room for research in the field of making these models more and more intelligent, be it in disambiguation, intent understanding etc. The basis of all starts from a language model. Types Language model is broadly of two types: Statistical LM: A language model is formalized as a probability distribution over a sequence of strings (words), and traditional methods usually involve making an n-th order Markov assumption and estimating n-gram probabilities via counting and subsequent smoothing (Chen and Goodman 1998). The count-based models are simple to train, but probabilities of rare n-grams can be poorly estimated due to data sparsity (despite smoothing techniques) Neural LM: The use of neural networks in the development of language models has become very popular, to the point that it may now be the preferred approach. The use of neural networks in language modeling is often called Neural Network based Language Models, or NNLM for short.\nNeural network approaches are achieving better results than classical methods both on standalone language models and when models are incorporated into larger models on challenging tasks like speech recognition and machine translation. What does it take to build a language model? A corpus large enough to contain multiple variations possible and a good model :D Sample Use cases Autocorrect Automatic summarization Automated reply to emails Spell Corrector (Grammarly)", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Basic idea of NLP Concept of tokenization, lemmatization etc. Just a skim through read of n-gram modeling(if possible, else what use will I be of :P) Basic python coding Scikit learn, NLTK libraries of Python", "Section": "Data science", - "Speaker Info": "Co-Founder of Architect Corner, Bhagvan has around 18 years experience in the industry, ranging from large scale enterprise development to helping incubate software product startups. He has completed a Masters in Industrial Systems Engineering at Georgia Institute of Technology, and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras", - "Speaker Links": "https://www.youtube.com/channel/UChu9J4M85CC7C8hMYp5cgRg/video", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhagvank", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-management-next-generation-platform~dPJ6a/", - "title": "Learning Management : Next Generation Platform" - }, - "181": { - "Content URLs": "https://nim-lang.org http://slides.com/akapatkar/nim-for-python-programmer", - "Description": "Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org As Python programmers, we are used to a language which is expressive, intuitive and versatile. Python is widely lauded for its productivity, minimalistic syntax, standard library feature set and is an inspiration to newer languages like Go, Swift, and Julia. However, there are some areas like speed, distribution, and multicore processing where it lacks a good solution. Nim is a statically typed and high-performance garbage-collected language which builds upon Python\u2019s strengths and addresses someone its weakness in an innovative way. This talk introduces Nim to Python programmers by diving into powerful language design, syntax, data and control structures, static analysis, metaprogramming, portability/distribution and standard library features. At the end of this talk, you should have learned enough to a) get started with Nim on a project b) get familiar with Nim\u2019s growing ecosystem c) leverage/extend existing Python skills on a Nim project. Timeline breakdown: 1) Intro to Nim (10mins) 2) Language tour from Python\u2019s point of view (20 mins) 3) Things you can do with Nim + ecosystem (5 mins) 4) Q&A (5mins", - "Last Updated": "12 May, 2018", - "Section": "Others", - "Speaker Info": "I am a language enthusiast and a Python developer at Netflix. I\u2019ve been learning and using Nim for over a year now and I have benefited immensely from its learnings. There is a strong correlation between Nim and Python and I would like to explain that to the audience and show them a way to think problems using Nim\u2019s construct which I am sure will help them improve their Python skills. I am currently using Nim to write an interpreter for \u2018lox language\u2019. More details here https://github.com/cabhishek/nimlo", - "Speaker Links": "International Conference Talks: PyCon Ukraine 2018 https://2018.uapycon.org/#schedule PyCaribbean 2018 http://pycaribbean.com/schedule.html Python San Sebastian 2017 http://pyss17.pyss.org/", - "Target Audience": "Advanced", + "Speaker Info": "Data Scientist with ~4 years of experience. For more info, please pay a visit to my LinkedIn", + "Speaker Links": "https://www.linkedin.com/in/divyachoudhary28", + "Target Audience": "Intermediate", "Type": "Talks", - "author": "Abhishek Kapatker (~abhishek69)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/nim-for-python-programmers~aO9Ed/", - "title": "Nim for Python Programmers" + "author": "Divya Choudhary (~divya798)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~bqm0b/", + "title": "Language Model (Text Analysis) using Python from scratch" }, - "182": { - "Content URLs": "https://github.com/DL4Jets https://docs.google.com/presentation/d/1dDxxsMkfg8vwMi7QDkDaVwCQnxsaXVh9-6xrgrkLvnY/edit?usp=sharin", - "Description": "Ever wondered if you could build your own deep learning framework for hundreds of users? Well, we did build one and turns out it's not as hard as it sounds. With thousands of people working towards democratising artificial intelligence (AI) , we have seen an explosion in the availability of machine learning libraries that make it simpler to build and deploy models for a wide range of tasks. From finance to art, every field has been revolutionised by the introduction of AI. At the European Organisation for Nuclear Research (CERN) we work on understanding the fundamental particles that constitute the universe by performing various experiments in particle physics. Of late, we have experienced a stratospheric rise in deep learning applications to various problems - RNNs, CNNs, and GANs - that have yielded promising results. Like, this stuff is craaazy, dude. It works! We delve into the development of one such project as it evolves from a set of scripts into a full-blown framework with multifarious applications in high-energy physics. In this talk we will detail the evolution on the DeepJet Python environment. Specifically, we will start with the problem(s) we were facing and how we evolved from a set of scripts hastily patched together to a structured, cross-platform framework built on top of Tensorflow and Keras. The library is a WIP so we're shipping updates on a daily basis with the goal of improving usability with focus on documenting our existing code base. Initially envisaged to support the development of the namesake jet-tagger in the CMS Experiment at CERN, it has grown to encompass multiple purposes within the collaboration. It is aimed at outlining how to go from a set of scripts to building a library that is used by hundreds of scientists in the world's largest physics research collaboration. The presentation will describe the major features the environment sports: simple out-of-memory training a with multi-threaded approach to maximally exploit the hardware acceleration, simple and streamlined I/O to help bookkeeping of the developments, and finally Docker image distribution, to simplify the deployment of the whole ecosystem on multiple datacenters. The talk will also cover future development, mainly aimed at improving user experience. ", - "Last Updated": "12 May, 2018", - "Prerequisites": "Preferred (but not necessary): Experience working with virtual environments or anaconda Basic knowledge of concepts in machine learning", + { + "Content URLs": "https://github.com/bhoom10 https://www.linkedin.com/in/bhoomika-agarwal", + "Description": "Do you spend too much time manually testing your user interfaces? Automation is the answer. Python and Selenium offer a simple but powerful framework to script any testing. In this talk, I will show you how to use the combination of Selenium WebDriver and Python code to automate web UI tests. Follow along and learn how to locate elements, navigate pages, test user interactions with forms and drag-and-drop elements, and use waits to control test timing and execution. The lessons are practical and can be immediately applied to your development workflow. \nTopics include: What is automated testing? Python-Selenium bindings Parsing the DOM structure Locating elements in the DOM Navigating and interacting with pages Explicit and implicit waits", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Python basics HTML basics", + "Section": "Developer tools and Automation", + "Speaker Info": "Bhoomika Agarwal is a developer associate at SAP Labs India. She works in the field of cloud development, machine learning and open source technologies at SAP Labs. Prior to this, she has worked in Sprinklr and completed her graduation in Computer Science from PES Institute of Technology, Bangalore. She has done research in Big Data, Quantum Computing, Linear Algebra and Brain Computer Interface. She has published research papers and given presentations at numerous conferences about these topics. She has published tutorial courses online on Unacamedy and Lynda to disseminate the knowledge she has acquired over the years with experience", + "Speaker Links": "https://www.lynda.com/Python-tutorials/Python-Automation-Testing/651196-2.html https://unacademy.com/user/bhoomika1", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "bhoom10", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/web-ui-automation-using-selenium~ern4e/", + "title": "Web UI automation using Selenium" + }, + { + "Content URLs": "https://github.com/Blaze404/Digit_Recognitio", + "Description": "As neural networks, or in general, machine learning, form the crux of almost all the new technologies , its good to know the internal machinery of these algorithms. We will, in this workshop, train a neural network and study its ins and outs, and finally classify hand written digits with any image of choice . First we will get our hands onto numpy and using that matrix calculus . Next will be learning about gradient descent with multiple multidimensional visualizations using matplotlib( not necessary to be acquainted with). Here we will understand why it is best way to find a needle in a very very big haystack, by performing live comparisons with other methods. And that will be all you'll need to kill in this session. The Neural Net : This will start with structure of neural networks and why it is that way . Then forward propagation , and getting our heads over what is multiplied/dotted with with what. \nThen we'll study about different activation functions and cost functions , and where to use which. And finally, back-propagation , conquering the last enemy and minimizing the cost function for Keanu Reeves like precision. In addition to it, we'll differentiate between stochastic, batch and mini-batch gradient descent , and compare their results. At the end of session, we'll test our neural network on digit images of our choice , and further train the network if necessary", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Introductory knowledge of python Basic calculus Basic Matrix operation", "Section": "Data science", - "Speaker Info": "Swapneel is a computer scientist working at Compact Muon Solenoid (CMS) Experiment at the European Organisation for Nuclear Research where physicists and engineers are probing the fundamental structure of the universe. They use the world's largest and most complex scientific instruments to study the basic constituents of matter \u2013 the fundamental particles. His work at CERN encompasses the creation of a framework that can facilitate the use of deep neural networks and provide a suite of functions to serve multiple use-cases such as jet classification, particle reconstruction, and so on. He is an open-source enthusiast, writing and contributing to various projects in his free time", - "Speaker Links": "https://opensourceforu.com/author/swapneel-mehta/ https://medium.com/@swapneel_mehta http://www.ccdev.in/swapneel-mehta/ https://github.com/swapneel", + "Speaker Info": "I'm Mustafa Qazi, a third year Engineering student in Computer Science, from Govt. College of engineering, Aurangabad. I have four to five months of experience in Python and two months now in machine learning. I have a few projects in machine learning and this being one of them. I know somewhat about big-data jargons like map-reduce, Pig and Spark .Ya, I'm not an Ian Goodfellow in machine learning, but I'll be happy share what I have learned uptill now, and learn further with what experience I'll get from this", + "Speaker Links": "Github LinkedI", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Mustafa Qazi (~mustafa65)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/training-and-optimizing-an-artificial-neural-network-for-classification-from-scratch-with-just-numpy~avr0a/", + "title": "Training and optimizing an Artificial Neural Network for classification from scratch with just numpy." + }, + { + "Content URLs": "Presentatio", + "Description": "Today DASH streams are being used industry wide in Live media (Twitch, Facebook Live, Youtube Live) and would be soon incorporated in static media delivery. We would try to go through most of the use cases we as a consumer or developer would need to utilize these or serve our very own livestream. MPEG DASH (Dynamic Adaptive Streaming over HTTP) is an ISO standard employing adaptive bitrate streaming technique which works by breaking the content into a sequence of small HTTP-based file segments. Each segment contains a short interval of playback time of content, served in several bitrates/codecs, where all of this information is enclosed in a XML media presentation description (MPD). Unlike conventional streaming protocols, this works with standard HTTP servers over TCP, and can fully utilize the benefits of HTTP/2 if both client and server supports it. Naturally, most CDN's and servers can serve the dynamic stream as segmented static media files, with one dynamic entry point which delivers the MPD serving the current time. Due to lack of open libraries handling DASH media, we would be building a DASH utility toolkit. It would be carrying out activities of segmenting (generation), re-merging (consumption), and clipping out a specific period of clip, where the on-media tasks are carried out by ffmpeg. Special care will be taken for \"dynamic\" streams which are live streams. We will go through some production code behind https://esl.atx.sx which is specialized facebook streamer, and some challenges that came up serving its 1 million users", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Conventional streaming media basics asyncio Media descriptors - codecs, timestamps", + "Section": "Networking and Security", + "Speaker Info": "Arnav is currently working as a Developer at hedgehog lab , Hyderabad. He has presented technical talks at previous PyCons. He maintains several pet projects, his most recent https://esl.atx.sx serving the esports community. Having spent a decade behind the computer screen, he often gives valuable insight into Web Architecture, Network Infrastructure & Security and Hardware. When he is unable to find the most elegant and practical way to approach a solution, he is often found reading and outputting chunks of python code. He also takes out time and enjoys mentoring peers on good coding practices. Rest of the time he is deeply devoted leading his DotA team", + "Speaker Links": "arnav.at PyCon India 2017 Talk linkedin.com/in/arnav", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Swapneel Mehta (~SwapneelM)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-deep-learning-framework~dN18b/", - "title": "Building a Deep Learning Framework" + "author": "_arnAV", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handling-dash-streams-generation-consumption-clipping~dwv1b/", + "title": "Handling DASH streams - Generation, Consumption & Clipping" }, - "183": { - "Content URLs": "", - "Description": "A short and crisp interactive session for the first time attendees of PyCon India to help them navigate through the conference and make the most of the next 4 days. 2011 was my first PyCon and in hindsight was a major turning point in my professional life. The experiences I had, the people I met and the friends I made during the conference are still shaping the choices I make and the decisions I take even today. PS: This will be a heavily opinionated talk and the attendees will be requested to weigh the advice being shared and adapt the ones that suit them the most. The audience will be implored to introspect and answer the following and more for them Which talks to attend? How to decide which talks to attend. Can I walk out of a talk in the middle? Should I attend every talk? What is the hallway track? Should I talk to strangers at the conference? How to start talking to strangers? Can I volunteer now that the conference is already happening? The volunteers are awesome people will they accept my help? How can I help? Should I help the volunteers? What is the dev-sprint? How to make the most of the dev sprint? I just started learning python, will people make fun of me if I speak? i need a job, what should I do? I need to hire, what can I do?", - "Last Updated": "12 May, 2018", - "Prerequisites": "A ticket to the conference, willingness to learn, un-learn and re-learn", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has been a part of PyCon India since 2011 where he found enlightenment and confidence to take charge of his education and steered his career in a direction that feels like success at least to him. These days, along with his team at https://essentiasoftserv.com he consults for companies that need assistance maintaining, scaling, and sanitizing their python based codebase", - "Speaker Links": "https://anuvrat.i", + { + "Content URLs": "https://towardsdatascience.com/python-basics-for-data-science-6a6c987f2755 https://towardsdatascience.com/customizing-plots-with-python-matplotlib-bcf02691931f https://towardsdatascience.com/5-quick-and-easy-data-visualizations-in-python-with-code-a2284bae952", + "Description": "Data is a commodity, but without ways to process it, its value is questionable. Data science is a multidisciplinary field whose goal is to extract value from data in all its forms. Machine Learning is a field which is raised out of Artificial Intelligence(AI). It is about extracting knowledge from data and is an integral part of many commercial applications and research projects today, in areas ranging from medical diagnosis and treatment to finding your friends on social networks. My talk will show what data visualisation is, and how it is an essential component for data science. Data visualisation is the key to actionable insights, It allows us to take our complex findings and present them in a way that is informative and engaging to all stakeholders. Also, data visualisation helps us make sense of large amounts of data in quick, easy way in a universal manner. In the end, the consumer of the product of all artificial intelligence or machine learning endeavors will be people. We should ensure results are delivered as actionable, impactful insights to act upon in business and in life. By the time the conference is over, you will have a brief overview of data visualisation and started thinking of how to use data visualisation for your organisation or projects", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Basic knowledge of python. Knowledge of basic graphical representations like bar graphs, scatter plots etc.", + "Section": "Data science", + "Speaker Info": "Myself Saurabh Sunil Deshmukh, currently pursuing my B.E. (Computer Science and Engineering ) from Government college of Engineering Aurangabad, Maharashtra. I started with python three months before considering its scope and popularity in data science and machine learning. I have also studied Big Data analytics using Apache Spark and Apache Hadoop. I would love to share my (just started) journey into data science also eager to hear from everyone else", + "Speaker Links": "https://github.com/Saurabh2798/Python https://github.com/Saurabh2798/introduction_to_ml_with_pytho", "Target Audience": "Beginner", "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-make-the-most-of-pycon-india-2018~dLBva/", - "title": "How to make the most of PyCon India 2018" + "author": "Saurabh Deshmukh (~saurabh15)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-machine-learning-and-importance-of-data-visualisation~egN3d/", + "title": "Introduction to machine learning and importance of data visualisation" }, - "184": { - "Description": "So you started learning python, and you have been able to stitch few lines of code together and it worked, but you do not know why, then this is the talk for you. We will delve into elementary yet obscure concepts that are more often than not skipped by beginners eg why is if _ name_ == _ main_ required in python scripts. et el. In a 3 hour power packed interactive and fully-hands on workshop we shall be learning python from ground up using examples from the real world. Basics of python will be covered with less emphasis on the basics of programming itself. The topics to be covered during the workshop shall include but not be limited to: Hello World Variables Loops and conditionals String Lists, Dictionaries and Tuples. functions File handling classes modules and imports lambda, map and reduce decorators and generators raising and handling exceptions sample exercises for the attendees to work on based on the concepts covered in the first half of the workshop.", - "Last Updated": "12 May, 2018", - "Prerequisites": "The person should be familiar with a *nix based operating system, and the shell should not be alien to them. Attendee should be familiar with the concepts of a hierarchical file system and at least be able to find where their editor saved the file they just created. Knowledge / experience of at least one other programming language will give them an unfair edge", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat, along with his team at https://essentiasoftserv.com consults for python based projects which need help in maintaining, sanitizing and scaling to achieve their true potential.\nHe was one of the four who revamped the https://pydelhi.org community and volunteered for over a dozen https://pythonexpress.com workshops", - "Speaker Links": "https://anuvrat.i", + { + "Description": "The Tor network is a group of volunteer-operated servers that allows people to improve their privacy and security on the Internet. Tor's users employ this network by connecting through a series of virtual tunnels rather than making a direct connection, thus allowing both organizations and individuals to share information over public networks without compromising their privacy. Along the same line, Tor is an effective censorship circumvention tool, allowing its users to reach otherwise blocked destinations or content. Tor can also be used as a building block for software developers to create new communication tools with built-in privacy features. It has become even more important as we kept hearing all the different stories about government surveillance and how the big companies are tracking everyone on Internet. In this talk, I will showcase a few ways any Python developer\ncan make use of the Tor Project inside of their code or infrastructure and provide solutions which thinks about the users' privacy from the beginning. Talk outline Introduction to the Tor Project Simple Python example to do HTTP calls using Tor network Using Stem to control the Tor process for your project Deploying any Python (or any otherone) web application and creating Onion service for the same Points to remember Nyx to monitor More upsteam usecases (onionshare, ooni). The audience will get a chance to learn about the various ways they can connect and use the Tor network using Python", + "Last Updated": "10 Jul, 2018", + "Section": "Networking and Security", + "Speaker Info": "Kushal Das is privacy advocate who is also part of the Tor community team and a CPython Core developer. He is working as SecureDrop developer in the Freedom of the Press Foundation ", + "Speaker Links": " https://kushaldas.in Tor community team", "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/yet-another-introduction-to-python~aKE8d/", - "title": "Yet another introduction to Python" + "Type": "Talks", + "author": "Kushal Das (~kushal)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-tor-network-for-python-developers~ejNle/", + "title": "THe Tor Network for Python developers" }, - "185": { - "Content URLs": "The work in progress repository of all the associated code - fromscratchtoml . The official website of fromscratchtoml . The work in progress python notebooks . The author's github profile ", - "Description": "Each step we take we are closing in into a world of Artificial General Intelligence . All these so called modern inventions ignite a feeling of astonishment among newbie developers across the globe - seeking answers to how these things work from the very basic level. There are myriad resources available on the internet theorising machine learning algorithms. But - what these resources lack is something that can bridge the gap between the theoretical concepts and the actual coding aspects. When a relatively novice developer skim through the code of these libraries he can barely understand what exactly is going on behind the recondite code. In the midst of making the code efficient these libraries often come up with chunks of code which are barely comprehensible. fromscratchtoml The primary goals of this library is - to bridge the gap between the theoretical and coding aspects of machine learning algorithms. To write intuitive blogs as python notebooks so as to juxtapose theory and code . Explaining the fundamentals of the algorithm from the very basics. To minimise the use of external dependencies except the fundamental ones like numpy and matplotlib . To make sure that the developed algorithms are coherent with already existing machine learning frameworks. The library is still in a nascent stage but will take shape in a couple of months. Given that the commit frequency is huge. The audience is requested to be patient. LIME (Local Interpretable Model-Agnostic Explanations) - When you are writing a machine algorithm from scratch you want to make sure that your results are coherent and your model is learning the features it is meant to learn. LIME explains why your model behaved the way it did. I will quote excerpts from their blog below - Imagine we want to explain a classifier that predicts how likely it is for the image to contain a tree frog. We take the image on the left and divide it into interpretable components (contiguous superpixels). As illustrated below, we then generate a data set of perturbed instances by turning some of the interpretable components \u201coff\u201d (in this case, making them gray). For each perturbed instance, we get the probability that a tree frog is in the image according to the model. We then learn a simple (linear) model on this data set, which is locally weighted\u2014that is, we care more about making mistakes in perturbed instances that are more similar to the original image. In the end, we present the superpixels with highest positive weights as an explanation, graying out everything else. Even from a human's perspective these explanations do make sense. BONUS - MrMark (A personal customisable assistant integrated with Google assistant ) - I am going to use Mr. Mark to vocally invoke commands like ' open LIME explanations for RNN , train CNN for face recognition ` etc.. TODO Write timelines. prepare content specific for presenting. DISCLAIMER - All the content related to LIME belongs to their respective owners", - "Last Updated": "11 May, 2018", - "Prerequisites": "Novice level experience of python and development in general. Acquaintance with basic machine learning will be a plus", + { + "Description": "In this era of automation, AI and machine learning have conquered the hearts of Techno enthusiasts.\nAs for this very purpose,\nI would like to focus on training Machine Learning model from scratch . Dividing the session as into 3 groups of which part 2 will be extensively loaded with information. 1: A BIT LOOK-OVER (very precise): Synopsis of Pandas ,numpy,matplotlib,scikit-learn. 2: UNDERSTANDING (crux and to depths) : Understanding Machine Learning ,concepts of training a model ,Theory along with Mathematics ,roles of the above libraries to reach our motive. 3: APPLICATION ( Attention in part 1 and 2 would be enough): Training a model using Linear Regression as well as a model with Logistic Regression", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic Python,basics of mathematics", "Section": "Data science", - "Speaker Info": "I have graduated from IIT ISM Dhanbad in 2017. In daytime I work for a London based startup - ALIS labs , at night I am a bug buster vigilante working for my organization jellAIfish where I am the author of fromscratchtoml . I am also RaRe's incubator program member - the same organization which looks after the reputed topic modelling library gensim . I will be giving a demo prep-talk for this proposal in Hyderabad Python Meetup group on 2nd June 2018", - "Speaker Links": "Author's open source contribution can be seen at his github profile where it all started. Author's current blog where he discussed a 'bit' about the impact of AI. Author's old blog archive where he talked about random developer stuff. Author's another delusional repository which he has trouble explaining to people. Author sometimes also blogs for RaRe technologies . Author is omnipresent on the web by the handle markroxor ", + "Speaker Info": "I am Devyani Sudhir Kulkarni ,\nThird year student and \npursuing B.E. from Government College of Engineering Aurangabad ,Maharashtra.\nAs user of Python I am new to Python community and so acquainted to few features of it .\nData science and field of Analysis has always been of my interests, so I managed to gain bit knowledge learning hadoop ,hive ,spark ,pig and currently using python", + "Speaker Links": "https://www.linkedin.com/in/devyani-kulkarni-a63717135", + "Target Audience": "Beginner", + "Type": "Workshops", + "author": "Devyani_Kulkarni", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/training-machine-learning-model-using-regression~bkNEa/", + "title": "Training Machine Learning model using Regression." + }, + { + "Content URLs": "Note: This talk is inspired by Armin Ronachar's (creator of Flask & a key-note speaker at this PyCon) blog post and a talk by a fellow Mozilla Tech Speaker - Vigneshwer. Armin Ronacher: A Python and Rust love story Dan Callahan - My Python's a little Rust-y - PyCon 2015 Extending Python with Rust (Samuel Cormier-Iijima) All you need to know about FFI", + "Description": "Python is a great language, we all know that. Although, sometimes Python\ncan be a bit of a slowcoach when it comes to performing certain tasks. That's where developers have\nbeen using C/C++, building extensions and integrating them with Python to speed up processes. However, writing C/C++ extensions with strict deadlines and timelines is a bit difficult and also, these low level languages tend to introduce bugs with respect to memory management, lead to segmentation faults and data races. How often have we all faced the dangling pointer error in C/C++ just because we forgot the de-reference a pointer somewhere? Enter Rust , a modern systems programming language that's much better in terms of memory safety, libraries and owing to it's amazing ownership & borrowing principles - keeps the bugs few. documentation up to date and a whole lot more! Bonus - it's completely a open sourced programming language, supported by Mozilla, the non-profit behind the Firefox browser. Basic outline of the talk Python's performance story and the need for native extensions [ 4-5 minutes ] Problems with C/C++ [ 4-5 minutes ] Rust and its success stories [ 8-10 minutes ] Why is Rust so cool!? [ 10-12 minutes ] Ownership & Borrowing, Garbage Collection, FFI (Foreign Function Interface) - along with code snippets Get started with Rust! - links to community & reach-out [ 2 minutes ] Q/A - [ 2 minutes ] Who is this talk for? Python developers who deal with performance issues on a daily basis The curious folk who want to know what Rust is, and why it's growing steadily C/C++ developers who'd like to check out a new systems level programming language Key takeaways A fresh perspective to improve performance metrics in python projects Preview of Rust code and samples Sample of Rust's FFI to ensure python developers can easily call Rust code Note: This talk is inspired by Armin Ronachar's (creator of Flask & a key-note speaker at this PyCon) blog post and a talk by a fellow Mozilla Tech Speaker, Vigneshwer", + "Last Updated": "10 Jul, 2018", + "Prerequisites": " Basic scripting in Python Coding experience in C / C++", + "Section": "Others", + "Speaker Info": "Abhiram has been a part of the open source world in Bangalore for over 3 years now. As a student volunteer in Bangalore, he started contributing to Mozilla as well as FSMK (Free Software Movement Karnataka). After becoming a Mozilla Rep, he has presented over 40 sessions and workshops on python scripting, web dev, Rust and git version control at various venues all over India. Being an internet activist, he was an integral part of the #SaveTheInternet campaign in India during the fight against net neutrality violations. In 2016, he was invited to Mozilla\u2019s Leadership Summit in Singapore to present a talk on running a successful campus club for ~3 years. Currently, he is a Mozilla Tech Speaker well versed in topics like full stack web development, decentralization, scalable infrastructure set up, open source contribution practices and mentoring web enthusiasts . For the past 2 years, he is working at SAP Labs in Bangalore as a full stack web developer and continues to contribute to Mozilla India on a voluntary basis. Recently, he was invited to record a programming course on Rust by the educational website Lynda.com at Los Angeles, California. The course is titled First Look: Rust went live last week", + "Speaker Links": "Events and speaking engagements Mozillians profile - endorsements Mozilla Reps profile - activities and speaking engagements LinkedIn - professional career GitHub - code base & projects Slides.com Speakerdeck.com - presentations and decks Blogs and social media Personal blog Twitter - @abhi12ravi", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Mohit Rathore (~markroxor)", - "created_on": "11 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/from-scratch-to-ml-the-machine-learning-library-you-really-understand-and-explaining-its-predictions-with-lime~dJXya/", - "title": "From scratch to ML - The machine learning library you really understand and explaining its predictions with LIME." + "author": "Abhiram Ravikumar (~abhiram89)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speed-up-your-python-modules-using-rust~elNrb/", + "title": "Speed up your Python modules using Rust" }, - "186": { - "Content URLs": "Repository for the content", - "Description": "Orbital Mechanics/Astrodynamics is one of the most difficult things to understand and take care of! For this simple reason it is called \"Rocket Science\". poliastro is a python package intended to make Astrodynamics Open Source, and easy to understand and visualise. Through the talk, various modules of the poliastro package will be introduced. I will show how we can solve very complex Orbital Mechanics problem in 2 minutes that takes years for a scientist to solve manually! The talk will cover some parts of AstroPy, numba and a bunch of plotting libraries such as matplotlib and plotly", - "Last Updated": "09 May, 2018", - "Prerequisites": "Basic introduction to plotly , matplotlib . Knowledge of some core packages like numpy, etc is beneficial. Knowledge of some of the core Astronomy libraries such as AstroPy is also beneficial", + { + "Content URLs": "Will update this repository in a few days to include sample notebooks : https://github.com/mohdkashif93/PyCon-Graph-Analysis In the meantime you can checkout these repositories for reference Networkx example notebooks Quickstart using graph-tools", + "Description": "In this short tutorial we will be exploring graph networks from the ones mentioned below and work on analysing it various properties and features which will help us to analyse the various patterns that may exist in a network. We will exploring : Community detection in a network Identifying nodes of influence Graph properties like betweeness, centrality, transitivity, clustering coefficients, etc. and what information do they provide about the graph Path finding in a network ( If time permits, we will try to take an image of a maze and find the shortest path out of the maze, by using CV and networkx) Graph Databases in Python Analyzing graphs based on the no. of cliques, k-cliuqes, etc. Visualizing graphs in 2D and 3D space using Python We will be covering the following libraries in this tutorial Networkx graph-tools Neo4J (Graph Database usingPython) Visualization examples using graph-tools, networkx and plot.ly We will be using the following graph data for our analysis: Game of thrones network Marvel Universe Social Graph StackOverflow tag Data Facebook Ego Networks Bonus : If time permits we will take up a random image of a maze and try finding the path out of it, something similar to this (we will be using scikit-image for skeletonizing and networkx for path finding)", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic knowledge for Python will suffic", "Section": "Data science", - "Speaker Info": "I am Shreyas Bapat, half \"Electrical Engineer\" and a passionate developer. I study at Indian Institute of Technology Mandi and constantly contribute to open-source projects. I have contributed to some projects like plotly, dash, poliastro and astroquery. I like Astronomy and related fields a lot and hence keep searching for projects related to that. Also, I am into Deep Learning from quite a time and love tweaking Neural Networks to get amazing results. I am the co-ordinator and maintainer at STAC-IITMandi . I have mentored the Astronomy Code Camp organised by Nehru Planetarium and Astronomical Society of India", - "Speaker Links": "GitHub Profile : shreyasbapat Find my contibutions in Poliastro at #4 : https://github.com/poliastro/poliastro/graphs/contributor", + "Speaker Info": "Hi, I am a Python Developer at Qualcomm, who is super enthusiastic about comics and video games. Sometimes when I get bored I head over to Stackoverflow and solve other people's problems, which is my version of being the friendly neighbourhood spiderman (or Nagraj, since Python translates loosely to Naag or snake in Hindi, so you know... sorry that was a lame reference) :", + "Speaker Links": "Stackoverflow : https://stackoverflow.com/users/story/8160718 Github : https://github.com/mohdkashif93 LinkedIn : https://www.linkedin.com/in/mohdkashif93", + "Target Audience": "Beginner", + "Type": "Talks", + "author": "Mohammed Kashif (~mohdkashif93)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/network-analysis-using-python~bmgre/", + "title": "Network analysis using Python" + }, + { + "Content URLs": "Will Update Shortl", + "Description": "I swear by the Dutch, this is not an ML Workshop * If you are one of the Cool Kids doing Style Transfer , Visual Translation or lurking at arxiv-sanity for what is hot, but wondering how would you take the model beyond Jupyter notebooks? It is my impression that the world of deep learning research is starting to plateau.\nWhat's booming: deploying DL to real-world problems. Fran\u00e7ois Chollet I trod the same path when I started as a founding ML Engineer, over the past two years I have learned that solid engineering is essential for building ML Application at web scale. Productionizing ML model is the last mile journey, the most dreaded and less talked about topic, knowing the right toolchain to automate your build pipeline is essential for APIfiying your ML Models. Typical ML pipeline is accompanied by a big data infrastructure to de-normalize and preprocess the application data to prepare training data, then a microservice to expose the trained model artifact on a runtime component as a service. In this workshop, we will explore the DevOps toolchain to build, train, test, deploy and monitor an ML Model. The focus will be on the toolchain and how to automate the entire process from commit to deployment. To illustrate the whole process we would build a toy recommendation application for an on-demand streaming service provide Pyflix . Application Architecture: Here is the reference Application Architecture for our Pyflix Recommendation Engine. Tentative Agenda Introduction to DevOps Culture Quick Introduction to ML/Big Data tools used in the Application - PySpark, Scikit-Learn (if required) Introduction to Containers and Cloud Infrastructure (Docker and AWS) Introduction to Infrastructure as Code (Terraform and Ansible) Building CI/CD pipeline with Jenkins Building Data Pipeline with Airflow Building RESTful Service with Django Rest Framework Application Architecture Introduction - Pyflix Putting All Together to Build Recommendation Engine", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "The workshop will spin around DevOps tools to build ML Pipeline. We will implement a rudimentary recommendation engine so a basic understanding of ML is enough. We will start with an introduction to DevOps and tools used, however good understanding of DevOps culture will help participants get the most out of the workshop. The edx course on DevOps by Microsoft is a great resource, but not necessary for this workshop. The Demo could be set up either in local with Docker or in the cloud. Basic understanding of Containers Basic understanding of Cloud Infrastructure (AWS) Basic understanding of ML/BigData(PySpark) A little bit of googling on Jenkins and Airflow will help Required Tools For local demo A Linux PC with preferably 8GB Ram, Windows or Mac users needs to perform some additional steps to install Docker. Docker Docker Compose For AWS awscli with configured credentials Terraform", + "Section": "Developer tools and Automation", + "Speaker Info": "By profession, Prabakaran Kumaressha designs algorithms to score complex user interactions, classify use generated contents, derive insights and APIfying them to run at scale. He has been data wrangling for 5+ years, specialized in NLP, uses Jupyter to analyze data that fits his PC memory, PySpark for anything that doesn't, uses Django+DRF to create microservices embracing DevOps culture, mostly on AWS. Occasionally he gives talks at local meetups", + "Speaker Links": "@iPrabakaran Github LinkedI", + "Target Audience": "Intermediate", + "Type": "Workshops", + "author": "Prabakaran Kumaresshan (~prabakaran16)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/devops-for-machine-learning-deploying-ml-models-at-scale~enjEe/", + "title": "DevOps for Machine Learning: Deploying ML Models at Scale" + }, + { + "Content URLs": "http://slides.com/dascommunity/gnupg-for-developers#", + "Description": "\u201cArguing that you don't care about the right to privacy because you have nothing to hide is no different from saying you don't care about free speech because you have nothing to say.\" -Edward Snowden. One\u2019s data is the extension of the person, the digital self. It should be treated as the part of our body. In the present age of massive digital surveillance, it is very difficult to protect the right to privacy. While the developers code or communicate in the digital sphere, she needs to safeguard the privacy rights of the users and the person she is communicating with, respectively. Encryption makes our life easy by protecting the digital self, whereas it makes life difficult for different surveillance agencies. GnuPG is the most trusted tool on that front. GnuPG is the free software version of the OpenPGP cryptographic software suite. This command line application permits one to encrypt and put the signature on your data and communication. There are Python modules which allow easy access to GnuPG\u2019s key management, encryption and signature functionality from Python programs. In the talk, we will learn how to use the same in your Python application, which will in turn help to protect the privacy of the users for your application. Why does this talk matter in current times? Keeping the users safe, keeping their right to privacy protected is one of the major concern for the modern application developers. Using the GnuPG tool with Python binding makes it easier for the application developers to protect the information. This talk will help new Python programmers to use GnuPG to jumpstart using GnuPG in their application safeguarding the users. This talk will also throw some light on the general usage of the GnuPG for the community at large. \u201cPower of community, which is at the heart of the GPG encryption,\u201d says Thenmozhi Soundararajan the Executive Director of Equality Labs", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic Python knowledg", + "Section": "Networking and Security", + "Speaker Info": "Anwesha Das, an Advocate, a PyLady and a core believer of Free and Open Source Software ideology. She provides consultation regarding legal, policy-making and community-related issues in the Free Software and Open Source Software world. She is the Organiser of PyLadies Pune and also leads the PyLadies efforts in India. Privacy and Freedom in the software space are the two of her very close to heart topics. She maintains her personal blog at https://anweshadas.in/. She currently blogs for PSF", + "Speaker Links": "Blogs at https://anweshadas.in/ Previous talk experiences: Keynote at PyCon UK 2017, [Communities and education - exploring together ] (https://www.youtube.com/watch?v=89Kc9ap0h6o&t=8s) PyCon US 2017, [The trends in choosing licenses in Python ecosystem PyCon 2017] (https://www.youtube.com/watch?v=ikT2i4I2LYY) ", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Shreyas Bapat (~shreyasbapat)", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/through-python-to-the-stars-orbital-mechanics-made-easy-and-open-source~dGK5d/", - "title": "Through Python to the Stars! - Orbital Mechanics Made Easy and Open-Source" + "author": "Anwesha Sarkar (~anwesha)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gnupg-for-the-python-application-developers~eplNe/", + "title": "GNUPG for the Python Application Developers" }, - "187": { - "Content URLs": "Github and presentation will be uploaded shortly", - "Description": "Functional programming is an essential part of any programming language. It allows you to harness the language, performing tasks which can replace tens of lines with just one. This is one programming paradigm which enables the programmer to give more importance to functions than classes. Instead of the traditional approach, we shall solve problems by using functions. A ramp up with Collections and a little bit of Object Oriented concepts in python, Functional Programming can be a great curve to harness python's usability and simplicity. At the end of this session, participants will be able to use the collections library in python, list comprehensions , deal with classes , objects and write anonymous functions , lambda expressions and resolve traditional snippets to reduce , map and filters for each of the use case", - "Last Updated": "09 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college folks", + { + "Content URLs": "Content url will be provided after the session in the form of github repo", + "Description": "The human visual system is one of the wonders of the world. The difficulty of visual pattern recognition becomes apparent if you attempt to write a computer program to recognize digits. Neural networks approach the problem in a different way. The idea is to take a large number of handwritten digits, known as training examples, and then develop a system which can learn from those training examples. In other words, the neural network uses the examples to automatically infer rules for recognizing handwritten digits. Furthermore, by increasing the number of training examples, the network can learn more about handwriting, and so improve its accuracy", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic python programming. Certain basic knowledge about neural networks. Curiosity and enthusiasm", "Section": "Core python and Standard library", - "Speaker Info": "Currently working as a Software Development Engineer at Olacabs. http://sameera.me https://www.linkedin.com/in/sameera-sy During my freetime I try the below. https://stackoverflow.com/users/4303216/sameera-sy https://www.hackerrank.com/sameerasy https://leetcode.com/sameerasy https://doselect.com/@sameera.sy", - "Speaker Links": "Below are some of my sample works. https://github.com/sam95 I have also conducted a webinar on JS for JavaScript Meetup Bangalore group. https://github.com/sam95/js-for-newbies-3 https://www.youtube.com/watch?v=JXg1GT6zDGQ", + "Speaker Info": "The speaker is Aditya Patil who is pursuing his carrier in Computer Science Engineering at Government Engineering College Aurangabad,Maharashtra.\nHe is a coding enthusiast familiar with python and java and has major interest in Data science especially Spark, also have background knowledge of hadoop ", "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sameeras", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/functional-programming-with-python~eEQle/", - "title": "Functional Programming with Python" + "Type": "Talks", + "author": "Aditya Patil (~aditya89)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fun-with-visual-pattern-recognition~bqmGb/", + "title": "Fun with visual pattern recognition!" }, - "188": { - "Description": "React has been out there for quite some time now and its arguably one of the hottest front end frameworks out there. But MERN architecture hasn't caught up. And that's what I want to teach/discuss in my talk at pycon. How MERN could be the hottest kid on the block in the upcoming days", - "Last Updated": "08 May, 2018", - "Prerequisites": "Javascript\nBeginner level React.\nLittle to no knowledge of Node, Express and Mongo", - "Section": "Web development", - "Speaker Info": "https://himanshuc3.github.io/\nSolving problems bit by bit. After all, computer is just bits. Cracking PJs and living life to not make the most of it but make the most of me", - "Speaker Links": "https://github.com/himanshuc3\nhttps://medium.com/@himan\nhttps://drive.google.com/file/d/1wzhC56jvrriO6XOogapWE2aOMN8Afsiz/view?usp=sharin", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "08 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mern-could-be-the-buzz-word~bDEkd/", - "title": "MERN could be the buzz word" + { + "Description": "tes", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "tes", + "Section": "Data science", + "Target Audience": "Advanced", + "Type": "Talks", + "author": "bhanu546", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/attention-networks~ernKe/", + "title": "Attention networks." }, - "189": { - "Content URLs": "https://github.com/rahulbajaj0509/Automation-with-Ansibl", - "Description": "Ansible is software that automates software provisioning, configuration management, and application deployment. Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications\u2014 automate in a language that approaches plain English, using SSH, with no agents to install on remote systems. This workshop introduces a beginner to basic fundamentals of Ansible with easy to do hands-on exercises. The workshop introduces basic use cases of Ansible followed by an introduction to Ansible Inventory, Playbooks, Modules, Variables, Conditionals, Loops and Roles. Each mentioned topic is accompanied by a set of coding exercises giving the attendees a hands-on experience in developing Ansible Playbooks. Introduction to configuration management [15 mins] What is configuration management?\nAgent vs Agent-less\nPush and Pull configurations.\nImperative vs Declarative DevOps Concepts [10 mins] Infrastructure as code.\nDeterministic Builds/Deployments.\nIdempotency.\nCommunications channels \u2013 Message Queueing vs SSH Introduction to Ansible [30 mins] Requirements\nInstallation\nConfiguration Working with Ansible [100 mins] Ansible Inventory\nPlaybooks\nModules\nVariables\nConditionals\nLoops\nRoles\nAnsible Galaxy Ansible in DevOps environment [20 mins]\nQuestions and Answers [10 mins", - "Last Updated": "07 May, 2018", - "Prerequisites": "Pre-Requisites Basic Linux Administrator Skills\nOpen mind and spirit to learn. Software Requirements We will be using two centos7 vagrant machines for the workshop. Make sure you are using a Linux distribution and have vagrant configured with any of the providers like libvirt, virtual box, etc.\nIf you are unable to install vagrant on your Linux systems, then you might want to install Fedora operating system and come for the workshop, we can do the rest together", + { + "Content URLs": "https://pypi.org/project/pbr", + "Description": "Python is a great language to get started quickly, it's very easy to learn and it has a huge number of libraries available. One of the biggest challenges I found was how do you package is your code for distribution. Building and packaging is kind of a black box for me when I started with it. How to package your code/library in python and publish to PyPI? What's the difference between wheels and eggs? Do I use setuptools or pbr? What is pbr? Why should I use twine? Should define dependencies in setup.py or requirements? How to push my package in PyPI? History of python packaging. Do I use setuptools or distutils? What is pbr and history or pbr? What is setup.py and what goes in it Features of pbr How to manage versions using pbr ? Demo.", + "Last Updated": "10 Jul, 2018", "Section": "Developer tools and Automation", - "Speaker Info": "Rahul is an Associate Software Engineer, Red Hat. He is a part of the official foreman organization(https://github.com/rahulbajaj0509). He contributes mostly to the Foreman project and is a \u2018Red Hat Certified Specialist in Configuration Management\u2019. He is also the organizer of Foreman Pune Meetups", - "Speaker Links": "Blog: https://rahulbajaj05.wordpress.com/\nGithub: https://github.com/rahulbajaj050", "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Rahul Bajaj (~rahul56)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automation-with-ansible-beginner-to-advanced~azY2e/", - "title": "Automation with Ansible: beginner to advanced" + "Type": "Talks", + "author": "Vamsi (~code-R)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-and-shipping-python-packages-with-reasonableness~avrXa/", + "title": "Building and shipping python packages with Reasonableness" }, - "190": { - "Content URLs": "https://docs.google.com/presentation/d/1DE-_l9N8Scu-M8d_bFxuKQak3TYipEDsGX5HIsB59s0/edit?usp=sharing PS: First Draft, need to organize it better and improve the demos", - "Description": "Dask is a general purpose parallel computing system capable of Celery-like task scheduling, Spark-like big data computing, and Numpy/Pandas/Scikit-learn level complex algorithms, written in Pure Python. Dask has been adopted by the PyData community as a Big Data solution. This talk focuses on the distributed task scheduler that powers Dask when running on a cluster. We will start by comparing Dask with the other solutions that are available for big data ETL and analytics . We will talk about how easily you can parallelize the work loads that you do with your favourite scipy libraries for eg Numpy, Pandas etc. Lastly we will also talk about how you can integrate Dask with your existing code and parallelize it's work load", - "Last Updated": "07 May, 2018", - "Prerequisites": " Good understanding of Python Programming Must have used any scipy library before Nice to have some idea regarding the big data tools available for analytics and ETL", + { + "Description": "At Genpact we built product recommendation category engine which helped our client to avoid practical challenges in current product recommendation algorithms as either consumers ignore their recommendations or the sales team sees no value due to familiarity with the customer\u2019s\nrequirements and preferences from past experience.Our system intelligently categorises the recommendation generated by existing recommendations into three types of opportunities, viz. \u2018Default\u2019, \u2018Linked\u2019, and \u2018Hidden\u2019.\u2018Default\u2019 opportunities are generic recommendations that are independent of customer\u2019s past purchases.\u2018Linked\u2019 opportunities are obvious recommendations that are easy to identify from past experience of the\ndomain. \u2018Hidden\u2019 opportunities go beyond the \u2018Default\u2019 and \u2018Linked\u2019 opportunities, which even the sales team may not be aware of", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Python,Recommendation Engine,Market Basket Analysis", "Section": "Data science", - "Speaker Info": "I am an enthusiastic developer and aspiring entrepreneur who holds a particular passion for the intersection of web development and emerging technologies. I am constantly exploring innovative ways to solve real world problems and improve existing solutions. I genuinely enjoy working with people, taking risks, and developing new applications. I am currently working at Dubizzle as a Associate Software Engineer. Previously I worked at Corridor Funds as a Technology Architect where I built and Architected a data driven Loan valuation and Portfolio Management tool for retail and institutional lenders. I am open source contributor at Gluster, FOSS Asia, NGUI and GDG. Previously I lead a GDG Chapter in Gujarat. I have also spoken at tech meet ups and conferences like Women techmakers, Google Devfest, Google Cloud Next Extended, Mozilla Gujarat, Local GDGs and Startup Gujarat. In addition to that, I am always experimenting with new and interesting side projects", - "Speaker Links": " Github: http://github.com/smitthakkar96 Linkedin: http://linkedin.com/in/smitthakkar96", - "Target Audience": "Intermediate", + "Speaker Info": "Ladle Patel has 6+ years of experience with a focus in Machine learning, Big data and Deep Learning", + "Speaker Links": "https://www.linkedin.com/in/ladlepatel", + "Target Audience": "Advanced", "Type": "Talks", - "author": "smit thakkar (~smitthakkar96)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/dask-distributed-data-science-in-a-pythonic-way~axLPa/", - "title": "Dask: Distributed Data Science in a pythonic way" + "author": "Ladle Patel (~ladle)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/intelligent-categorization-of-product-recommendations-for-enhanced-customer-experience~dwvMb/", + "title": "INTELLIGENT CATEGORIZATION OF PRODUCT RECOMMENDATIONS FOR ENHANCED CUSTOMER EXPERIENCE" }, - "191": { - "Content URLs": "Will be uploading soon", - "Description": "Almost all developers spend countless hours on configuring, tweaking and micro-managing their dotfiles with an obsession to exactly have them like one wants them to be. I do too . Dotfiles are just configuration files like .vimrc and .gitconfig on your OS, that stores the settings you have for applications/environments/tools to make life easier while giving you more portability. Well, do you have to use bash scripts for initial setups of your dotfiles? or do you want to setup your dotfiles but don't want to learn or be limited by Bash? Do you forget to update/maintain your dotfiles periodically? Do you struggle with the installation of applications later on? \n Well, Python could be the answer to all of your problems. With Python, one can easily manage , maintain and do a lot more with their dotfiles. My talk would start with a basic intro of what exactly are Dotfiles? and what is the common way of setting them up? This helps beginners who are new to the topic, get interested and a quick recap of why dotfiles are important for all developers. Building up the momentum by visual queues and comparisons through slides, I would show how exactly Python does the same using Homely as Bash does. Later, work through the more intricate details by talking about the features one can implement using Homely and Python highlighting limitations of bash. Like Automation , Logging , git control , debugging , installation of applications and so much more . Summing up by demonstrating a number of scripts that I will be preparing in-advance to showcase the same features that we just talked about. This helps people grasp the talk, the topic, and \" the why we are doing, what we are doing \" part. Ending the talk , with a round of questions and showing the setup I use after months of searching through dotfiles repositories to leave them open to all the options they can choose from for setting up their dotfiles and pick the best setup from the knowledge they just gained. Sub Category : Developer Tool", - "Last Updated": "07 May, 2018", - "Prerequisites": "A laptop computer running any flavor of Linux. It would help if python 3 is already installed. Coming without a laptop is also fine. The presentation would be enough to understand", - "Section": "Others", - "Speaker Info": "I am a student who also happens to be Linux enthusiast, loves to code in Python, currently, part of Google Summer of Code 2018 under Sugar Labs and an active volunteer at PyDelhi and ALiAS . I friviously collect C&H comic strips because I like to... When I am not busy, I devote my time towards closing issues on GitHub and scooping through my twitter feed. Also, sometimes I like to write my thoughts and the things that I have learned on my blog, Mixster . Check it out", - "Speaker Links": "Professional Profile @ LinkedIn , Contribute @ GitHub , Blog @ Mixster I go by vipulgupta2048 all over the web. Feel free to connect/talk with me", + { + "Description": "The rapid rise of Artificial Intelligence (AI) poses fundamental challenges for the creative industry. Although AI technologies are being adopted at an ever faster pace, Design as an academic discipline has so far failed to provide a convincing answer to the opportunities and challenges of AI. As the number of interfaces between humans and information multiplies, so do the amount of design frameworks that are required to support this technology. When it comes to the Internet of Things (IoT), it\u2019s easy to focus on technological aspects. You can talk about different platforms or discuss which IoT solution might be the best to solve a specific problem. Looking below this layer of technology, it quickly becomes apparent that there are many more aspects that determine the success of the IoT. Not the least of which is the matter of how today\u2019s connected products are designed. Artificial Intelligence (AI), which was designed initially to replace highly repetitive, manual work, has exceeded expectations to complete tasks involving emotional creativity. A limiting factor of IoT is it adds devices and buttons which makes your life more complicated. Now with AI, you\u2019re able to say things like \u2018turn on the lights\u2019 instead of pushing buttons, and it makes life simpler. It is the AI layer of natural language processing that helps IoT improve our lives. In tapping into technology\u2019s potential, it\u2019s important to remember the end user \u2014 us humans. But as more and more experiences are built with ML, it\u2019s clear that UXers still have a lot to learn about how to make users feel in control of the technology, and not the other way round. How do we create experiences that are user friendly and human-centric, while taking advantage of technology? This talk will discuss some of the guidelines focusing on human-centered approach and can be used as reference by any UX designer to help navigate the new terrain of designing ML-driven products. As ML starts to power more and more products and experiences, let\u2019s step up to our responsibility to stay human-centered, find the unique value for people, and make every experience great", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Non", + "Section": "Data science", + "Speaker Info": "I am currently working as an Ecosystem Engagement Manager at Beahead Private Limited. I am an Intel Software Innovator and Organizer for Google Cloud Developer Community, New Delhi. I have been involved in delivering trainings on topics like: Internet of Things, Artificial Intelligence, Machine Learning, Deep Learning, Scratch and App Inventor at various national as well as international platforms. I also execute Google Design Sprints \u2013 a Design Thinking and Agile Development Methodology focused workshop series to improve the UX of applications by focusing on Unified User Experience. In addition to my professional pursuits, I am a volunteer at Headstart Network Foundation, India's largest grass-roots level organization that supports entrepreneurship and start-ups where he helps support and mentor various early stage start-ups and aspiring entrepreneurs. I am also an Oracle Certified Java Professional, Google AdWords Certified Professional and recipient of Google India Challenge Scholarship 2018", + "Speaker Links": "LinkedIn : https://www.linkedin.com/in/sidagarwal04/ Article : https://software.intel.com/en-us/blogs/2018/06/03/bringing-artificial-intelligence-to-the-edge Github : https://github.com/sidagarwal04 Mentions : https://medium.com/@jap.jolly/international-womens-day-celebration-gdg-and-wtm-new-delhi-a2067ae44714, https://pydelhi.org/blog/pydelhi-meetup-31-march-2018.html, https://software.intel.com/en-us/blogs/2018/03/19/intel-black-belt-software-developers-intel-software-innovators-intel-studen", "Target Audience": "Beginner", "Type": "Talks", - "author": "Vipul Gupta (~vipulgupta2048)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/keeping-your-dotfiles-in-check-with-python~dw7Xd/", - "title": "Keeping your Dotfiles in check with Python" + "author": "sidaxy", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-design-of-things-designing-for-ai-iot-conversations-and-the-future~axxqa/", + "title": "The Design of Things: Designing for AI, IoT, Conversations, and The Future" }, - "192": { - "Description": "DNS is a non-encrypted protocol. DNS responses which are sent over UDP or TCP lack confidentiality, privacy and security. DNS often contains password files, geolocations, email service and fax numbers, certificate identity and pinning for TLS and much more. Parsing DNS without encryption would lead to different vulnerabilities such as eavesdropping and spoofing. DNS over HTTPS(DoH) is a web protocol that argues for sending DNS requests and receiving DNS responses via HTTPS connections, hence providing query confidentiality. DoH provides more than just privacy \u2013 it also helps guarantee the integrity of the response users receives their requests. Because the DNS response is invisible between responder and user, ISPs and others in the end-to-end network chain can't interfere with the responses. Moreover, Responses from the use of recursive resolvers to clients are the most vulnerable to undesired or malicious changes, because generally recursive resolvers do not encrypt any of your queries. Henceforth, we would be discussing the implementation and parsing of DNS over HTTPS. Further, we provided added support for handling IPv4 and IPv6 DNS packets (A + AAAA records) as well as support for EDNS for edns-client-subnet usage. The integration with HTTP provides a transport suitable for traditional DNS clients seeking access to the DNS. In the end, we will discuss how our client will be sending DNS queries and get DNS responses over HTTP using https:// and implies TLS security integrity and confidentiality. Furthermore, I plan to put some light on how DNSSEC validation is getting involved here with DNS resolution through HTTP to provide ultimate privacy and security support for \n the DNS packets", - "Last Updated": "06 May, 2018", - "Section": "Networking and Security", - "Speaker Info": "I\u2019m currently in my sophomore year, pursuing an undergraduate degree in Computer Science and Engineering from Amrita University. I\u2019m an active member of a FOSS club in our university(FOSS@Amrita). I started actively contributing to various open source organizations from the year 2016. Initially, I started my career in Open Source by contributing to KDE. I was selected for Season of KDE(KDE-SoK) 2016-17 in which I worked on an astronomy software named called Kstars. Further, I was selected for Google Summer of Code 2017 under KDE, where I worked on a project for a libre graphics software, Krita. My work involved introducing a data sharing module in it. The module enables communication between Krita and a remote KDE server in order to help users save and publish their data online. This also required modifying the underlying framework to enable client/server communication. I have been selected for Google Summer of Code for the 2nd time, where I am working on the project Wget2 under GNU organisation. I GSoC project involves adding support for DNS over HTTPS in Wget2. I was invited as a speaker for KDE India Conference 2017 in IIT Guwahati, where I gave a talk on the topic \u201cObject tracking using OpenCV and Qt\u201d. Further, I will be travelling to Austria on August to give a talk in KDE conference, Akademy and will be talking on the topic \"Strengthen Code Review Culture: rm -rf \u2018Toxic Behaviors", - "Speaker Links": "http://anikethfoss.wordpress.com http://gitlab.com/aniketh01/ https://conf.kde.org/en/Akademy2018/public/speakers/1", + { + "Content URLs": "TB", + "Description": "The Problem As technology becomes cheaper and more available, we start taking it for granted. Nowhere is this more true than in\nmachine learning. As machines become cheaper and data becomes more and more voluminous, our approach to specific\nmachine learning problems often, and understandably, becomes haphazard. Since GPUs are much cheaper and more widely\navailable than ever before, we implicitly believe that throwing enough artificial neurons at a problem will eventually\nsolve it. While this by itself may be true, it is not uncommon for ML practitioners to realize - unfortunately only in\nhindsight - that most of the iterations required to build a successful predictive model were unnecessary. Ironically,\nthese 'missteps' are often what lead us to the correct answer. Solving a machine learning problem is like traversing a\nminefield, where the safest path can only be determined by blowing up a significantly large number of mines. You can\nonly figure out the right approach after making a bunch of mistakes. Since there is no general rule for determining a\n'best model', most things in deep learning can only be solved with trial and error. To a large extent, this 'see what\nsticks' approach cannot be avoided. However it can be curbed significantly, with a structured approach to running\nmachine learning experiments. This structured approach is what this talk is about. The Solution The building blocks of neural networks and the science behind them, including that of their efficiency and\ntrainability, are already very well understood [1]. The heuristics required to ascertain reasonable convergence and\npredictive accuracy have also been studied in detail [2]. On a very high level, these best practices are simply a\nresult of studying and understanding the underlying mathematics of neural networks. However, the lack of a structured\napproach prevents us from fully utilizing these best practices. The ideal way of managing machine learning experiments is\nwith a lab journal. Each machine learning experiment can be reasonably characterized by a hypothesis, a procedure and\nfinally drawing inferences from it's results. A well kept journal would help practitioners from repeating mistakes,\nand narrowing down to the right approach. The Tools This talk will introduce a lab journal powered by Python, and optimized for deep learning experiments. It will allow\nusers to log experiments carried out on sklearn estimators and keras models. The journal also behaves like a\nhyperparameter grid manager, which also alerts the user if the user accidentally re-runs the same experiment on the\nsame data with the same parameters. It will have some meta-learning features which allow for an end-to-end approach to\nmachine learning experiments. [1]. Efficient BackProp [2]. Improving Deep Neural Network", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "An understanding of basic neural network optimization techniques", + "Section": "Data science", + "Speaker Info": "I'm a data scientist based in New Delhi, India. I build data-driven products and the tooling around them for a living. My research interests are in signal processing and computational harmonic analysis. I'm obsessed with applications of machine learning in personal productivity and recommendation systems. I blog about these here ", + "Speaker Links": "https://twitter.com/jaidevd https://github.com/jaidevd https://jaidevd.github.i", "Target Audience": "Intermediate", "Type": "Talks", - "author": "Aniketh Girish (~Aniketh01)", - "created_on": "06 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/privacy-concerns-how-dns-resolves-over-https~avLnd/", - "title": "Privacy concerns: How DNS resolves over HTTPS" + "author": "Jaidev Deshpande (~jaidev)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-the-scientific-method~dyyPd/", + "title": "Deep Learning with the Scientific Method" + }, + { + "Description": "Data quality is a common concern. This talk is about common patterns of data quality errors, how these can be automatically detected in Python, and how they can be fixed (automatically where possible", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Prior experience in data sourcing and transformation, no matter how simpl", + "Section": "Data science", + "Speaker Info": "Anand is a co-founder of Gramener, a data science company, and an aspiring data storytelle", + "Speaker Links": "https://YouTube.com/sanand", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Anand S (~anand40)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cleaning-data-with-python~azzma/", + "title": "Cleaning data with Python" + }, + { + "Description": "Hands training for developers ,data scientists ,researchers in deep learning using TensorFlow and Keras. Approach: Instructor led hands-on bootcamp to implement deep learning based applications for Computer Vision and Natural language processing. Topics covered . 1.Deep learning concepts\n a)Neurons\n b)Neural newtork\n c)Activation functions\n d)Back propagation algorithm\n e)Stochastic gradient descent\n f)Adaptive learning\n g)Momentum\n2.Installation and setup of GPU server on aws/gcloud 3.Deep learning for computer vision\n a)Image classification\n b)Object detection\n c)Image segmentation\n4.Deep learning for Natural language processing\n a)Word Embedding\n b)LSTMs Packaging Deep Learning models\n6.Case Studies", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Python,Basics of linear algebra, Basics of calculu", + "Section": "Data science", + "Speaker Info": "Ladle Patel has 6+ years of experience in Machine learning, Big data and Deep Learning", + "Speaker Links": "https://www.linkedin.com/in/ladlepatel", + "Target Audience": "Advanced", + "Type": "Workshops", + "author": "Ladle Patel (~ladle)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-deep-learning-using-tensorflow-and-keras~aAlPe/", + "title": "Hands on Deep learning using TensorFlow and Keras" + }, + { + "Description": "Vyper is a recently launched python based smart contract programming language. The talk will focus on the features and benefits of Vyper and compare it to Solidity which is similar to Javascript and will include brief demos comparing smart contract implementations.\nTopics to be covered: Features of Vyper and their comparisons to solidity Design pattern of smart contracts Creating smart contracts : demos in both languages", + "Last Updated": "10 Jul, 2018", + "Prerequisites": "Basic knowledge about Blockchain and the Ethereum ecosystem would be helpful", + "Section": "Others", + "Speaker Info": "The speaker is currently working as a research associate at IIIT Delhi and has worked on the Ethereum blockchain as smart contract developer building decentralised applications and web3js based frontends for these applications", + "Speaker Links": "You can reach me at : https://aerophile.github.io https://twitter.com/shubham0075_", + "Target Audience": "Intermediate", + "Type": "Talks", + "author": "Shubham Gupta (~shubham98)", + "created_on": "10 Jul, 2018", + "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/vyper-vs-solidity-smart-contracts-in-the-python-ecosystem~bok3b/", + "title": "Vyper vs Solidity: Smart contracts in the Python ecosystem" } -} \ No newline at end of file +] \ No newline at end of file From 2a2dc64715a34c54298686dd5f93b6b753ee3984 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Fri, 13 Jul 2018 20:09:01 +0530 Subject: [PATCH 08/17] removed unnecessary files --- cfp_crawler/proposal/spiders/crawler.py | 1 + cfp_crawler/proposal/spiders/logs.log | 0 cfp_crawler/proposal/spiders/proposals.json | 4910 ------------------- cfp_crawler/proposal/spiders/test.json | 18 - 4 files changed, 1 insertion(+), 4928 deletions(-) delete mode 100644 cfp_crawler/proposal/spiders/logs.log delete mode 100644 cfp_crawler/proposal/spiders/proposals.json delete mode 100644 cfp_crawler/proposal/spiders/test.json diff --git a/cfp_crawler/proposal/spiders/crawler.py b/cfp_crawler/proposal/spiders/crawler.py index 23a73d8..4610f26 100644 --- a/cfp_crawler/proposal/spiders/crawler.py +++ b/cfp_crawler/proposal/spiders/crawler.py @@ -3,6 +3,7 @@ import json from scrapy import signals + class CrawlerSpider(scrapy.Spider): name = 'crawler' allowed_domains = ['in.pycon.org'] diff --git a/cfp_crawler/proposal/spiders/logs.log b/cfp_crawler/proposal/spiders/logs.log deleted file mode 100644 index e69de29..0000000 diff --git a/cfp_crawler/proposal/spiders/proposals.json b/cfp_crawler/proposal/spiders/proposals.json deleted file mode 100644 index 6e6a799..0000000 --- a/cfp_crawler/proposal/spiders/proposals.json +++ /dev/null @@ -1,4910 +0,0 @@ -[ - { - "Content URLs": "Will add slides later. Have added links to papers in my description", - "Description": "Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources. Compression of Neural Networks (NN) has become a highly studied topic in recent years. The main reason for this is the demand for industrial scale usage of NNs such as deploying them on mobile devices, storing them efficiently, transmitting them via band-limited channels and most importantly doing inference at scale. A number of papers have been published in last few years, proposing different approaches to minimize the footprints of neural networks. The aim of my talk will be to summarize recent developments and techniques in this field, by quoting benchmarks, algorithms and results from papers. On a superficial level, there are two basic types of compression are Network Pruning and Quantization. Network Pruning The motive behind network pruning is to selectively nullify or remove some nodes in order to reduce the size of the NN without losing much accuracy. Not only does this reduce the space required to store the model but also reduces the number of computations for sample. A number of papers in the last 2 years have suggested using Bayesian inferences and Variational Dropout , a probabilistic approach to estimating deterministic weights and selectively pruning some of them after sparsifying respective weight matrices. Quantization Conventionally, weights are stored and operations are performed with 32bit floating point numbers but with the rising need for running models on constrained devices, neural networks can be further compressed by either reducing the number of unique weights by clustering or by reducing the number of bits required represent weights , which also adds a regularizing effect, often resulting in higher accuracy than raw models", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Knowledge of Bayes Theorem, Convolution Neural Networks and common Image Classification datasets", - "Section": "Embedded python", - "Speaker Info": "Hello world. I\u2019m Vishal Gupta, a final year CSE undergrad at SSN, Chennai, India. A Python programmer by heart and ML enthusiast by inspiration, I have worked on a number of different projects, some out of boredom and some for startups. This summer I had to chance to work at Microsoft Research India (Bangalore), on using Bayesian Compression on Object Detection Networks (tiny-yolo) and deploying it on an FPGA board. I was working with a team from IIITD guided by Prof. Saket Anand. I'm also participating in Google Summer of Code 2018 under Debian. Past Experience : Chatbot intern at GoBumpr, Chennai CV intern at XR Labs, Chennai NLP intern at BicycleAI, Banglore", - "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vishal Gupta (~vishal11)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/compression-of-neural-networks~dBmNb/", - "title": "Compression of Neural Networks" - }, - { - "Content URLs": " Winning Solution for Analytics Vidhya Hiring Hackathon Winning Solution for TechGig Machine Learning Hackathon Feature Engineering by Kaggle Expert Organization for learning competitive data science solutions - MLByte ", - "Description": "With advancements in machine learning and artificial neural networks, the answers to previously unknown questions are surfaced. It is the data and the feature engineering aspect that makes this development a great hype of the 21st century. Albeit the algorithm being super complex and extraordinary at solving a task there is always need of feature engineering and crunching the numbers right that help models and neural networks understand the trend and classes better. This proposal shall cover the feature engineering for competitive machine learning problems that are used at platforms like Kaggle, Analytics Vidhya, and HackerEarth. Additionally, this will cover a case study of a winning solution and the inferences from the competitions", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Python Pandas Scikit-learn", - "Section": "Data science", - "Speaker Info": "Mohammad Shahebaz is a data scientist intern at Analytics Vidhya. He is also India's finalist in Microsoft World Championship 2013, the finalist at Master Orator Champion 2016, and has bagged a regional gold medal in International Maths Olympiad (IMO). Currently pursuing out the latest trends in Machine Learning and Artificial Intelligence while winning a competitive position at National level competitions and on Kaggle platform. He loves open-source and have contributed to organizations like Google Web Fundamentals, Scikit Learn, FOSSASIA and is serving as Social Committee Lead at Oppia.org in Google Summer of Code. On a path to set machine learning and artificial intelligence to Indian masses, he open-sources his code and approaches at GitHub and organization MLBYTE", - "Speaker Links": " LinkedIn Profile GitHub Profile - shaz13 Rank 2 at Analytics Vidhya overall leaderboard Mentions Master Orator Champion 1st runner-up of TechGig Machine Learning Hackathon - June 8, 2018", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Mohammad Shahebaz (~shaz13)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/feature-engineering-for-kaggle-and-machine-learning-competitions~e0Pye/", - "title": "Feature Engineering for Kaggle and Machine Learning Competitions" - }, - { - "Description": "draf", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "draf", - "Section": "Core python and Standard library", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mlops-in-draft~e5XKd/", - "title": "MLOps in draft" - }, - { - "Description": "draf", - "Last Updated": "10 Jul, 2018", - "Section": "Core python and Standard library", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/repurposing-yolo-for-detecting-country-stamps~e72yd/", - "title": "repurposing yolo for detecting country stamps ." - }, - { - "Content URLs": "https://github.com/Imaginea/i-tagge", - "Description": "This talk focuses on below two points Software architecture which helps to try different models on different data sets. In the end we will take a real world use case where our architecture helped in speeding up the development process. Bi-Directional LSTM with CRF. ", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Knowledge of Python, ML and DL", - "Section": "Data science", - "Speaker Info": "Anil and Gaurish are part of Data Science team at Pramati technologies. They work on building ML and DL models to solve real world problems", - "Speaker Links": "Anil Kumar - https://www.linkedin.com/in/anil-kumar-reddy-309552ab/ Gaurish - https://www.linkedin.com/in/gaurishthakkar", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anil Kumar Reddy (~anil_kumar46)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-model-for-sequence-tagging~egNGd/", - "title": "Deep Learning model for sequence tagging" - }, - { - "Description": "IBM came up with PowerAI Vision to grab its share - out of available AI Vision 1.2$ billion market opportunity.\nPowerAI Vision Minimum Viable Product (Vision 1.1.0) was GA'ed on May 25th, which can run on standalone Linux and Ubuntu OS, on Nimbix cloud and can also run on IBM Cloud Private. This was an important achievement for IBM as it is expected to accelerate IBM latest Power processor P9 revenue.\nIBM PowerAI Vision is a video and image analysis platform that is built for IBM Power Systems servers, which includes tools and interfaces for anyone with limited skills in deep learning technologies. One can use PowerAI Vision to easily label images and videos that can be used to train and validate a model and perform image / video inferencing. The first regular PowerAI Vision release was MVP. Vision MVP is composed of different Docker images maintained and managed by Kubernetes", - "Last Updated": "10 Jul, 2018", - "Section": "Data science", - "Speaker Info": "Durgarao Simhadri, Sourav Biswas, Madhuri Katragadda - All are working for IBM PowerAI Vision Project in IBM Hyderaba", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sourav Biswas (~sourav31)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/ibm-powerai-vision~b2Q1a/", - "title": "IBM PowerAI Vision" - }, - { - "Content URLs": "https://drive.google.com/file/d/18-0JPLC7d8NduXd00DOk9HzaoJYaXLDd/view?usp=sharin", - "Description": "DevOps is evolving fast with the massive growth that chat-based automation and processes has seen in the recent years. We focus on how to leverage the bot-enabled chat platforms like Slack, MSTeams, Mattermost to your advantage in the context of DevOps using various ChatOps techniques. We also focus on the building and deployment of ChatOps using Python, Django, Docker and Kubernetes. An entire array of DevOps processes such monitoring, CI/CD, analytics can be streamlined through different aspects of ChatOps - bots, cross-application workflows and tying together the internal tools, external tools and microservices in any team's DevOps tool-chain. Productivity, speed and transparency in DevOps can be achieved with the use of ChatOps. Our intention with this workshop would be to focus on the development of ChatOps using Python, Django, Docker and Kubernetes. While several tools are available for developers to build and implement ChatOps for their organization, we believe that the combination of these tools allows for the most versatile, scalable, flexible product. Through our talk, the participants will learn to use these platforms for advanced ChatOps development to automate Dev and DevOps in their teams. We will cover various use cases for all stages of Dev and DevOps cycle. This would give the audience a chance to identify their needs and current state. Next comes the ways these requirements can be tackled through various tools like Python, Django, Docker and Kubernetes(we also cover the advantages and drawbacks of the same). After a well-rounded view of how to implement ChatOps for all kinds of DevOps teams - based on requirements, preferable architecture and choice of language, we end with an interactive Q&A session", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic Python \nDjang", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Ankur, founder and CTO at YellowAnt . I take care of Managing the product architecture, system design and infrastructure design. I have been working on Python for 5 years now. I have intensive knowledge of AWS, Scalling application, Kubernetes, Docker, Databases, etc, and have been conducting developers sessions, meetups and workshops for the same. Prior to founding these companies, I worked with Sasken Communication and IBM India Software labs for 5 years. There, I worked on Perl, C/C++, DB2, XML and other technologies. I have also worked with universities in structuring their Data Mining courses to incorporate real-world use cases, and as a judge for events in TGMC (Organised by IBM) and Engineer (Annual TechFest organised by NITK Surathkal). I have also consulted with Banks, Startups and NGOs for their Tech Stacks", - "Speaker Links": "https://github.com/yellowanthq/\nhttps://twitter.com/YellowAntHQ\nhttps://github.com/ankurrawal\nhttps://twitter.com/ankurrawal1987\nhttps://www.linkedin.com/in/ankur-rawal-53230b13/ https://blog.yellowant.com/6-reasons-why-chatops-make-workplace-better-875659187d0c\nhttps://blog.yellowant.com/how-to-build-a-yellowant-application-in-7-easy-steps-c0feb38c3e5d\nhttps://blog.yellowant.com/advanced-chatops-with-microsoft-teams-part-1-1845acdc11a5\nhttps://blog.yellowant.com/advanced-chatops-with-microsoft-teams-part-2-real-world-use-cases-6470975e574", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ankur Rawal (~ankurrawal)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/accelerating-devops-with-chatops-using-python-django-docker-and-kubernetes~b80gb/", - "title": "Accelerating DevOps with ChatOps using Python, Django, Docker and Kubernetes" - }, - { - "Content URLs": "tes", - "Description": "tes", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "tes", - "Section": "Core python and Standard library", - "Speaker Info": "tes", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/ner-in-legalcontracts~b64Ve/", - "title": "NER in legalcontracts" - }, - { - "Content URLs": "https://www.jaegertracing.io", - "Description": "Distributed tracing is a technique for monitoring & profiling systems built on microservices architecture. Distributed tracing is quickly becoming a must-have component in the tools that organisations use to monitor their complex, microservice-based architecture. Jaeger is an open source tool and part of CNCF project released and worked by Uber. Outline: Introduction to Microservices\nDistributed Tracing & OpenTracing standards\nUsing Jaeger to monitor microservices-based distributed systems covering: - Distributed context propagation\n - Distributed transaction monitoring\n - Root cases analysis\n - Service dependency analysis\n - Performance / Latency optimization Implementing Tracing with python library live and transforming existing code to traceable code.\nDemo Jaeger with an (python code) example from a monitoring perspective (specific to solve latency issue).\nDemo of tracing to collect application metrics. And more", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Knowledge of Python and application development", - "Section": "Core python and Standard library", - "Speaker Info": "Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "https://www.linkedin.com/in/vivsridh/ https://twitter.com/vivek_sridha", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Vivek Sridhar (~vivek861)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tracing-http-request-latency-using-jaeger-with-python~e3POa/", - "title": "Tracing HTTP request latency using Jaeger with Python" - }, - { - "Content URLs": "https://github.com/RushikeshJachak https://github.com/Heisenberg020", - "Description": "Many people are claiming to learn machine learning using standard libraries while not knowing the math behind it. My objective is clear to implement and give a intuition of linear regression model while at the same time telling what steps makes a model good fit for training sets. It includes:- A. Getting comfortable with libraries by actual implementation Introduction to numpy, pandas and matplotlib Exploring data using pandas Exploring relation between various variables using matplotlib. Knowing what are the problems are for a bad model. B.Exploratory Data Analysis :- Classifying features as continuous or categorical. Handling missing data. Feature Extraction and Selection. Correlation and causation. Dummy Variables Visualizing Data C. Implementation of Model Cost function Gradient Descent Normal Equations ", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic knowledge of python like defining function, declaring variables. Knowledge of Matrix Basic Mathematics.", - "Section": "Data science", - "Speaker Info": "I am Rushikesh Jachak, Currently pursuing computer science and engineering in government college of engineering, Aurangabad. I moved towards python from last two months due to my interest in data science field especially machine learning. I am complete novice in python environment, i do not know the hooks and crux of python but i do believe the more you share more you learn.So i would definitely like to share my journey till know and and knowledge of maths and intuition behind the most common algorithm of ML. I also have a bit knowledge of Big-data technologies such as Hadoop hive, and poses a keen interest in field of Data Science", - "Speaker Links": "https://github.com/Heisenberg0203/Kaggle https://github.com/Heisenberg0203/MachineLearning/tree/master/Week1 https://www.linkedin.com/in/rushikesh-jachak-44b723135", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "rushikesh jachak (~rushikesh)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/implementation-of-linear-regression-from-scratch-using-numpy-pandas-and-matplotlib~e9PBd/", - "title": "Implementation of Linear Regression from scratch using numpy, pandas and matplotlib" - }, - { - "Content URLs": " Research paper - Vritthi framework for IT recruitment based on machine learning techniques Slides of other talks can be found on Speakerdeck", - "Description": "Abstract Want to learn how you can use the huge amounts of open data available on social platforms like Twitter, GitHub and StackOverflow to build a profile for a software developer? Yes, it's possible using python's sci-kit library. Mine data, extract features, compute quotients and finally, visualize! Detailed description The talk will start with an overview of data mining and machine learning concepts, during the course of which common misconceptions about data science would be cleared. As a real life example, the problem statement of job-seekers and recruitment is introduced. This then leads to the solution Vritthi , an open source project and then the technical aspects follow. Vritthi uses data mining and machine learning to help job-seekers to understand their skill sets and take up courses that would help them improve their technical expertise. Vritthi can automatically calculate a professional quotient by collating data from websites like GitHub, StackOverFlow and LinkedIn. This analysis is a result of parsing thousands of similar profiles available through the APIs of the above websites. GitHub archive is one of our data sources which actually helps set standards to coding competencies of individual profiles. Collection of data from GitHub using its API is explained in detail, along with the feature-set used to analyze profiles. Once the data is collected from the API, it passes through the data cleaning phase after which a set of features are extracted. These features could be as simple as number of commits, number of projects in a particular programming language, and so on. Right after this, python sci-kit is used to build the data model that\u2019s required for analysis. A supervised learning model is used which consists of two phases - clustering profiles and computing quotient values. Once the data model is ready, computing technical quotient values per programming language or skill is focused upon. For example, \u201cprogramming languages used\u201d is one of the attributes of the feature vector. Finally, the computed quotients are visualized using a web application which uses Python\u2019s Bokeh visualization library. Thus, classic data mining and machine learning have been employed on openly available data to solve a specific problem statement. Who is this talk for? Python developers who\u2019d like to explore sci-kit Web developers who\u2019d like to explore python\u2019s bokeh library for data viz. Entrepreneurs who would like to see how a practical use case is solved using open data What will participants take away? Live example of machine learning and how to adopt python sci-kit library in a ML use case A solid understanding of data science and how it can solve problems in real life Deeper understanding of GitHub\u2019s API for data extraction and mining", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic programming knowledge in any object-oriented language would be helpful", - "Section": "Data science", - "Speaker Info": "Abhiram has been a part of the open source world in Bangalore for over 3 years now. As a student volunteer in Bangalore, he started contributing to Mozilla as well as FSMK (Free Software Movement Karnataka). After becoming a Mozilla Rep, he has presented over 40 sessions and workshops on python scripting, web dev, Rust and git version control at various venues all over India. Being an internet activist, he was an integral part of the #SaveTheInternet campaign in India during the fight against net neutrality violations. In 2016, he was invited to Mozilla\u2019s Leadership Summit in Singapore to present a talk on running a successful campus club for ~3 years. Currently, he is a Mozilla Tech Speaker well versed in topics like full stack web development, decentralization, scalable infrastructure set up, open source contribution practices and mentoring web enthusiasts . For the past 2 years, he is working at SAP Labs in Bangalore as a full stack web developer and continues to contribute to Mozilla India on a voluntary basis. Recently, he was invited to record a programming course on Rust by the educational website Lynda.com at Los Angeles, California. The course is titled First Look: Rust and it went live last week", - "Speaker Links": "Events and speaking engagements Mozillians profile - endorsements Mozilla Reps profile - activities and speaking engagements LinkedIn - professional career GitHub - code base & projects Slides.com Speakerdeck.com - presentations and decks Blogs and social media Personal blog Twitter - @abhi12ravi", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Abhiram Ravikumar (~abhiram89)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/harnessing-open-data-to-build-user-profiles-using-python-sci-kit~ejNPe/", - "title": "Harnessing Open Data to build user profiles using python sci-kit" - }, - { - "Content URLs": "Coming Soo", - "Description": "While majority of the time is spent in differentiating the programmer and designer, this talk aims to use python to mix the two to produce art. Don\u2019t understand read more: Disclaimer! \nYou won\u2019t be taught: What is art or programming. Writing Python syntax How to start loving python How to live life How to make money How to design You will learn about: How to use python to evolve as a designer Eventually, how to appreciate art and art in nature A different perspective towards art Ease your work as a designer and hence be more productive Make visually compelling art with python Generate complex art that would be exhausting to produce with GUI based softwares How to go beyond just making basic geometry shapes in your Computer Graphics class at University Typographic scripting i.e. Python scripting for font design Scripting with python to edit images Python to design layouts This talk is not just about the technology used. Hence, you might start loving python eventually or at least love for it might increase. Mine increased 10-folds, but you aren\u2019t expected for the same. Still, don\u2019t understand? Come to the talk", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Must know python\u2019s basic syntax Have desire to be creative but technical with code Interested in exploring the thin line between chaos and order", - "Section": "Others", - "Speaker Info": "Tanya Jain has been designing and making art for about 10 years now, and plans to start a design studio of her own with the name of Magvaari. She has previously designed for various conferences including PyDelhiConf. She has publically spoken at tech communities like PyDelhi, LinuxChix India. Tanya is currently in 3rd year of her BTech degree at Amity University, Noida and is an active member at the ALiAS tech club. While out in public places, she has a constant thought on how can a place be evolved with design. And hence it also reflects her love for travel! She has a keen interest in learning computer related technologies. Other than designing, Tanya is interested in Data Science and Machine Learning. Yet whatever she learns, she somehow finds the way to join various topics and that is how this talk proposal emerged", - "Speaker Links": " LinkedIn , GitHub://Tanya-Jain Website: tanya-jain.xyz Blog: stellaradventurer.com", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanya Jain (~Tanya-Jain)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-scripting-for-graphic-designers~bkNNa/", - "title": "Python Scripting for Graphic Designers" - }, - { - "Description": "In this hands-on course using Python, participants will learn how to use Python for various aspects of Data Engineering Participants will work on a real-life scenario of Ingesting data Cleaning & Transforming data Perform Exploratory Data Analysis (EDA) on the dataset As part of this exercise participants will be introduced to various useful Python libraries that every Data Engineer should know. The session will cover various other aspects of a robust, scalable data pipeline", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "This is an intermediate level hands-on course on Python. To benefit from this course the participants are expected to have Basic familiarity with Python programming Conceptual knowledge of data pipelines, relational data and big data Using Jupyter Python notebook environment", - "Section": "Data science", - "Speaker Info": "Arijit Saha Arijit Saha is a data professional with over sixteen years of industry work experience in architecting, designing & developing large-scale data products, platforms & solutions for both big & medium size enterprises. Currently he is busy architecting Enterprise AI data platform & products in one of the fastest growing startup Noodle.ai. He is an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Data Architecture, Big Data Analytics, Geospatial Analytics and application of Artificial Intelligence in Enterprises. Sumit Sen Sumit Sen is a software development professional with more than 15 years of development experience in areas of embedded systems, mobile and virtualization technologies. Currently he is working on the architecture of the AI as a Service offerings of Noodle.ai, an exciting startup in the Enterprise AI space. He is passionate about High Performance Computing, virtualization and IoT systems", - "Speaker Links": "Arijit Saha LinkedIn: https://www.linkedin.com/in/arijitsaha/ Twitter: @arijitsaha Sumit Sen LinkedIn: https://www.linkedin.com/in/sumitsenddn", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "arijit.saha", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-for-data-engineers~bmg9e/", - "title": "Python for Data Engineers" - }, - { - "Description": "Over the years, machine learning has been on the rise. It is so powerful that it almost tempt us to skip the Exploratory Data Analysis phase. It is not a very good idea to just feed data into a black box and wait for the results.\nExploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods.Pandas is a Python library that provides extensive means for data analysis.In conjunction with Matplotlib, Pandas provides a wide range of opportunities for visual analysis of tabular data", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic knowledge of python", - "Section": "Data science", - "Speaker Info": "I am Purva Chaudhari ,3rd year student of computer science and engineering from Government Engineering College ,Aurangabad.I have a bit knowledge of Big-data technologies such as Hadoop,hive,spark etc.I have started python from last 2 months as I'm interested in Data Analytics and Data Science", - "Speaker Links": "https://www.linkedin.com/in/purva-chaudhari-044007165", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Purva_Chaudhari", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploratory-data-analysis-using-pandas-matplotlib~elNgb/", - "title": "Exploratory Data Analysis using pandas ,matplotlib" - }, - { - "Content URLs": "Body to body movement transfer using GANs: https://github.com/rahulbaburaj/body2bod", - "Description": "The workshop will be divided into two sessions spent learning about generative modelling. Both sessions will touch upon Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). We will be teaching about the different types of GANs and VAEs and their architectures in general. We will conduct a demo at the end of each session, where we will be generating images of new types of Pokemon. At the end of the sessions, we will be comparing the results from the images that each generative model's AI has produced. It will be interesting to witness the unfolding of new Pokemon, and learn the reasoning behind the output.", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Participants should have a basic understanding about how python works. Also, some basic knowledge on machine learning concepts will be useful", - "Section": "Others", - "Speaker Info": "Lovish, Rahul and Vishnu are all Research Fellows at the Center for Visual Information Technology at International Institute of Information Technology, Hyderabad", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Vishnu Sashank (~vishnu59)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gotta-gan-em-all-pokecon~enjWe/", - "title": "Gotta GAN 'em all! PokeCON!" - }, - { - "Content URLs": " Github Repo : https://github.com/raptor419/uavtalk Slides : http://blueraptortech.com/uavtalk", - "Description": "They might not be delivering our mail ( or Pizzas ) yet , but drones are now intelligent, simple, and reliable enough that they cannot be considered as just toys but as formidable business tools. This talk will briefly go into the inner workings of UAV systems and will demonstrate how python tools can be used to make fully autonomous drones for various purposes. The contents of this talk include: Flight Controllers and control theory ( Ardupilot ) MAVLink ( pymavlink , mavproxy ) Real-time computer vision ( OpenCV , Tensorflow ) DroneKit-Python Obstacles and Implications of IoD We will go extensively into the abilities of DroneKit-Python and into the future of the Internet of Drones using real-life examples such as pest control ( ScAIRcrow ), \ncommercial mapping ( Drone Deploy ) and delivery ( Flirtey ) etc. The talk will end with a small drone taking a picture of all of us, autonomously ofcourse, demonstrating the discussed topics and the formidable ability of autonomous drones", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Python Programming, the concept of APIs and libraries Computer Vision basics The IoT concept An eager mind", - "Section": "Embedded python", - "Speaker Info": "Harsh has been tinkering with technology since he was 9, he received the presidential gold award for National Child Award for Exceptional Achievement by Shree Pranav Mukherjee in 2012. A CS undergrad at IIIT Delhi, he is also the Director of the establishment BlueRaptorTech , which is venturing into the field of big data based algorithmic day trading. A CV Specialist for Aurora , the aerial robotics team of IIIT Delhi, and an AI/ML HackerSpace Intern for Flytbase , a US-based Internet of Drones specialized platform, he has worked extensively and is passionate about drones and has attended many AUV events. His expertise in UAVs lies in making intelligent solutions by the intersection of Computer Vision and Precision Robotics", - "Speaker Links": " LinkedIn GitHub Facebook Website BlueRaptorTech", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harsh Bandhey (~harsh31)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/making-uavs-autonomous-and-the-internet-of-drones~bokBb/", - "title": "Making UAVs autonomous and the Internet of Drones" - }, - { - "Description": "DNS is a non-encrypted protocol. DNS responses which are sent over UDP or TCP lack confidentiality, privacy and security. DNS often contains password files, geolocations, email service and fax numbers, certificate identity and pinning for TLS and much more. Parsing DNS without encryption would lead to different vulnerabilities such as eavesdropping and spoofing. DNS over HTTPS(DoH) is a web protocol that argues for sending DNS requests and receiving DNS responses via HTTPS connections, hence providing query confidentiality. DoH provides more than just privacy \u2013 it also helps guarantee the integrity of the response users receives their requests. Because the DNS response is invisible between responder and user, ISPs and others in the end-to-end network chain can't interfere with the responses. Moreover, Responses from the use of recursive resolvers to clients are the most vulnerable to undesired or malicious changes, because generally recursive resolvers do not encrypt any of your queries. Henceforth, we would be discussing the implementation and parsing of DNS over HTTPS. Further, we provided added support for handling IPv4 and IPv6 DNS packets (A + AAAA records) as well as support for EDNS for edns-client-subnet usage. The integration with HTTP provides a transport suitable for traditional DNS clients seeking access to the DNS. In the end, we will discuss how our client will be sending DNS queries and get DNS responses over HTTP using https:// and implies TLS security integrity and confidentiality. Furthermore, I plan to put some light on how DNSSEC validation is getting involved here with DNS resolution through HTTP to provide ultimate privacy and security support for \n the DNS packets", - "Last Updated": "06 May, 2018", - "Section": "Networking and Security", - "Speaker Info": "I\u2019m currently in my sophomore year, pursuing an undergraduate degree in Computer Science and Engineering from Amrita University. I\u2019m an active member of a FOSS club in our university(FOSS@Amrita). I started actively contributing to various open source organizations from the year 2016. Initially, I started my career in Open Source by contributing to KDE. I was selected for Season of KDE(KDE-SoK) 2016-17 in which I worked on an astronomy software named called Kstars. Further, I was selected for Google Summer of Code 2017 under KDE, where I worked on a project for a libre graphics software, Krita. My work involved introducing a data sharing module in it. The module enables communication between Krita and a remote KDE server in order to help users save and publish their data online. This also required modifying the underlying framework to enable client/server communication. I have been selected for Google Summer of Code for the 2nd time, where I am working on the project Wget2 under GNU organisation. I GSoC project involves adding support for DNS over HTTPS in Wget2. I was invited as a speaker for KDE India Conference 2017 in IIT Guwahati, where I gave a talk on the topic \u201cObject tracking using OpenCV and Qt\u201d. Further, I will be travelling to Austria on August to give a talk in KDE conference, Akademy and will be talking on the topic \"Strengthen Code Review Culture: rm -rf \u2018Toxic Behaviors", - "Speaker Links": "http://anikethfoss.wordpress.com http://gitlab.com/aniketh01/ https://conf.kde.org/en/Akademy2018/public/speakers/1", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Aniketh Girish (~Aniketh01)", - "created_on": "06 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/privacy-concerns-how-dns-resolves-over-https~avLnd/", - "title": "Privacy concerns: How DNS resolves over HTTPS" - }, - { - "Content URLs": " Slides for the talk - DotPython Demo Dotfiles Repository - DotvFiles", - "Description": "Almost all developers spend countless hours on configuring, tweaking and micro-managing their dotfiles with an obsession to exactly have them like one wants them to be. I do too . Dotfiles are just configuration files like .vimrc and .gitconfig on your OS, that stores the settings you have for applications/environments/tools to make life easier while giving you more portability. Well, do you have to use bash scripts for initial setups of your dotfiles? or do you want to setup your dotfiles but don't want to learn or be limited by Bash? Do you forget to update/maintain your dotfiles periodically? Do you struggle with the installation of applications later on? \n Well, Python could be the answer to all of your problems. With Python, one can easily manage , maintain and do a lot more with their dotfiles. My talk would start with a basic intro of what exactly are Dotfiles? and what is the common way of setting them up? This helps beginners who are new to the topic, get interested and a quick recap of why dotfiles are important for all developers. Building up the momentum by visual queues and comparisons through slides, I would show how exactly Python does the same using Homely as Bash does. Later, work through the more intricate details by talking about the features one can implement using Homely and Python highlighting limitations of bash. Like Automation , Logging , git control , debugging , installation of applications and so much more . Summing up by demonstrating a number of scripts that I will be preparing in-advance to showcase the same features that we just talked about. This helps people grasp the talk, the topic, and \" the why we are doing, what we are doing \" part. Ending the talk , with a round of questions and showing the setup I use after months of searching through dotfiles repositories to leave them open to all the options they can choose from for setting up their dotfiles and pick the best setup from the knowledge they just gained. Sub Category : Developer Tool", - "Last Updated": "07 May, 2018", - "Prerequisites": "A laptop computer running any flavor of Linux. It would help if python 3 is already installed. Coming without a laptop is also fine. The presentation would be enough to understand", - "Section": "Others", - "Speaker Info": "I am a student, a Linux enthusiast, loves to code in Python, currently, part of Google Summer of Code 2018 under Sugar Labs, mentoring the GirlScript Summer of Code project, WTF Python and an active volunteer for PyDelhi since 2016 and managing an open-source community in my college, ALiAS . I friviously collect C&H comic strips because I believe everyone should have a hobby and that is mine. I have spoken before at Local User Meetup groups and this would be my first time speaking for PyCon India. When I am free, I devote my time towards closing issues on GitHub and scooping through my Twitter feed. I like to share my thoughts and meet new people. Hence, been writing for a year now, for many organizations such as OpenEBS and TheGeekyWay. Also, I have my own blog, Mixster ", - "Speaker Links": "Professional Profile available @ LinkedIn , Contribute to FOSS projects @ GitHub , Blog @ Mixster I go by vipulgupta2048 all over the web. Feel free to connect/talk with me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vipul Gupta (~vipulgupta2048)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/keeping-your-dotfiles-in-check-with-python~dw7Xd/", - "title": "Keeping your Dotfiles in check with Python" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1DE-_l9N8Scu-M8d_bFxuKQak3TYipEDsGX5HIsB59s0/edit?usp=sharing PS: First Draft, need to organize it better and improve the demos", - "Description": "Dask is a general purpose parallel computing system capable of Celery-like task scheduling, Spark-like big data computing, and Numpy/Pandas/Scikit-learn level complex algorithms, written in Pure Python. Dask has been adopted by the PyData community as a Big Data solution. This talk focuses on the distributed task scheduler that powers Dask when running on a cluster. We will start by comparing Dask with the other solutions that are available for big data ETL and analytics . We will talk about how easily you can parallelize the work loads that you do with your favourite scipy libraries for eg Numpy, Pandas etc. Lastly we will also talk about how you can integrate Dask with your existing code and parallelize it's work load", - "Last Updated": "07 May, 2018", - "Prerequisites": " Good understanding of Python Programming Must have used any scipy library before Nice to have some idea regarding the big data tools available for analytics and ETL", - "Section": "Data science", - "Speaker Info": "I am an enthusiastic developer and aspiring entrepreneur who holds a particular passion for the intersection of web development and emerging technologies. I am constantly exploring innovative ways to solve real world problems and improve existing solutions. I genuinely enjoy working with people, taking risks, and developing new applications. I am currently working at Dubizzle as a Associate Software Engineer. Previously I worked at Corridor Funds as a Technology Architect where I built and Architected a data driven Loan valuation and Portfolio Management tool for retail and institutional lenders. I am open source contributor at Gluster, FOSS Asia, NGUI and GDG. Previously I lead a GDG Chapter in Gujarat. I have also spoken at tech meet ups and conferences like Women techmakers, Google Devfest, Google Cloud Next Extended, Mozilla Gujarat, Local GDGs and Startup Gujarat. In addition to that, I am always experimenting with new and interesting side projects", - "Speaker Links": " Github: http://github.com/smitthakkar96 Linkedin: http://linkedin.com/in/smitthakkar96", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "smit thakkar (~smitthakkar96)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/dask-distributed-data-science-in-a-pythonic-way~axLPa/", - "title": "Dask: Distributed Data Science in a pythonic way" - }, - { - "Content URLs": "https://github.com/rahulbajaj0509/Automation-with-Ansibl", - "Description": "Ansible is software that automates software provisioning, configuration management, and application deployment. Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications\u2014 automate in a language that approaches plain English, using SSH, with no agents to install on remote systems. This workshop introduces a beginner to basic fundamentals of Ansible with easy to do hands-on exercises. The workshop introduces basic use cases of Ansible followed by an introduction to Ansible Inventory, Playbooks, Modules, Variables, Conditionals, Loops and Roles. Each mentioned topic is accompanied by a set of coding exercises giving the attendees a hands-on experience in developing Ansible Playbooks. Introduction to configuration management [15 mins] What is configuration management?\nAgent vs Agent-less\nPush and Pull configurations.\nImperative vs Declarative DevOps Concepts [10 mins] Infrastructure as code.\nDeterministic Builds/Deployments.\nIdempotency.\nCommunications channels \u2013 Message Queueing vs SSH Introduction to Ansible [30 mins] Requirements\nInstallation\nConfiguration Working with Ansible [100 mins] Ansible Inventory\nPlaybooks\nModules\nVariables\nConditionals\nLoops\nRoles\nAnsible Galaxy Ansible in DevOps environment [20 mins]\nQuestions and Answers [10 mins", - "Last Updated": "07 May, 2018", - "Prerequisites": "Pre-Requisites Basic Linux Administrator Skills\nOpen mind and spirit to learn. Software Requirements We will be using two centos7 vagrant machines for the workshop. Make sure you are using a Linux distribution and have vagrant configured with any of the providers like libvirt, virtual box, etc.\nIf you are unable to install vagrant on your Linux systems, then you might want to install Fedora operating system and come for the workshop, we can do the rest together", - "Section": "Developer tools and Automation", - "Speaker Info": "Rahul is an Associate Software Engineer, Red Hat. He is a part of the official foreman organization(https://github.com/rahulbajaj0509). He contributes mostly to the Foreman project and is a \u2018Red Hat Certified Specialist in Configuration Management\u2019. He is also the organizer of Foreman Pune Meetups", - "Speaker Links": "Blog: https://rahulbajaj05.wordpress.com/\nGithub: https://github.com/rahulbajaj050", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Rahul Bajaj (~rahul56)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automation-with-ansible-beginner-to-advanced~azY2e/", - "title": "Automation with Ansible: beginner to advanced" - }, - { - "Description": "React has been out there for quite some time now and its arguably one of the hottest front end frameworks out there. But MERN architecture hasn't caught up. And that's what I want to teach/discuss in my talk at pycon. How MERN could be the hottest kid on the block in the upcoming days", - "Last Updated": "08 May, 2018", - "Prerequisites": "Javascript\nBeginner level React.\nLittle to no knowledge of Node, Express and Mongo", - "Section": "Web development", - "Speaker Info": "https://himanshuc3.github.io/\nSolving problems bit by bit. After all, computer is just bits. Cracking PJs and living life to not make the most of it but make the most of me", - "Speaker Links": "https://github.com/himanshuc3\nhttps://medium.com/@himan\nhttps://drive.google.com/file/d/1wzhC56jvrriO6XOogapWE2aOMN8Afsiz/view?usp=sharin", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "08 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mern-could-be-the-buzz-word~bDEkd/", - "title": "MERN could be the buzz word" - }, - { - "Content URLs": "Github and presentation will be uploaded shortly", - "Description": "Functional programming is an essential part of any programming language. It allows you to harness the language, performing tasks which can replace tens of lines with just one. This is one programming paradigm which enables the programmer to give more importance to functions than classes. Instead of the traditional approach, we shall solve problems by using functions. A ramp up with Collections and a little bit of Object Oriented concepts in python, Functional Programming can be a great curve to harness python's usability and simplicity. At the end of this session, participants will be able to use the collections library in python, list comprehensions , deal with classes , objects and write anonymous functions , lambda expressions and resolve traditional snippets to reduce , map and filters for each of the use case", - "Last Updated": "09 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college folks", - "Section": "Core python and Standard library", - "Speaker Info": "Currently working as a Software Development Engineer at Olacabs. http://sameera.me https://www.linkedin.com/in/sameera-sy During my freetime I try the below. https://stackoverflow.com/users/4303216/sameera-sy https://www.hackerrank.com/sameerasy https://leetcode.com/sameerasy https://doselect.com/@sameera.sy", - "Speaker Links": "Below are some of my sample works. https://github.com/sam95 I have also conducted a webinar on JS for JavaScript Meetup Bangalore group. https://github.com/sam95/js-for-newbies-3 https://www.youtube.com/watch?v=JXg1GT6zDGQ", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sameeras", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/functional-programming-with-python~eEQle/", - "title": "Functional Programming with Python" - }, - { - "Content URLs": "Repository for the content", - "Description": "Orbital Mechanics/Astrodynamics is one of the most difficult things to understand and take care of! For this simple reason it is called \"Rocket Science\". poliastro is a python package intended to make Astrodynamics Open Source, and easy to understand and visualise. Through the talk, various modules of the poliastro package will be introduced. I will show how we can solve very complex Orbital Mechanics problem in 2 minutes that takes years for a scientist to solve manually! The talk will cover some parts of AstroPy, numba and a bunch of plotting libraries such as matplotlib and plotly", - "Last Updated": "09 May, 2018", - "Prerequisites": "Basic introduction to plotly , matplotlib . Knowledge of some core packages like numpy, etc is beneficial. Knowledge of some of the core Astronomy libraries such as AstroPy is also beneficial", - "Section": "Data science", - "Speaker Info": "I am Shreyas Bapat, half \"Electrical Engineer\" and a passionate developer. I study at Indian Institute of Technology Mandi and constantly contribute to open-source projects. I have contributed to some projects like plotly, dash, poliastro and astroquery. I like Astronomy and related fields a lot and hence keep searching for projects related to that. Also, I am into Deep Learning from quite a time and love tweaking Neural Networks to get amazing results. I am the co-ordinator and maintainer at STAC-IITMandi . I have mentored the Astronomy Code Camp organised by Nehru Planetarium and Astronomical Society of India", - "Speaker Links": "GitHub Profile : shreyasbapat My Website: shreyasb.com My Portfolio: Click here Find my contibutions in Poliastro at #4 : https://github.com/poliastro/poliastro/graphs/contributor", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shreyas Bapat (~shreyasbapat)", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/through-python-to-the-stars-orbital-mechanics-made-easy-and-open-source~dGK5d/", - "title": "Through Python to the Stars! - Orbital Mechanics Made Easy and Open-Source" - }, - { - "Content URLs": "The work in progress repository of all the associated code - fromscratchtoml . The official website of fromscratchtoml . The work in progress python notebooks . The author's github profile . Sample slides will be uploaded here ", - "Description": "The aim of this workshop is to give a hands on coding experience for writing machine learning / deep learning algorithms from scratch without using external frameworks alongside visualising the model and explaining its predictions using LIME. from-scratch-to-ml The primary goals of this library is - - This framework is intended to be and educational tool to learn deep Learning . - To bridge the gap between the theoretical and coding aspects of machine learning algorithms. - To write intuitive blogs as python notebooks so as to juxtapose theory and code . Explaining the fundamentals of the algorithm from the very basics. - To minimise the use of external dependencies except the fundamental ones like numpy and matplotlib .\n - To make sure that the developed algorithms are coherent with already existing machine learning frameworks. The library is still in a nascent stage but will take shape in a couple of months. Given that the commit frequency is huge. The audience is requested to be patient. LIME (Local Interpretable Model-Agnostic Explanations) - When you are writing a machine algorithm from scratch you want to make sure that your results are coherent and your model is learning the features it is meant to learn. LIME explains why your model behaved the way it did. I will quote excerpts from their blog below - Imagine we want to explain a classifier that predicts how likely it is for the image to contain a tree frog. We take the image on the left and divide it into interpretable components (contiguous superpixels). As illustrated below, we then generate a data set of perturbed instances by turning some of the interpretable components \u201coff\u201d (in this case, making them gray). For each perturbed instance, we get the probability that a tree frog is in the image according to the model. We then learn a simple (linear) model on this data set, which is locally weighted\u2014that is, we care more about making mistakes in perturbed instances that are more similar to the original image. In the end, we present the superpixels with highest positive weights as an explanation, graying out everything else. Even from a human's perspective these explanations do make sense. SOURC", - "Last Updated": "11 May, 2018", - "Prerequisites": "Just a bit of curious dabbling around with some basic machine learning", - "Section": "Data science", - "Speaker Info": "I have graduated from IIT ISM Dhanbad in 2017. Formerly I worked for a London based startup - ALIS labs , currently I am a research fellow at CVIT Lab IIIT Hyderabad alongside being the author of fromscratchtoml . I am also RaRe's incubator program member - the same organization which looks after the reputed topic modelling library gensim . I have given prep talks and mentored dev sprint on the same in Hyderabad Python Meetup group twice", - "Speaker Links": "Author's open source contribution can be seen at his github profile where it all started. Author's current blog where he discussed a 'bit' about the impact of AI. Author's old blog archive where he talked about random developer stuff. Author's another delusional repository which he has trouble explaining to people. Author sometimes also blogs for RaRe technologies . Author is omnipresent on the web by the handle markroxor ", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Mohit Rathore (~markroxor)", - "created_on": "11 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/from-scratch-to-ml-the-machine-learning-library-you-really-understand-and-explaining-its-predictions-with-lime~dJXya/", - "title": "From scratch to ML - The machine learning library you really understand and explaining its predictions with LIME." - }, - { - "Description": "So you started learning python, and you have been able to stitch few lines of code together and it worked, but you do not know why, then this is the talk for you. We will delve into elementary yet obscure concepts that are more often than not skipped by beginners eg why is if _ name_ == _ main_ required in python scripts. et el. In a 3 hour power packed interactive and fully-hands on workshop we shall be learning python from ground up using examples from the real world. Basics of python will be covered with less emphasis on the basics of programming itself. The topics to be covered during the workshop shall include but not be limited to: Hello World Variables Loops and conditionals String Lists, Dictionaries and Tuples. functions File handling classes modules and imports lambda, map and reduce decorators and generators raising and handling exceptions sample exercises for the attendees to work on based on the concepts covered in the first half of the workshop.", - "Last Updated": "12 May, 2018", - "Prerequisites": "The person should be familiar with a *nix based operating system, and the shell should not be alien to them. Attendee should be familiar with the concepts of a hierarchical file system and at least be able to find where their editor saved the file they just created. Knowledge / experience of at least one other programming language will give them an unfair edge", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat, along with his team at https://essentiasoftserv.com consults for python based projects which need help in maintaining, sanitizing and scaling to achieve their true potential.\nHe was one of the four who revamped the https://pydelhi.org community and volunteered for over a dozen https://pythonexpress.com workshops", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/yet-another-introduction-to-python~aKE8d/", - "title": "Yet another introduction to Python" - }, - { - "Content URLs": "https://github.com/bhagvank https://ingeniopythonis.wordpress.co", - "Description": "Video content management, AI, Blockchain and Virtual/Augmented reality technologies are changing the learning management platforms. Customer focused learning systems are emerging in enterprises. Enterprises are structuring their curriculum products to help solve the high value use cases of their customers. Members of the LMS system (python/ Django stack) can tailor their educational experience by choosing courses based on their learning styles. The courses are becoming more effective and helping members retain information. Platforms are differentiating by providing better, faster ways to find relevant content, whenever and wherever learners need it. Modern learning management platform is an end-to-end eLearning solution which has capabilities to create, distribute, edit and manage entire courses from start to finish independent of the content. Educational success and fulfilment are achieved through personalization and optimization of the learner\u2019s path through courses and gaining of competencies. This new class of learning technology vendors is making it possible to augment their systems with cloud-based applications which can be easily integrated with an enterprise-scale technology ecosystem. Enterprises are now tracking and analyzing learning experiences with incredible precision which can be used to improve ongoing program and business outcomes. Tracking and reporting comes in learner-oriented dashboards and reports built for the staff", - "Last Updated": "12 May, 2018", - "Prerequisites": "python, djang", - "Section": "Data science", - "Speaker Info": "Co-Founder of Architect Corner, Bhagvan has around 18 years experience in the industry, ranging from large scale enterprise development to helping incubate software product startups. He has completed a Masters in Industrial Systems Engineering at Georgia Institute of Technology, and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras", - "Speaker Links": "https://www.youtube.com/channel/UChu9J4M85CC7C8hMYp5cgRg/video", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhagvank", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-management-next-generation-platform~dPJ6a/", - "title": "Learning Management : Next Generation Platform" - }, - { - "Content URLs": "https://github.com/DL4Jets https://docs.google.com/presentation/d/1dDxxsMkfg8vwMi7QDkDaVwCQnxsaXVh9-6xrgrkLvnY/edit?usp=sharin", - "Description": "Ever wondered if you could build your own deep learning framework for hundreds of users? Well, we did build one and turns out it's not as hard as it sounds. With thousands of people working towards democratising artificial intelligence (AI) , we have seen an explosion in the availability of machine learning libraries that make it simpler to build and deploy models for a wide range of tasks. From finance to art, every field has been revolutionised by the introduction of AI. At the European Organisation for Nuclear Research (CERN) we work on understanding the fundamental particles that constitute the universe by performing various experiments in particle physics. Of late, we have experienced a stratospheric rise in deep learning applications to various problems - RNNs, CNNs, and GANs - that have yielded promising results. Like, this stuff is so cool. It works! We delve into the development of one such project as it evolves from a set of scripts into a full-blown framework for supervised learning in high-energy physics. In this talk we will detail the evolution on the DeepJet Framework. It will delieate the development isssues, and how it evolved from a set of scripts hastily patched together to a structured, cross-platform framework built on top of Tensorflow and Keras. The library is a WIP so we're shipping updates on a daily basis with the goal of improving usability with focus on documenting our existing code base. Initially envisaged to support the development of the namesake jet-tagger in the CMS Experiment at CERN, it has grown to encompass multiple purposes within the collaboration. It is aimed at outlining how to go from a set of scripts to building a library that is used by hundreds of scientists in the world's largest physics research collaboration. The presentation will describe the major features the environment sports: simple out-of-memory training with a multi-threaded approach to maximally exploit the hardware acceleration, simple and streamlined I/O to help bookkeeping of the developments, and finally Docker image distribution, to simplify the deployment of the whole ecosystem on multiple datacenters. The talk will also cover future development aimed at improving user experience. ", - "Last Updated": "12 May, 2018", - "Prerequisites": "Preferred: Experience working with virtual environments or Anaconda Knowledge of basic ideas within machine learning such as training, testing, and evaluation of models Basic knowledge of particle physics helpful but not require", - "Section": "Data science", - "Speaker Info": "Swapneel is a computer scientist working at Compact Muon Solenoid (CMS) Experiment at the European Organisation for Nuclear Research where physicists and engineers are probing the fundamental structure of the universe. They use the world's largest and most complex scientific instruments to study the basic constituents of matter \u2013 the fundamental particles. His work at CERN encompasses the creation of a framework that can facilitate the use of deep neural networks and provide a suite of functions to serve multiple use-cases such as jet classification, particle identification, and so on. He is an open-source enthusiast, writing and contributing to various projects in his free time", - "Speaker Links": "Personal Website Github Medium Blog Writing - Open Source for You Magazin", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Swapneel Mehta (~SwapneelM)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-deep-learning-framework-for-high-energy-physics~dN18b/", - "title": "Building a Deep Learning Framework for High-energy Physics" - }, - { - "Content URLs": "https://nim-lang.org http://slides.com/akapatkar/nim-for-python-programmer", - "Description": "Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org As Python programmers, we are used to a language which is expressive, intuitive and versatile. Python is widely lauded for its productivity, minimalistic syntax, standard library feature set and is an inspiration to newer languages like Go, Swift, and Julia. However, there are some areas like speed, distribution, and multicore processing where it lacks a good solution. Nim is a statically typed and high-performance garbage-collected language which builds upon Python\u2019s strengths and addresses someone its weakness in an innovative way. This talk introduces Nim to Python programmers by diving into powerful language design, syntax, data and control structures, static analysis, metaprogramming, portability/distribution and standard library features. At the end of this talk, you should have learned enough to a) get started with Nim on a project b) get familiar with Nim\u2019s growing ecosystem c) leverage/extend existing Python skills on a Nim project. Timeline breakdown: 1) Intro to Nim (10mins) 2) Language tour from Python\u2019s point of view (20 mins) 3) Things you can do with Nim + ecosystem (5 mins) 4) Q&A (5mins", - "Last Updated": "12 May, 2018", - "Section": "Others", - "Speaker Info": "I am a language enthusiast and a Python developer at Netflix. I\u2019ve been learning and using Nim for over a year now and I have benefited immensely from its learnings. There is a strong correlation between Nim and Python and I would like to explain that to the audience and show them a way to think problems using Nim\u2019s construct which I am sure will help them improve their Python skills. I am currently using Nim to write an interpreter for \u2018lox language\u2019. More details here https://github.com/cabhishek/nimlo", - "Speaker Links": "International Conference Talks: PyCon Ukraine 2018 https://2018.uapycon.org/#schedule PyCaribbean 2018 http://pycaribbean.com/schedule.html Python San Sebastian 2017 http://pyss17.pyss.org/", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Abhishek Kapatker (~abhishek69)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/nim-for-python-programmers~aO9Ed/", - "title": "Nim for Python Programmers" - }, - { - "Content URLs": "", - "Description": "A short and crisp interactive session for the first time attendees of PyCon India to help them navigate through the conference and make the most of the next 4 days. 2011 was my first PyCon and in hindsight was a major turning point in my professional life. The experiences I had, the people I met and the friends I made during the conference are still shaping the choices I make and the decisions I take even today. PS: This will be a heavily opinionated talk and the attendees will be requested to weigh the advice being shared and adapt the ones that suit them the most. The audience will be implored to introspect and answer the following and more for them Which talks to attend? How to decide which talks to attend. Can I walk out of a talk in the middle? Should I attend every talk? What is the hallway track? Should I talk to strangers at the conference? How to start talking to strangers? Can I volunteer now that the conference is already happening? The volunteers are awesome people will they accept my help? How can I help? Should I help the volunteers? What is the dev-sprint? How to make the most of the dev sprint? I just started learning python, will people make fun of me if I speak? i need a job, what should I do? I need to hire, what can I do?", - "Last Updated": "12 May, 2018", - "Prerequisites": "A ticket to the conference, willingness to learn, un-learn and re-learn", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has been a part of PyCon India since 2011 where he found enlightenment and confidence to take charge of his education and steered his career in a direction that feels like success at least to him. These days, along with his team at https://essentiasoftserv.com he consults for companies that need assistance maintaining, scaling, and sanitizing their python based codebase", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-make-the-most-of-pycon-india-2018~dLBva/", - "title": "How to make the most of PyCon India 2018" - }, - { - "Content URLs": "For workshop home here and here such as to get sample data, Jupyter notebooks, slides etc For workshop slides pls see her", - "Description": "Geospatial representation are so prevalent in day to day life, such as even in simple travel related conversation to maps, aerial/satellite images etc. In digital era, geospatial data is extensively produced and consumed in ever growing proportion. Python with its free and open source libraries are giving wide variety yet simple and effective set of tools to visualise and analyse geospatial data. The current workshop is directed for beginners of Python programming language, who have basic understanding on computing and data formats. The primary objective of the workshop is to introduce and give hands on training on selected list of FOSS libraries for geospatial analysis. The workshop as a do it yourself fashion tries to solve two real world problems in Geographical Information System (GIS) and its geospatial data sources. The workshop comprised of three components: Component 1 Python environment and work flow setup, an assisted task of setting up the Docker and Jupyter notebook setup. Setting up the Geographical Information System (GIS) environment with extended discussion. Setting up of GIS tools such as FOSS QGIS and Google earth. This component is comprised of four exercises. 1. Introduction to vector data, 2. Introduction to raster data, 3. binary and text file formats of geospatial data, 4. Introduction to tools of GIS, 5. Introduction to literal programming- Jupyter notebook Component 2 Find characteristics of road network(type of road network, length of the type) within a 1X1 km grid. The data source is Open Street Map (OSM) road network data on a city level (60X60km size). This operation is operationally simple such as measure a line feature but computationally intensive as the operation comprised of geometry within operation on dense road network seen in urban setup. Libraries such as Shapely, Fiona, Geopandas and rtree index will be used for the fast processing of this operation. This component comprised of three exercises 1. Find distance between two points 2. Find distance between two points constrained by another vector 3. Find distance between large number of points in for loop Component 3 Find cloud cover percentage over area of interest. The data source is Landsat satellite imagery. Searching cloud free Landsat images over an Area of Interest for a temporal extent of a year or more is manual and time consuming. Applying cloud cover detection algorithm could make this operation automatic. Libraries such as rasterio, Geopandas, Fiona, and libraries related to landsat algorithms will be used for this task. This component comprised of two exercises 1. Convert the imagery in geotiff into numpy arrays 2. Apply the algorithms to find the cloud cover Workshop Plan Introduction and setup- 30 minutes Component 1- 30 minutes Component 2- 45 minutes Component 3- 45 minutes", - "Last Updated": "12 May, 2018", - "Prerequisites": " Laptop 32bit/64 bit Workshop material is tested on 64 bit computer, it is said to be working in 32 bit, lets experiment! A copy of Docker container image from here , file from the link foss-pt-gsa_v3.tar.gz is 2.5 GB in size, will be using this container for DIY Local copy of Docker toolbox from here for windows 64 bit, for 32 bit Windows, follow this link , if any issue, don't worry, we have a session for setting up the docker! Local copy boot2docker.iso from here , we will be following old method of docker toolbox instead of docker native software for Windows.", - "Section": "Data science", - "Speaker Info": "I am a research associate at UrbanEmissions.info . My doctoral study was related to interoperable management of data from air pollution monitors and atmospheric models. I used free and open source libraries of Python for the study, especially on geospatial data compilation, analysis and visualization. Freedom and customization of free and open source languages such as of R and Python were immense. After Conda python package manager came into existence, the world of Python was so easy and I started to use Python for most of computing", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "nishadhka", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/free-and-open-source-libraries-of-python-for-geo-spatial-analysis-and-visualisationmaps-and-satellite-imageries~aQL5e/", - "title": "Free and Open Source libraries of Python for Geo spatial Analysis and Visualisation(Maps and Satellite imageries)" - }, - { - "Description": "Millions of visitors visit business websites every day and each one of them takes different set of steps in order to seek the right information/product. Yet most of them leave disappointed or dejected for some reason and very few get to the right page within the website. In this kind of situation, it becomes difficult to find out if the visitor actually got the information that he was looking for? Also, the individual journeys of these visitors can\u2019t be compared to each other since every visitor has done different set of activities. So, how can we know more about these journeys and compare these visitors to each other?\nSequence Embedding is a powerful way that offers us the flexibility to not only compare any two distinct visitors entire journey in terms of similarity but also to predict the probability of visitor\u2019s conversion. Sequence embeddings essentially helps us to move away from using traditional features to make predictions and considers not only the order of the activities of a user but also the average time spent on each of the unique pages to translate into more robust features and used in Supervised Machine Learning across multiple use cases (next possible action prediction, converted vs non-converted, product classification)\u00a0.Using traditional Machine learning models on the advanced features like sequence embeddings, we can achieve tremendous results in terms of prediction accuracy but the real benefit lies in visualizing all these user journeys and observing how distinct are these paths from the ideal ones. This session will unfold the process creating sequence embeddings for each user\u2019s journey in python and use them to build machine learning classification model to predict visitor conversion along with comparing all the user journeys in terms of similarity score", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic understanding of Machine Learning ,\nPython Basic", - "Section": "Data science", - "Speaker Info": "Co-Founder of DataScienceBridge and currently Sr. Data Scientist at SapientRazorfish core Data Science Team has around 8 years\u2019 experience in the industry, ranging from large scale IT enterprise business development to building complex Machine Learning models by applying state of the art techniques. He has completed his Master\u2019s in Business at Symbiosis International University and certified professional in Machine Learning from IIM-Calcutta.\nHis core expertise involves Machine Learning, Deep Learning, Recommendation Systems using python, spark and Tensorflow for various projects. He is president of Data Science meet up group at SapientRazorfish and conducts multiple webinars on Machine Learning. Along with that he is also a speaker and recently presented a talk at \u201cGreat Indian Developer Summit \u201c(GIDS 2018).\nIn his spare time, he likes to read, code and help aspiring Data Scientists", - "Speaker Links": "https://www.youtube.com/watch?v=Nbpz79v2y5", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pramod Singh (~pramodchahar)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sequence-embeddings-in-python-classification-user-journey-comparison~dRBwd/", - "title": "Sequence Embeddings in Python: Classification & User journey Comparison" - }, - { - "Content URLs": "https://github.com/devxp", - "Description": "My talk is related to my work on ZProc , a library for doing multiprocessing in python Its provides a high-level wrapper over zeroMQ, the distributed messaging library. I will provide a basic introduction to the ways we can natively implement concurrency/parallelism in our applications and how ZProc is a better way to do multi-tasking", - "Last Updated": "14 May, 2018", - "Prerequisites": " A good knowledge of basic python. Some knowledge about the python Process/Thread interface is appreciated If you ever had your hands on the zguide , I have a hunch you'll like this. ", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm 19 year old python programmer, picked up python when I was around 15. My adventures with multi-tasking applications started when I was 17, trying to build a concurrent youtube downloader. I am since, trying to find ways to make writing concurrent, multi-core applications simpler in python", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Dev Aggarwal (~devxpy)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/zproc-process-on-steroids~bWBoa/", - "title": "ZProc - Process on steroids" - }, - { - "Description": "A lot of budding programmers use print() function or logging module to display the state of the program. However, it soon becomes untenable to reason about the program in a barrage of print statements. At that time, a debugger is a must. Debuggers are a better and structured way to inspect a program. A practical and basic understanding of debuggers will help in locating bugs easily and save developer's time and unnecessary frustration. In this talk, we are going to learn the terminology associated with debugging and explore the most commonly used commands of pdb", - "Last Updated": "14 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college students or people who just started programming in Python", - "Section": "Core python and Standard library", - "Speaker Info": "I'm currently a Senior Web Developer and Curriculum Designer at Pesto Tech. I've programmed in Python and Flask since the last 3 years. Open source enthusiast, and frequent blogger", - "Speaker Links": "Medium - https://medium.com/@arfatsalman Twitter - https://twitter.com/salman_arfat GitHub - https://github.com/ArfatSalman LinkedIn - https://www.linkedin.com/in/arfatsalman", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Arfat Salman (~ArfatSalman)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-basics-and-debugging-python-scripts-with-pdb~eVZoe/", - "title": "Debugging basics and debugging python scripts with pdb" - }, - { - "Content URLs": "https://atad.xyz\n[ Will share the GitHub repo during the talk with sample web crawlers ", - "Description": "Introducing to Web Scraping. A complete walkthrough the below items: Challenges in scraping websites and parsing the data, Introducing Scrapy, a widely used framework to extract data Dos & Don'ts Usage of Proxies & IP Rotation Crawling hundreds of websites, running and scaling them to huge volumes", - "Last Updated": "14 May, 2018", - "Prerequisites": "Laptop with Ubuntu or a similar OS. \nPython and MySql latest versions Basic understanding of Python and MySql\nGood to have knowledge in writing Xpaths and usage of proxie", - "Section": "Data science", - "Speaker Info": "I am Raja Emmela, \nI Run Headrun Technologies, Bangalore - helping clients in Data Scraping and Web Applications We are in this space for the last seven years, extracting data and parsing them. My experience helps do share the challenges we faced with domestic and NA & APAC clients while scraping websites and the don'ts in particular", - "Speaker Links": " LinkedIn Twitter Blog", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "rajaemmela", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-intro-to-web-scraping-dos-donts-and-the-challenges-in-scaling-it-to-huge-volumes~eXVVb/", - "title": "An intro to Web Scraping, dos & don'ts and the challenges in Scaling it to huge volumes" - }, - { - "Content URLs": "I will soon share presentation, resources, and code soon on GitHub", - "Description": "Abstract Think of wireless internet, but has the wire somewhere. Serverless architecture still has the server behind :P. What serverless actually means that developer should focus on the code rather than thinking about the servers. As a technique, it removes most of the manel parts of an application, so you can actually spend your day coding. This means that you, developers, can quickly create apps that handle production-ready traffic. You do not have to actively manage scaling for your applications. You do not have to provision the server, or to pay for resources that are unused. The serverless movement started with the release of AWS Lambda, a Function-as-a-Service (FaaS) compute service. But serverless is much more than just FaaS Chatbots have been around for quite a long time. But why this sudden surge and interest in chatbots now? Well, there are various reasons. Unlike the earlier days, many AI and NLP capabilities are now available as consumable services. Also, serverless technologies make chatbots easier to build and scale. The question is, how is the backend served? Would you set up a dedicated server (or a cluster of servers)? That\u2019s costly, painful, and time-consuming! or You will deploy it to Heroku, which will eventually sleep (only happens in the free tier) if no one uses your chatbot. Imagine suddenly, traffic increased your chatbot is used by thousands of people at a time. When Heroku free tier is over, the application crashed or you exceeded memory limit. What would you do now? That\u2019s where serverless technology can help. Benefits of serverless No Administration - We can deploy our code without provisioning anything beforehand, or manage anything afterward. There is no concept of a fleet, an instance, or even an operating system. Scalability - One doesn't have to care about auto-scaling, No need to show alerts or write scripts to scale up and down. With serverless, we can handle quick bursts of traffic. Cost - Function-as-a-service (FaaS) compute and managed services charged based on actual usage rather than pre-provisioned capacity. This means one pay the amount we use, so if we use service for 10 sec then we pay for 10 sec. Faster Development - Now loop between having an idea and deploying to production is shortened because no one need to manage anything after deployment, smaller teams can ship more features. It's easier than ever to make your idea live. Easy Integration With Other Services Going serverless allows a seamless integration to various other cloud services from the same provider. For example, if you are using the AWS platform for chatbots, then you can use DynamoDB for the database, write programming logic as Lambda functions, and expose them through the API Gateway. Session key Takeaways The main question is how to write code which is serverless compliant. This is where this session will help you. This talk will help people to move a step ahead of the traditional way of writing code as some of you had already developed chatbot, I will share how can you can write the simple chatbot in python and can take leverage of serverless to deploy and publish. I will cover Serverless Framework principals AWS Lambda, Amazon Lex and API Gateway How to write a chatbot in python and create a Lambda function How to troubleshoot in a serverless world", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic knowledge of python and development in general", - "Section": "Others", - "Speaker Info": "Vaibhav Singh is an undergrad final year student of BML Munjal University, Gurugram. He had worked with AWS services as a solution architect intern in Amazon and he is also open source enthusiast and contributed to many open source organization like Fossasia, coala, etc. He is now Google Summer Of Code intern with FOSSASIA. Previously, He was the finalist winner in Codeheat competition. I write mostly in python ;). I had written various small scripts to make my life easier :", - "Speaker Links": "Website GitHub Twitter Facebook Linkedin Mai", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vaibhav Singh (~vaibhavsingh97)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-serverless-framework-build-a-chatbot~eZXgb/", - "title": "The Serverless Framework - Build a Chatbot" - }, - { - "Content URLs": "Sensor Fusion Introduction\nhttps://youtu.be/C7JQ7Rpwn2k Sklearn Quick Tutorial\nhttp://scikit-learn.org/stable/tutorial/basic/tutorial.htm", - "Description": "Abstract The primary purpose of this talk to describe how we are using python and Sklearn to model and analyse time series sensor data. In particular, I will walk through how we use Python to process data from an IoT enabled sensor attached to a cricket bat, build machine learning models on the data, and use open source tools to deploy our models in the sensor device as a smart IoT application. Description With the steep increase in the number of smart-things connected to the internet, the amount of data that is being generated by such devices is increasing exponentially. However, much of that data is not useful and therefore filtering unuseful data is an important task. How do we filter the important part and remove the noise from sensor data streams to generate actionable insights? To demonstrate the problem we are placing a sensor device on a cricket bat. The IoT device is a miniaturised, wireless MEMS inertial measurement unit (IMU). The IMU incorporates three-axis sensing of bat acceleration and angular velocity with a low-power Bluetooth to transmit this data to a mobile. First, we gather event-based data rather than storing the entire stream. This again poses the question: how do we define an event? What makes an event unique from the surrounding \u2018non-event\u2019 context? These are some of the questions that need to be answered in order to define an event. Watching a cricket batter stand and prepare to swing, the human brain continuously filters its visual perception and is able to detect and differentiate a swing from the pre- and post-swing activity. We need to be able to automate that same process. Some data instances can be tagged while other can\u2019t be. This helps in training and evaluating machine learning models later. Secondly, After we have extracted time series data based on the instances, we can start analysing these event-based sets of data to understand the language of sensor data. For this, we are using Jupyter Lab to interactively work with data. How does an accelerometer data depict the real world physical motion? This step helps us find the relation between the real world actions and the sensor data set. Well, the extraction process will be prone to noises. The data comes in CSV files, python seems the right choice for us to read and analyse the data. Pandas and offer data frames that come handy to rapidly form and validate hypothesis interactively in Jupyter notebooks. Any analysis is incomplete without visualisation, that's where Matplotlib helps us understand the data better. We quickly test the machine learning models by using Sklearn, which has most of the standard algorithms already implemented. This keynote will describe some of the analysis (along with python code) to show how we have taken several steps right from forming the hypothesis to implementing a solution in the device level layer. All of this demonstrates how Python and its rich set of libraries are helpful in forming solutions to some of the product related features. Thirdly, we need to automate the task of classifying a particular instance from the stream. For this to happen, we can either feed a machine learning model or create a rule-based algorithm which can classify the events into buckets. Now every step has its own set of challenges, firstly the application we are working on involves using motion sensors attached to the back of a cricket bat. There are network constraints in the field. If a sportsperson wants to know real-time analytics from the device, the segregation needs to happen offline. We have to deploy the models on the miniature sensor devices because sometimes the players don\u2019t even carry their mobile phones to the playing area. Therefore our objective is to enable the devices to remain independent in running machine learning algorithms by themselves", - "Last Updated": "14 May, 2018", - "Prerequisites": "Participants should have an understanding of python basics", - "Section": "Data science", - "Speaker Info": "Sanjiv Soni is a data scientist at Str8bat, Bangalore. He currently an international fellow at University of San Francisco for Deep Learning Programme. Sanjiv has experience with Software and product ecosystem. He has interests in building software devised solutions to problems solved by humans", - "Speaker Links": "https://twitter.com/sanjivsoni7 https://www.linkedin.com/in/sanjiv-soni", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "sanjiv soni (~sanjiv)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/swing-and-a-miss-deploying-machine-learning-models-for-iot-enabled-devices-using-python~bYXYa/", - "title": "Swing and a Miss: Deploying machine learning models for IoT enabled devices using Python" - }, - { - "Content URLs": " Coming soon...", - "Description": "Take it from someone who has introduced an exorbitantly high number of bugs in empty files for most of his life: debugging is hard indeed. But since the dawn of time, developers have been debugging code: there's no escaping that. Software testing, as the elders would tell you, is one of the greatest weapons in your arsenal against those bugs. It's easy to write tests. It helps you write more robust software. And it really helps you sleep at night: and your on-call ops team would love you! But testing is also deeply mystified, unfortunately. Beginners, and sometimes even seasoned developers, generally have a difficult time just to get started: so they eventually miss out on this easy way to attain peace of mind. This talks aims at removing all the mystery around software testing in Python, and give the attendees a head-start into the easiest way of writing tests for their code. As part of being a Python developer for the past 8 years and leading a team of developers building enterprise-grade software for the past 4 years, I've learnt immensely about the important role of software testing in building scalable, durable software; and also a better, pragmatic way of thinking about testing in Python. This talk aims at providing a distilled version of my learning to the audience: both beginners to Python, and seasoned Pythonistas. The talk would broadly cover these topics: A formal way of thinking about software testing / Why you should even bother about writing tests? Writing the simplest of tests in Python / Brief exploration of unittest and pytest Introduction to mocking in Python / In-depth exploration of mock and how to effectively use it for mocking any type of scenario in your code Writing tests for complex applications / working code examples from real life \u2014 This section would contain walkthrough of tests written in a few real-life applications and Python libraries, and a discussion on how to add test coverage for things that might not seem very straightforward to mock in a unit test. A few (opinionated) recommendations about testing Apart from providing to the audience an easy-to-grasp framework of thinking about software testing, this talk aims to teach by examples from real world. Complex and not so straightforward concepts would be explained with code samples and tests from production, so it's easy for the audience to truly grasp them. The talk also features anecdotes from my own experience in building software to give the audience better context", - "Last Updated": "15 May, 2018", - "Prerequisites": "This talk is intended for newcomers to Python (who might never have written a test yet), as well as experienced developers (who might not be writing tests effectively). There are no technical pre-requisites for this talk. The key takeaways would be patterns you can directly start using in writing tests for your own code", - "Section": "Developer tools and Automation", - "Speaker Info": "Sanket ( @sanketsaurav ) is co-founder and Chief of Geeks at DoSelect . He\u2019s 50% developer and 50% designer. He\u2019s been dabbling with computers since the age of 10, and had started his first venture at 18. He loves the Web and likes building cool stuff that matter. His languages of choice are Python, Go and JavaScript, and he\u2019s been building production apps using these for the past two years. He\u2019s also spoken at more than 50 events and hackathons across the country on open source technologies including Python, HTML5 and web applications in general. Sanket also contributes extensively to open-source, with contributions to projects like Django, Celery and Docker, and original Python modules like S3Tree and mimelib ", - "Speaker Links": "Social presence: GitHub Website DoSelect Past talks: Talk at PyCon India 2017 Talk at PyCon Pune 2017 Talk at PyCon India 2013 Django on Steroids -- Slides Lessons from Scale: Django", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sanket Saurav (~sanket)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-is-hard-testing-is-easy~e17qb/", - "title": "Debugging is hard, testing is easy!" - }, - { - "Content URLs": "https://games.renpy.org/category/rpg https://www.renpy.org", - "Description": "Ren'Py is one of the most versatile and easy-to-use frameworks, written in Python, for the development of Visual Novels and smaller Role-playing games. The talk will explore the details about creating your own development environment for development of visual novels, writing a script and developing GUI, porting your game to Android and iOS and how you can get help for issues in development process. The talk will also explore some of the games which have been developed in Ren'Py like Katawa Shoujo, Doki Doki Literature Club, Imre's Curse: The Prologue etc. The talk will be an interactive one and have a very light and humorous note", - "Last Updated": "15 May, 2018", - "Prerequisites": "No prerequisites required. An open mind and familiarity with Python is all what is needed to attend the talk", - "Section": "Others", - "Speaker Info": "I am currently involved with Lernr Project, a startup based in Ahmedabad and have been working with Python for 3+ years, certified as a\nSoftware Carpentry Instructor and one of the organizers of Django Girls Bangalore. Contributor to Biopython, Galaxy Project, bioconda and conda-forge communities. My interests are in the field of Bioinformatics, High-Performance Computing and am working under Prof. V.K. Jayaraman in the field of Proteomics", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sourav Singh (~sourav)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/make-your-own-visual-novel-in-renpy~b2JAb/", - "title": "Make your own Visual Novel in Ren'Py" - }, - { - "Description": " Understanding Neural Networking using NumPy Implementing CNN using Keras & understanding foundations Using Pretrained models. Transfer training for doing dog breed identification", - "Last Updated": "15 May, 2018", - "Prerequisites": " Python Basics NumPy Machine Learning Basics", - "Section": "Data science", - "Speaker Info": " 10 + Industry Experience. Machine Learning & Deep Learning Trainer/Consultant for more than 20 companies https://www.linkedin.com/in/awantik/ Co-Founder EdYoda & Zekelabs", - "Speaker Links": "https://www.linkedin.com/in/awantik", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Awantik Das (~awantik)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-using-python-from-scratch-image-classification~b4KJa/", - "title": "Deep Learning using Python from Scratch - Image Classification" - }, - { - "Description": "You only look once (YOLO) is a state-of-the-art, real-time object detection algorithm. The model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image. It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. This makes it extremely very fast. This talk teaches you to develop your own real-time object detection python application to detect and classify objects in images as well as videos in real-time, which you can use in your next self driving car", - "Last Updated": "16 May, 2018", - "Prerequisites": " Knowledge of basic Python and its syntax Idea/Overview of deep learning as a technology", - "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune. I'm currently working in HSBC Technology India, as a software developer. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": " LinkedIn Twitter Recent talk on WebVR", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-object-detection-coz-yolo~b6VNb/", - "title": "Real-time object detection coz YOLO!" - }, - { - "Content URLs": "https://github.com/sdonapar/data_analysis_pytho", - "Description": "Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data. Data Visualisation helps to get hidden insights quickly . Data Visualisation is key for summarising and communicating your insights. This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis and visualisation Following will be covered as part of this session How does data analysis fit in the life cycle of data science project Dealing with numpy arrays - quick overview Reading data using various formats and sources Data scrubbing/cleansing - dealing with missing values, data transformation Introduction to data visualisation and quick overview of libraries available Using visualisation to understand and communicate results Analysing one of the open source data set By the end of the session Audience will have very good understanding of how to apply numpy, pandas to analyse, visualise understand and communicate the results Scrub/Cleanse the data and prepare data set required for machine learning", - "Last Updated": "16 May, 2018", - "Prerequisites": "Hands on exposure with basic python programming language Software requirements: Please install Anaconda ( https://www.anaconda.com/download/) with Python 3.6 Download the git hub repo - https://github.com/sdonapar/data_analysis_pythonwe would be using jupyter notebooks for this worksho", - "Section": "Data science", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company. I have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar linkedin profile - https://www.linkedin.com/in/sasidonaparthi twitter handle - @sdonapa", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-visualisation-using-python~e50Xd/", - "title": "Data Analysis & Visualisation using Python" - }, - { - "Description": "The human voice is becoming an increasingly important way of interacting with devices, but current state of the art solutions are proprietary and strive for user lock-in. Mozilla\u2019s DeepSpeech and Common Voice projects are there to change this. In contrast to classic STT approaches, DeepSpeech features a modern end-to-end deep learning solution. Based on Baidu's Deep Speech research paper, it trains a model by machine learning techniques. This model directly translates raw audio data into text - without any domain specific code in between. To train systems like DeepSpeech, an extremely large amount of voice data is required. Most of the data used by large companies isn\u2019t available to the majority of people. That's why Mozilla launched Common Voice, a project to help make voice recognition open to everyone", - "Last Updated": "16 May, 2018", - "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune, and a Mozilla TechSpeaker. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": "Mozilla Research machine learning home page: https://research.mozilla.org/machine-learning/ Speaker's LinedIn: https://www.linkedin.com/in/shaguftagurmukhdas/ Speaker's twitter: https://twitter.com/shaguftamethwa", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mozillas-deepspeech-and-common-voice-projects~e7JBd/", - "title": "Mozilla's DeepSpeech and Common Voice projects" - }, - { - "Content URLs": "OpenFaas Docs: https://docs.openfaas.com/ OpenFaas Website: https://www.openfaas.com", - "Description": "OpenFaaS makes Serverless Functions simple with any programming language through the use of Docker containers. The project can be hosted on any cloud, or on your own hardware - even your laptop. Learn how to build Serverless functions with OpenFaaS and Python in this self-paced workshop lead by the community behind the project. Start by deploying OpenFaaS to your laptops with Docker for Mac or Windows and then learn how to build, deploy and invoke serverless functions in Python. Topics will include: Managing dependencies with pip, dealing with API tokens through secure secrets, monitoring functions with Prometheus, invoking functions asynchronously and chaining functions together to create applications. We'll finish by building a custom action for Google Home/Google Assistant for managing slack notifications using Google's DialogFlow and Slack API. The workshop will have the following labs: Prepare for OpenFaas Test things out Introduction to functions Go Deeper with functions HTML for your functions Asynchronous functions Advanced feature - Timeouts Advanced feature - Auto Scaling Advanced feature - Secrets Create a Slack bot using DialogFlow, Slack API and OpenFaaS", - "Last Updated": "16 May, 2018", - "Prerequisites": " Basic knowledge of Docker Functions will be written in Python, so prior programming or scripting experience is preferred. Requirements: We can use - https://labs.play-with-docker.com/ or any VM / box with the latest docker installed", - "Section": "Web development", - "Speaker Info": "Vivek Singh: Currently working as Software Engineer - II at Akamai Technologies. Been an active contributor to OpenFaaS project. Co-organizer and Speaker at OpenFaaS Bangalore meetup group . Loves to code in Python and Golang. Contributes to Open Source projects in free time. Vivek Sridhar: Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "Vivek Singh: Contributions: https://github.com/viveksyngh LinkedIn Profile: https://www.linkedin.com/in/viveksyngh/ Twitter: https://twitter.com/viveksyngh Website: https://www.viveksyngh.info Blog: https://www.viveksyngh.info/blog/ Vivek Sridhar: https://www.linkedin.com/in/vivsridh https://twitter.com/vivek_sridhar https://github.com/vivsridh4 https://hasgeek.tv/rootconf/2018-day-2/1509-distributed-tracing-with-jaeger-at-scale https://hasgeek.tv/rootconf/cloud-sever-management-delhi/1435-auto-remediation-at-scale-using-watchers-vivek-sridha", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Vivek Kumar Singh (~viveksyngh)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-serverless-with-openfaas-and-python~e9Xzd/", - "title": "Hands-On Serverless with OpenFaaS and Python" - }, - { - "Description": "DevOps is gaining momentum and we at Microsoft want our users to have great CI/CD story for any language targeting any platform. In this session, we will be talking about how easy is to get started on Cloud and DevOps for Python developer in this new generation of Microsoft We're going to start from scratch and before we're done we will use Visual Studio Team Services (VSTS) to setup Continuous Delivery for Python Applications on Cloud and demonstrate the DevOps strategy in action. The solution grows up to the most demanding needs of a modern software developers powered by VSTS. Whether you are starting new, bringing your own tool chain or inter-operating with existing tools and assets, you can accelerate your delivery of value with Azure and VSTS", - "Last Updated": "16 May, 2018", - "Prerequisites": "N", - "Section": "Developer tools and Automation", - "Speaker Info": "Alok Agrawal is Product Manager for Microsoft Visual Studio Team Services where he and his team are building next generation cloud based developer tools. He has been with Microsoft for over 7 years. Previously he has worked with Windows Application Compatibility and Azure Application team. Alok has Bachelor's degree in Computer Science and completed his business management from IIM Calcutta", - "Speaker Links": "http://www.imalokagrawal.com https://twitter.com/imalokagrawal https://github.com/imalokagrawa", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Alok Agrawal (~imalokagrawal)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-plumber-building-deployment-pipeline-in-minutes~e03Nd/", - "title": "Becoming a Plumber: Building deployment pipeline in minutes" - }, - { - "Description": "Sometimes it can be a laborious task for developers to build android apps using Java. Though Java supports Android apps in a powerful way but it also increases the code complexity for a high end app. Now, if you are a python enthusiast and also want to develop Android apps then Kivy comes to your rescue. Kivy is an open source python library for rapid development of cross platform apps. Using the Kv design language and the Kivy framework for Python, you can build amazing interactive multi-touch apps in just a matter of minutes. Kivy framework solves the complexity problem any android developer face while writing complex codes. It also serves the advantage of being cross platform which saves a great amount of time for any app developer. If you love Python, you will also love Kivy", - "Last Updated": "18 May, 2018", - "Prerequisites": "Python Basic Knowledge of Androi", - "Section": "Web development", - "Speaker Info": "The speaker goes by the name amanraj209 all over the web. I've been interested in learning new technologies since high school and I've been developing apps using Python, Javascript, Java, Go since the last 3 years. I've also done some small projects in Machine Learning. Being a developer gives me a great sense of feel to build apps for the users and contribute to the community. It has always been my passion to dive into the technology and contribute to the community something useful", - "Speaker Links": "Github: https://github.com/amanraj209 LinkedIn: https://www.linkedin.com/in/amanraj209 Facebook: https://www.facebook.com/amanraj20", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aman Raj (~amanraj209)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/developing-android-apps-using-kivy~el61b/", - "title": "Developing Android apps using Kivy" - }, - { - "Content URLs": " http://haridas.in https://github.com/haridas", - "Description": "Data-science mainly involves understanding your data and identify suitable models based on the data. Mastering the standard tools like pandas and seaborn will be key to gain insights about ML problems. This tutorial coverers, Basics of pandas and seaborn Different plotting patterns using seaborn for your data. Plotting Single and bivariate distributions, categorical plots with distribution. Understand two variable behaviour using regression plots. One usecase:- How I decided to buy a petrol car instead of diesel car by analysing my fuel spending.", - "Last Updated": "17 May, 2018", - "Prerequisites": "Lapatop with following packages installed. pip install seaborn pand", - "Section": "Data science", - "Speaker Info": "Haridas is a Principal Engineer in Pramati Technologies, part of Labs team. He has 8+ years of experience in multiple domains like, Web development, SOA, ML, Devops. He has been working extensively in different ML use-cases and applying them in real scenarios", - "Speaker Links": " http://haridas.in Twitter @haridas_n", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "haridas n (~haridas)", - "created_on": "17 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/find-patterns-in-your-data-using-seaborn-and-pandas~ejJ4e/", - "title": "Find patterns in your data using Seaborn and Pandas" - }, - { - "Content URLs": "Shall be updated soon", - "Description": "You have got this super awesome REST API served through Django/DRF based project and suddenly these requirements come in: We need to have a local support for Chinese language! In case, you've not written your application with localization and internationalization in mind, then \"Boy! You're in danger! You should better start praying to almighty to give you strength and endurance to support yet another language in your app\". In this talk, we'll see how do we support localization and serve our app in different languages, based on what language the client wants to communicate in. As a backend, we should be language agnostic and allow all clients to communicate with us in one of the languages we support. We'll see how to support translation for static data (using makemessages / compilemessages) and dynamic data, using various third-party services such as django-translations and transifex. Here, static data is translations for all the fields, error messages etc. that the app already has and dynamic data is the custom data input by the user in the app. This would enable you to have your admin panel, as well as RESTful APIs, served in different languages", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic knowledge of Python and Django", - "Section": "Web development", - "Speaker Info": "Why do you want this person to speak? Sanyam is a self-taught programmer with a \"can-do\" attitude who developed his interest in Computer Science and Software Development over the years. He mostly goes by CuriousLearner all over the web and you might run into him at various Python Conferences and local meetups. In his free time he contributes to FOSS. Some of his noticeable contributions are in Gecko Engine from Mozilla and CPython. You can read about his latest hacking CPython and other projects at http://www.SanyamKhurana.com/blog & http://medium.com/@CuriousLearner Highlights : Goes by CuriousLearner all over the web. Bug Triager and contributor to CPython (bugs.python.org) GSoC 2018 Mentor for Debian RGSoC 2016 Mentor Mozilla Reps Mentor and contributor to Mozilla's GeckoEngine, Add-ons ecosystem, and other few projects. Core-organizer for PyCon India 2016 & PyCon India 2017 Volunteer for PyCon India 2015.", - "Speaker Links": "Blog: http://www.SanyamKhurana.com/blog Website: http://www.SanyamKhurana.com Github: https://github.com/CuriousLearne", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sanyam Khurana (~CuriousLearner)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-multilingual-superhero-in-django~bkMve/", - "title": "Becoming a Multilingual SuperHero in Django" - }, - { - "Content URLs": "Coming up soon (related to this workshop", - "Description": "Convolution Networks - Framework = Vision in vanilla python. This workshop aims at providing the attendees an experience of implementing convolution neural from scratch without any big framework working in the backend supplementing the need for computation. This would give the attendees an overall understanding of what are Convolution Neural Networks and why do they work so exceedingly well! One does not simply code in vanilla python. What can you expect from this workshop! You'll understand what are convolution neural networks Why they work so well on image data? All the different implementation of Convolution network and how they improve the vanilla network What are the best ways to implement convolution network on a given data What this workshop is not! Just another workshop telling you to use frameworks Maths will not be looked over. (It's important) This workshop is not any other university lecture where you'll not understand anything. I find this image to be so apt given all the abstraction provided by frameworks", - "Last Updated": "18 May, 2018", - "Prerequisites": " Command over Python Familiarity with Numpy and basic math packages Intermediate Mathematics Familiarity with algorithms common in machine learning", - "Section": "Data science", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a deep learning enthusiast who loves mathematics and astronomy. I've been exploring machine learning/deep learning for about 2 years now and fiddling with the basic mathematics and scratch implementations always excite me. I'm currently mentor of deep learning in a Delhi based startup Greatech Soft Solutions and interning at Startup labs and a Google Summer of Code '18 student under the organization OpenAstronomy", - "Speaker Links": " http://prsr.me https://www.linkedin.com/in/prakharcode https://github.com/prakharcode", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/convolution-neural-networks-without-any-frameworks~bmX3a/", - "title": "Convolution Neural Networks without any frameworks" - }, - { - "Content URLs": " https://docs.julialang.org/en/release-0.4/ https://julialang.org/ Ppt (soon)", - "Description": "Julia Programming Language The Julia programming language is proving to be a new paradigm shift in the data science community due to it's easy to pick up syntax like python but and execution speed equivalent to C , this is possible due to flexible types and JIT compiler. The speed and user-friendliness are only some of its good parts. This talk delves deeper into understanding, how can Julia be the next language on your learning list. Outcomes of the talk What is Julia? How can I get it into my daily workflow What Julia offers that Python does not Understanding benefits of shifting to Julia How can a python-ista shift to Julia", - "Last Updated": "18 May, 2018", - "Prerequisites": " Laptop with Julia up and running", - "Section": "Others", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a recently born Julia-n, I do a lot of code in Julia and move back and forth from Julia to Python to C. I'm a deep learning practitioner and loves Astronomy. I recently got selected into Google Summer of Code under OpenAstronomy org and my project's fundamental language is Julia. I'm a computer science by day and dancer by night. Currently, I'm fiddling with Julia and it's awesomeness and I'll offer you nothing less than awesome", - "Speaker Links": " http://prsr.me https://linkedin.com/in/prakharcode https://github.com/prakharcode", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/julia-an-upgrade-to-python-programming-language~enJpe/", - "title": "Julia. An upgrade to Python Programming Language" - }, - { - "Content URLs": ">>> import thi", - "Description": "Tim Peters preached and we memorized that Explicit is better than implicit, but how many understood the deeper meaning enough to imbibe the essence of the zen? In this 20 min talk, we shall go through the zen and look at live examples where the golden words make a programmer's life easy", - "Last Updated": "19 May, 2018", - "Prerequisites": "Familiarity with the syntax of Python", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has spent countless hours wading through utterly un-pythonic, non-modular codebases that contain > 8000 lines in one file and >500 in one function, with nested try-except statements and has almost mastered the skill of keeping his calm and understanding even that", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-python-with-real-life-examples~epVyb/", - "title": "The Zen Of Python: with real life examples" - }, - { - "Content URLs": "This talk is going to be based on a series of blog posts I have written about the same topic - Python Project Workflows - Part 1 Python Project Workflows - Part 2 (Pipenv) Python Project Workflows - Part 3 (pylint)", - "Description": " Have conflicting dependencies (unpleasantly) surprised you? (Darn: It worked on my laptop!) Do deterministic builds matter? What about those run-time errors, which were a typo while accessing an attribute of a class? Has the codebase already started smelling a bit? Unit tests and what about Dockerization? Typically, when your Python project grows beyond a few modules and your team size is more than a couple of developers, having the right tools built into your project development workflow saves one from a lot of surprises (and perhaps late night calls). In this talk, we start with challenges typically seen in Python Projects and look at ways of overcoming them, so that the velocity of code deployment increases. Specifically we are going to be looking at tools that are out there that allow you to - Properly track dependencies ( pip , virtualenv and the new Pipenv ) Have a separate Dev and Production environment - so that dependencies in Dev environment don't spill into Production environment. Ensure that the builds are deterministic (across developer/build machines and time.) Enforce certain coding guidelines and capture the potential 'run-time' errors right during the development ( pylint ) and Eventually Dockerize your application.", - "Last Updated": "19 May, 2018", - "Prerequisites": "It's an intermediate level talk where you have already done some Python development and are at a point where you want to package, distribute or deploy your pet Project. If you are a beginner in Python, but have been involved in build/release of packages in any other languages, likely this talk is for you. If you do an equivalent of sudo pip install or sudo apt-get install when you want to download and use package foo , chances are you will benefit from this talk quite a bit", - "Section": "Developer tools and Automation", - "Speaker Info": "Running a Consulting Company 'hyphenOs Software Labs' in Pune, India. Python/Go programmer - Mostly for things that pay the bills and ideas that I want to try out. Datacenter Networking Enthusiast (hacking a yet another Container Networking technology, borrowing ideas from different Projects) Eternally grateful to whoever wrote tcpdump and the new Wireshark . Number of problems solved using these tools could run into triple digits. Hates trailing white spaces in a file.", - "Speaker Links": " Stack Overflow Github LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Abhijit Gadgil (~gabhijit)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-project-workflows-continuous-deployment-friendly~bq8ya/", - "title": "Python Project Workflows - Continuous Deployment Friendly" - }, - { - "Content URLs": " https://pytorch.org/docs/stable/index.html Slides (https://slides.com/rahulbaboota/deck)", - "Description": "Talk Abstract This talk aims to introduce Facebook's Deep Learning library - PyTorch. PyTorch is increasing becoming popular due to it's powerful features and shallow learning curve, making it accessible and easy to use to a larger community. This talk discusses about the 'Autograd' package, which is central to all neural networks in PyTorch. It also entails details about the different features and functionalities of PyTorch as well as equip the audience on how to create simple and complex Neural Networks in PyTorch. PyTorch helps to create dynamic computation graphs that allow you to change how the network behaves on the fly unlike static computation graphs. It offers modularity which enhances the ability to debug or see within the network. Outline of the Talk The talk will be broadly divided into 3 broad parts. Part 1 will be an Introduction to PyTorch. This part will focus on the use and need for PyTorch as a deep learning framework. This will be followed by instructions on how to setup PyTorch and a look at the basic building blocks behind the framework. Part 2 will dive more into the features of PyTorch, mainly it's AutoGrad package which lies at the heart of all Neural Networks created in PyTorch and PyTorch's ability to create dynamic computational graphs as opposed to the static computational graphs offered by some of it's counterparts (such as TensorFlow and Caffe). Part 3 will be a more 'hands on' part where the talk will focus on how to create and build simple as well as complex neural networks (such as Convolutional Neural Networks) with the framework", - "Last Updated": "19 May, 2018", - "Prerequisites": " A basic understanding of how Neural Networks work would be beneficial. Some knowledge about Numpy.", - "Section": "Data science", - "Speaker Info": "I am Rahul Baboota, a 3rd Year Undergraduate in India studying Computer Science and Engineering. I have an avid interest in the domain of Data Science, Machine Learning and Deep Learning. I have worked at various Data Science and Machine Learning based startups and labs. In my freshmen year, I worked at a data journalism startup to create and analyze smart data stories. I was also a part of a project funded by the Government of India for the development of a social media based analytics tool for the analysis of healthcare and nutrition in India. I am currently working at the Center for Artificial Intelligence at IIITD in the Autonomous Vehicle Lab 'Swarath'", - "Speaker Links": " https://www.linkedin.com/in/rahulbaboota/ https://github.com/RahulBaboota", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "rahul baboota (~rahul93)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/throwing-light-on-pytorch~er7La/", - "title": "Throwing Light on PyTorch" - }, - { - "Content URLs": "Slides: https://speakerdeck.com/satwikkansal/do-you-really-think-you-know-strings-in-python Also relevant: https://github.com/pydelhi/talks/issues/77 Most of the snippets and concepts to be discussed are taken from various resources I came across during my 6 months long research about Python. I have collected such snippets in a project called \"What the f*ck Python!\". Here's the source: https://github.com/satwikkansal/wtfpytho", - "Description": "Do you know that, 'a'[0][0][0][0][0] is a semantically valid statement in Python. print(r\"\\ some string\") is a valid statement, but print(r\"\\ some string \\\") raises a SyntaxError . print('wtfpython''') is valid but print(\"wtfpython\"\"\") raises SyntaxError . Do you know why, >>> a = \"some_string\"\n>>> id(a)\n140420665652016\n>>> id(\"some\" + \"_\" + \"string\")\n140420665652016 the id of both the objects in above snippet is same? And do you know why, >>> timeit.timeit(\"s1 = s1 + s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.25748300552368164\n# using \"+=\", three strings:\n>>> timeit.timeit(\"s1 += s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.012188911437988281 s1 = s1 + s2 + s3 is much slower than s1 += s2 + s3 . And finally, >>> 'a' * 20 is 'aaaaaaaaaaaaaaaaaaaa'\nTrue\n>>> 'a' * 21 is 'aaaaaaaaaaaaaaaaaaaaa'\nFalse\n\n# one last attack!\n>>> a = \"wtf\"\n>>> b = \"wtf\"\n>>> a is b\nTrue\n\n>>> a = \"wtf!\"\n>>> b = \"wtf!\"\n>>> a is b\nFalse\n\n>>> a, b = \"wtf!\", \"wtf!\"\n>>> a is b\nTrue Do you know the reason behind all the above-discussed facts and snippets? Some of them are really puzzling, right? I felt the same when I first came across all these intricacies. But don't worry, such behaviors, are mostly the consequences of strings being [immutable] [sequences] in Python. In this talk we'll be going through the concepts behind such snippets in detail, so that next time when you see such examples, the answer seems natural to you. Finally, we'll try to answer some interesting questions like, How does string concatenation work? What's the best way of building large strings in Python? (It may actually depend on your use-case) What happens when you multiply a string by a boolean? How strings in Python differ from strings in other languages like JavaScript, C++? and many more", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic familiarity with programming. Prior experience with Python would make the talk more interesting for the attendee", - "Section": "Core python and Standard library", - "Speaker Info": "I'm a Software Developer experienced with Decentralized Applications and Data Science. In my leisure time, I love doing pointless things with programming. Currently on a quest to learn as much as I could about Computer Science. And lastly, I prefer all things Python! (A humble brag ", - "Speaker Links": "Website | Github | Archives Past Speaking Experience PyCon India 2017 (Speaker for a DevSprint ) EuroPython 2017 ( Invited as a Speaker for a workshop , unable to attend though) IWD-Delhi 2018 ( Speaker ) PyDelhi biweekly meetup (Gave a small talk ) OSS DTU (Instructor and moderator)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Satwik Kansal (~satwik)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/do-you-really-think-you-know-strings-in-python~boJLa/", - "title": "Do you really think you know strings in Python?" - }, - { - "Content URLs": "(Slides to be uploaded soon", - "Description": "In computer vision, object detection is scanning and searching for an object in an image or a video (which is just sequence of images). Whereas, object tracking is like you are spying on someone and following it. Done in motion images like in animated gifs or videos, we want to track how an object is moving, where is it going, or its speed. Although it has been studied for dozens of years, object detection and tracking remains an open research problem . The difficulty level of this problem highly depends on how you define the object to be detected and tracked. If only a few visual features, such as a specific color, are used as representation of an object, it is fairly easy to identify all pixels with same color as the object. On the other extremity, the face of a specific person, which full of perceptual details and interfering information such as different poses and illumination, is very hard to be accurately detected, recognized and tracked. Thus, I believe it is important to address such challenges via a comparative study of object tracking and object detection in python. Here, I aim to present my own experience in tackling the problems while I tested different algorithms for the same", - "Last Updated": "19 May, 2018", - "Prerequisites": "Basic understanding of pytho", - "Section": "Data science", - "Speaker Info": "Anand Zutshi is currently pursuing his undergraduate B.E. degree from Netaji Subhas Institute Of Technology, Delhi. He has experience in developing and testing basic as well as advanced algorithms in C, C++. He has experience in developing a Learning Management System which uses dynamically trained neural network for scoring its users, and a LDA based tagging in its queries. He has in depth knowledge of Natural Language Processing, mainly with emphasis on word sense disambiguation and language models. His recent work of interest primarily focusses on object detection and object tracking in Python and sound classification and recognition. Currently, he is working on testing a biometric database management system along with predicting self and non-self processes in Operating system using Neural Networks", - "Speaker Links": "https://github.com/zutshianan", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "anand zutshi (~anand09)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-tracking-vs-object-detection-a-comparative-analysis~avJna/", - "title": "Object tracking vs Object detection- a comparative analysis" - }, - { - "Content URLs": " https://github.com/rahulkumaran/Telegram-Syntaxdb-bot There will be some slides that I'll prepare too but most of it is going to be an explanation from the GitHub repo and my talk https://github.com/python-telegram-bot/python-telegram-bot https://syntaxdb.com https://syntaxdb.com/api/v1 https://core.telegram.org/api", - "Description": "In this particular topic, I'll basically be telling people about how easy it is to create a Telegram Bot. The reason I'm interested in taking this up is because there are people who develop beautiful things and might want to let people to use it even on a mobile interface. The problem is not everyone's good with app development. So in such cases, deploying the beautiful things in the form of a bot would be a great idea. Bots can be of 2 types : Conversational Command based I'll be taking up the command based bot to help people get a feeling of this topic. Also, through the example I'll be giving, I'll try to make people understand as to what APIs are and how to use existing one. Later I'll show them how to create your own Python APIs because APIs make lives easier for programmers and it's always a good practise to know how to create an API as you never know when someone else might need it. CONTENTS AND ORDER OF THE TALK I'll be starting off with an introduction about myself and then I'll move on to what are bots. I'll then be explaining about why we could probably use these bots on Telegram, Discord, Slack and so on. Thereafter I'll be talking about the Telegram API for Python to help you interact with the bot and telling you how to use it. Before this, I'll show them how to prepare a bot on Telegram and get the Token. After this, I'll be talking about the importance of an API and utilizing existing ones as it makes your job much simpler. Slowly, I'll shift my focus on to how to build an API. I'll be explaining this using an example. Then using the Telegram Bot API and the API we build for Syntaxdb.com, we'll be creating a Telegram bot. Lastly, I'll summarise and entire talk and will take up a couple of questions. The entire talk will be based on a GitHub repository. The code links will be given to everyone for future reference", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Usage of libraries in Python", - "Section": "Others", - "Speaker Info": "The speaker, in this case is me, Rahul Arulkumaran . I'm an engineering undergrad currently going into my 3rd year. I'm also the Founder of the startup Free Flow . We still haven't registered it yet though. I started learning how to code when I came into engineering and Python was the first language I learnt. I never really developed anything until last year. It was after creating my first application that I got the interest to develop more using Python. From then to now, I've learnt a lot. I might not be an expert but yes, for my age, I think I'm better than most others. I'm also the President of the Computer Science Club, Enigma in my college Mahindra Ecole Centrale . I'm a Python developer and an open source enthusiast . I also am a Contributing and Managing member of PSF . I work on a lot of open source projects I love learning anything and everything related to coding. I'm also a Machine Learning and Data Science enthusiast ", - "Speaker Links": " https://rahulkumaran.github.io https://github.com/rahulkumaran https://www.linkedin.com/in/rahul-arulkumaran-101a63127", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-and-working-with-apis-to-develop-a-telegram-bot~dwgXd/", - "title": "Creating and working with APIs to develop a Telegram Bot" - }, - { - "Content URLs": "I will post presentation and Relevant codes soon on github. For reference please find the code here :\nhttp://magneplane.readthedocs.io/en/latest/index.htm", - "Description": "Content of My talk will have : Hyperloop : An Introduction How Python plays an Important role? Python Applications in the Project: Project Management, \nScripting the repeating processes, \nPython - ML in CFD, \nRaspberry Pi in Communications.", - "Last Updated": "20 May, 2018", - "Prerequisites": "An intermediate level knowledge of Python Knowledge of a Python and basic Math", - "Section": "Others", - "Speaker Info": "Suyash Singh is post graduate Student of Indian Institute of Technology, Madras Chennai. He is Head of Team Avishkar Hyperloop More Details about Avishkar Hyperloop : http://avishkarhyperloop.com/ He carries 4 years of work experience in Big Data and Data Science. Later his interest in fifth mode of transportation took him to IIT Madras. He has been pure pythonist. He has been a adviser to two small scale startups based out of Indore which deals with data science. He has a vision of transforming Transportation making it more efficient. He thinks Python will be an important tool to make it possible", - "Speaker Links": "LinkedIn Profile: https://linkedin.com/in/suyashao", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Suyash Singh (~suyash_singh)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hyperloop-how-python-helps-building-fifth-mode-of-transportation~el6jb/", - "title": "Hyperloop : How Python helps Building fifth mode of Transportation?" - }, - { - "Content URLs": " Slides on Introduction to NLP : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction%20to%20NLP%20%26%20Spacy.pdf Jupyter Notebook : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction.ipynb Note : The above slides are not complete and are suited for a quick introduction to NLP in 20 mins I will be introducing the following Libraries (and use them to create chatbots) NLTK : https://www.nltk.org/ SpaCy : https://spacy.io/ I will be developing a bot on the following Chat Platforms with emphasis on Messenger: Messenger : https://developers.facebook.com/docs/messenger-platform/ Slack : https://api.slack.com/ Telegram : https://core.telegram.org/bots", - "Description": "Introduction to NLP Natural Language Processing is a prominent field in Artificial Intelligence that deals with parsing and understand Natural language, (an ordinary language such as English is any language that has evolved naturally in humans through use). NLP lies at the core of Google Duplex and other smart assistants that respond to questions in English and natural languages. I will be explaining the following : Corpus and Datasets Processing and tokenizing Text Tagging, Stemming and Lemmatizing Words WordNet Introduction to libraries NLTK Spacy Sentiment Analysis Word Embedding using BOW and word2vec Developing Chatbots With rising need for customer support, Chatbot are one of the most common applications of NLP. These are applications that are trained conversation with a human by answering some preset list of questions. I will be developing a chatbot on three platforms : Messenger (Facebook) Slack Telegram These will be deployed locally using Django with ngrok for tunneling. Additionally, due to the immense popularity of Messenger, I'll be also explaining the different message templates and other features that Messenger has. If you'd like to see me cover another platform such as Discord, Skype, Google Assistant or Alexa, feel free to drop a commen", - "Last Updated": "20 May, 2018", - "Prerequisites": "Basic knowledge of Python, English Grammar and HTTP Requests", - "Section": "Others", - "Speaker Info": "About me Hello world. I\u2019m Vishal Gupta, a 3rd yr CSE undergrad at SSN, Chennai, India. \nWhile most people generally pick up a topic, or a concept (like say Computer Vision, Big Data, or just Algorithms), understand it and aspire to excel at it\u2026 I fell in love with a language, Python. As someone who has started out by learning C++ in school, learning Python was as easy as surprising. The speed at which I could translate ideas to code was amazing, and oh boy, all I wanted to do was make things, write simple scripts to automate everyday tasks. And hence I continued to explore Python, the countless modules and possibilities with Python. I went to Hackathons, won some but more importantly made something that others could use. Chatbots and me UI/UX has never been my strong suit but Chatbots made it simple to use serve any application in a conversational manner. Over the last 2 years, I have developed over a dozen chatbot for a variety of purposes, from fetching torrent links to code education to keeping track of events. One of my best messenger chatbots is still functional with nearly ~500 subscriptions. PyGeon , scrapes a number of sites everyday for developer events such as meetups, hackathons and contests in 7 indian cities. Newly added events are sent to users every day. Experience : Chatbot intern at GoBumpr , Chennai CV intern at XR Labs , Chennai NLP intern at BicycleAI Google Summer of Code participant with Debian", - "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Vishal Gupta (~vishal11)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-nlp-and-chatbots~bkMJe/", - "title": "Introduction to NLP and Chatbots" - }, - { - "Content URLs": "https://github.com/atulsinghphd/NL", - "Description": "In this hands-on course using Python, we will learn how to use machine learning for Natural Language Processing (NLP) through interactive notebooks. Natural Language Processing (NLP) is a field that covers computer understanding and manipulation of human language. Machine learning is a branch of Artificial Intelligence that focuses on the ability to automatically learn from existing information. Language processing uses models that attempt to understand and represent the information at various levels that includes morphology, syntax, semantics, pragmatics and discourse. In this training, we will learn how to use machine learning to build these models. This training includes the following topics: Representing text as a vector using count, TF-IDF and co-occurrence matrix Detecting similar documents Sentiment Analysis Identifying the themes in a set of documents Extracting the entities and the relationship between the entities (stretch goal depending on time) The course will introduce the participants to NLP libraries such as nltk, gensim and Spacy", - "Last Updated": "21 May, 2018", - "Prerequisites": "This is an advanced machine learning course. To benefit from this course the participants are expected to have:\n1. Understanding of supervised and unsupervised machine learning \n2. Knowledge of python, or a high-level programming language like Java or C#.\n3. Using jupyter Python notebook environmen", - "Section": "Data science", - "Speaker Info": "Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), geo-spatial analytics, and reinforcement learning. Sasidhar Donaparthi I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company", - "Speaker Links": "Linkedin Profiles https://www.linkedin.com/in/sasidonaparthi https://www.linkedin.com/in/atulsinghphd/ Twitter Profiles @sdonapa", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Atul Singh (~atul98)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deciphering-human-language-using-machine-learning~bm0Ra/", - "title": "Deciphering human language using Machine Learning" - }, - { - "Content URLs": "Few resources that I will be using in the workshop. https://github.com/koshikraj/proof-of-ownership https://github.com/koshikraj/neo-python-contracts https://github.com/koshikraj/neo-ico-template", - "Description": "Bitcoin has been gaining popularity in the recent years due to its market value. But more importantly, the underlying technology is gaining the attention among the developers. Many developer communities inspired by bitcoin have created their own platform to use the underlying technology widely known as \"blockchain\" to achieve decentralization. Ethereum is one such platform that has created a blockchain platform which allows developers to develop their own decentralized applications (dApps) in the ethereum network by coding the logic in the execulatable contracts called \"smart contracts\" . Although ethereum has gained a huge fame due to its smart contract implementation to create decentralized applications, it imposes developer to write the logic in an ethereum's domain-specific language called Solidity. In addition to coding in a new language, it mandates the developer to set up a new develop environment. NEO blockchain platform provides a convenient way to develop smart contracts in general purpose programming language. NEO achieves this by providing compilers to compile code written in most of the languages to bytecode that can be executed in NEO virtual machine. Currently, NEO allows compilation of python smart contracts through neo-python project. This is the first blockchain project to provide such a freedom to the developer. NEO project provides plenty of benefits over other blockchain platforms out there. \nIt plans to achieve smart economy by creating a strong digital identity. It achieves faster transaction rate which is the key to scale any platform. NEO is being referred to as the \"New Ethereum\" due to its increasing popularity. I plan on conducting a workshop to create a decentralized application by developing and deploying smart contract using neo-python. Following would be the agenda of the workshop. Introduction to Bitcoin, Blockchain, and consensus to achieve decentralization. (30 mins) Introduction to NEO and Setting up a NEO platform (30 mins) Creating and deploying Hello World contract using Python (15 mins) Creating a Proof of Ownership system (30 mins) Creating a user interface to create a complete Proof of Ownership DApp. (20 mins) Creating an Initial Coin Offering (ICO) using an existing template and Q&A (25 mins) ** This is a rough estimation of time and topics as of now. I will try to fit more topics if possible. An attendee will be able to create an asset management DApp such as document ownership system or launch a basic ICO after attending the workshop", - "Last Updated": "20 May, 2018", - "Prerequisites": " Novice level experience in python programming. Basic knowledge of how bitcoin or blockchain technology is\n implemented would help to grasp the topic pretty well. Although I will be using Ubuntu Linux distribution for the demo, Attendees can use any platform which has python 3.6 installed. Windows users might have to install a docker container manager as installation might create some issues.", - "Section": "Networking and Security", - "Speaker Info": " I completed my masters in Computer science and Information Security after getting fascinated by the security and cryptography field. I have a demonstrated history of working in the computer and network security industry (RSA Security) where I had worked for more than a year. I worked as a senior fullstack developer for a start-up called CoWrks. In the meantime, I got involved in the blockchain and decentralized application. I started devoting my entire time to blockchain and I'm currently writing a research book on the blockchain technology called Foundations of Blockchain", - "Speaker Links": " My Linkedin profile. Few of my opensource contributions. My semi active social profile. Check out my detailed bio at koshikraj.com", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Koshik Raj (~koshikraj)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-decentralized-smart-contracts-using-python~egXra/", - "title": "Creating decentralized smart contracts using Python" - }, - { - "Description": "In this talk the main aim is to demystify data science and introduce the audience with the concepts of data science and machine learning in python. Goals : What is Data Science ? What is Machine Learning ? Why Python for Data Science ? How to solve a Real world problem with data science ?", - "Last Updated": "21 May, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Data science", - "Speaker Info": "Jatin Ahuja is a self taught data scientist and machine learning practitioner. He's currently working in Data Science domain . He's the core team member (designated as PR Director) and city ambassador of AI Saturdays which is a community of over 5000+ students(over 100+ cities) to spread the knowledge of AI free of cost. He actively blogs about machine learning in his personal blog site named as everythingai . He mentors the aspirants in their journey to become a successful data scientist , machine learning engineer or deep learning engineer at MentorCruise.com ", - "Speaker Links": " Website ; https://everythingai.co.in Github : https://github.com/A-Jatin LinkedIn : https://linkedin.com/in/jatin-ahuja-89677614a/ ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "JATIN AHUJA (~jatin)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-science-with-python~enm5d/", - "title": "Data Science with python" - }, - { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "Abstract In this talk, I would be telling people how to write better and faster Python. I've been developing Python programs, scripts and softwares for over 2 years now and I come across people who have a problem of Python being slow. \nWhenever someone has to write a faster python code they are left with one option of just shifting their entire code from Python to C or C++. This talk will clear that misconception. People can actually write faster codes in Python, the only missing fact is how? . And this is exactly why I am interested to give this talk. Contents of the talk The talk will start with a basic introduction of myself as a Python developer. I will then talk about the misconception about shifting the code to C or C++. Then I will proceed onto some basic usage of Python Programming Language. Introduction to optimization techniques in Python. Then I will talk about when and why should one optimize their application. I will introduce the basic concepts of optimization in Python. Tell people about the available/built-in functions that can come in handy. Then I will proceed onto giving a demonstration on 'Writing better functions'. The talk will conclude with some examples of optimized code that performs better than conventional approaches. The talk will be open to questions, to make it more interactive and fun. The slides will be shared to the audience after the talk", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Will to learn See, It does not require much", - "Section": "Core python and Standard library", - "Speaker Info": "My name is Manish Devgan . I am a second year Information Technology student at Netaji Subhas Institute of Technology, Delhi . I am an Open Source Contributor and a learner . I have contributed to various different open source projects and won many hackathons . I was FOSSASIA Codeheat 2017 - Grand Prize Winner and Google Code-In 2017- Mentor . Currently I am a GSoC 2018 Student under FOSSASIA and RGSoC 2018 - Coach . I have contributed to Python's ChatterBot Machine Learning Engine , variety of FOSSASIA's Projects , and a wide variety of OSS projects like Github Linguist etc. Python is my favourite programming language . From writing small scripts to building small Machine Learning libraries , I've tried a lot :", - "Speaker Links": " https://github.com/gabru-md https://twitter.com/gabru_md https://facebook.com/gabrumd https://www.linkedin.com/in/gabru-md/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Manish Devgan (~gabru-md)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-faster-python-optimizing-your-code~ejJye/", - "title": "Writing Faster Python : Optimizing your code" - }, - { - "Description": "Many at times, we need to encapsulate our core logic in order to protect it from being reverse engineered and being exploited. Having a strong IP may not be the only protection. Once the code is open for the analysts, they can easily implement a modified version to achieve their goals. Some areas where the code obfuscation plays an important role are financial domain, security, web/mobile. Many times developers / teams fail to achieve the right level of code obfuscation which in turn fails to provide the level of protection to their code. We will be walking through the existing code obfuscation techniques in python and the level of protection they offer. I will be sharing my experiments and learnings during the journey to achieve a better obfuscation mechanism for python code", - "Last Updated": "22 May, 2018", - "Prerequisites": "Required : None. As we will be covering the required basic for code obfuscation in the talk it self. Good to have : Understanding the python run time process and how the code gets converted to executable binaries can be helpful", - "Section": "Core python and Standard library", - "Speaker Info": "I am Kailash, currently working as a Senior Software Engineer in Visa. I have been into python programming for the past 6 years now. I had worked on multiple levels of python projects ranging from scripting and automation, DevOps, Machine Learning, Computer Vision, Algorithmic Trading, Website Backends", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Venkata Naga Kailash Anantha (~avnkailash)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/effective-code-obfuscation-protecting-your-python-code-from-being-copied-reverse-engineered~axzld/", - "title": "Effective Code Obfuscation : Protecting your python code from being copied / reverse-engineered" - }, - { - "Content URLs": "wikipedia article on the brain computer interface Text Summarizer neural network model code is in the following lin", - "Description": "Brain Mapping Using Python: Over the past few years, machine learning and artificial intelligence has been making headlines and advancing quickly by creating products that can make optimistic decisions. Now this machine learning technology can be implemented in making a machine which can perform complex actions just like in brain which can make human life easier. Now the real challenge is can we create a neural network model which can perform complex\nactions like human brain? How Python can be used to accomplish this task and how far we can achieve this feat?\nThis talk will be focusing on the methods approached by brain to generate conclusions or make decisions which can be replicated in computers and generate results. Contents of the talk About me - Basic introduction of myself. What is Brain Mapping? Functionalities of Human Brain. Neural Networks Using Python. Types of Data Summarisation techniques in Python. How Computers can make decisions. What can we expect from Brain Mapping in future.", - "Last Updated": "21 May, 2018", - "Prerequisites": " basic syntax knowledge of python basic machine learning terminology neural network models functionality", - "Section": "Data science", - "Speaker Info": " ROHITH PUDARI Rohith is a B Tech student who is passionate about integrating the most complex organ known to human which is brain with computers. He is winner of the Hyderabad best coder championship conducted by JNTUH. He is one of the few persons in India who is selected for the google Udacity scholarship. He is always interested in decreasing the interaction gap between computers and humans and started his research in creating an interface which will allow humans to interact with computers in a more natural way. He created a neural network model which generates a summary of a given essay which won the title \"Best innovative idea\" at IIT Kanpur", - "Speaker Links": "you can see the projects and previous work of Rohith in the following link to his github profile. and linkedIn profile Rohith contributed to the following open source projects: Atom- open source code Editor OpenWISP- software platform that implements a complete Wi-Fi service Sugar Labs- desktop environment and learning platform Sustainable Computing Research Group (SCoRe)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "dvlpr_rohith", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/brain-mapping-with-python~bonYa/", - "title": "Brain Mapping with Python" - }, - { - "Content URLs": " Will share my slides after my talk as a Github repository.", - "Description": " Abstract This talk is for Python web developers interested in learning what are\nthe core ideas behind microservices, what problems they try to solve,\nand what are the viable options to implement them in Python, both from\ntechnical and teamwork point of views. Some of the topics that will be\ndiscussed include the role of APIs, the improvements microservices\nbring to application scalability, upgrades, and maintenance, and the\nchallenges in breaking up a monolithic application. Contents of the talk About me - Basic introduction of myself. What are Microservices? Monolithic Python Web Application. Problems with Monoliths. Microservice Example. Advantages of Microservices. Disadvantages of Microservices. How to refactor a monolithic application into microservices? ", - "Last Updated": "22 May, 2018", - "Prerequisites": " Basic Python", - "Section": "Core python and Standard library", - "Speaker Info": " My name is Kasam Sharif (Passionate Programmer | Startup Enthusiast |\nProblem Solver). I am currently Software Engineer at Agrostar, Pune.\nPreviously was working at Symantec having 3 year of experience in IT\nindustry. In free time love to learn new things.", - "Speaker Links": " Linkedln : https://www.linkedin.com/in/kasam-sharif-2027628b/ Twitter: https://twitter.com/kasam_sharif94 Github: https://github.com/kasamsharif", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kasam Sharif (~kasamsharif)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-microservices~dyA6d/", - "title": "Python Microservices" - }, - { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "RabbitMQ is a powerful messaging broker based on the Advanced Message Queueing Protocol (AMQP). Microservices do what they say on the tin. They\u2019re small, isolated services that represent an equally small portion of your business domain. Recently there's a trend to build an application using Microservices which place an emphasis on small processes. As an increase in Microservices, we need to a mechanism where we could use some channel(Pub-Sub) to talk between these Services. Contents 1) Introduction to RabbitMQ and Its Terminology 2) Microservices using Pub-Sub 3) Sample Execution At the end of this session, participants will be able to use the rabbitMQ for there application(Could be ETL's/ MicroServices etc", - "Last Updated": "22 May, 2018", - "Prerequisites": "1) Basic Pytho", - "Section": "Others", - "Speaker Info": "My name is Jigar Shah. I have completed my BTech from Walchand College of Engg Sangli. I am currently working as a Software Developer @Browserstack. Interests: Building Backend Architecture, System Design, Data Structures, Algorithms More Inf", - "Speaker Links": "Github Linkedl", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Jigar Shah (~jigarshahindia)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rabbitmq-in-python-for-event-based-communication-between-microservices~az4qd/", - "title": "RabbitMQ in Python for event-based communication between MicroServices" - }, - { - "Content URLs": " The main sunpy website - SunPy.org The code repository - sunpy My Experience with working on the SunPy project - Blog SunPy Gallery - Examples My Contributions to the SunPy Project - Code + Examples Contribution", - "Description": "The Problem The Sun releases huge amount of magnetic energy in the form of X-rays, EUV (Extreme ultraviolet) and high energy particles. This kind of radiation bursts can cause damage to space and ground based technological infrastructure. \nHence monitoring such solar activity is crucial. Research Work There has been considerable research in the field of solar activity monitoring as done by NASA Space Stations. Primary research includes locating sunspot regions or potential regions of high solar density along with detecting solar flares from the solar data. Solar Physics in Python In the field of solar physics, IDL is regarded as the primary programming language for solar data analysis purpose. But due to its less popularity and complexity there has been transition to using a much simpler yet robust language Python. The SunPy Project is such a community developed open source project for solar data analysis purpose based in Python. So how using python we can benefit the astrophysics and helio-physics community to query solar data and analyze them much more efficiently and produce much more insightful results ? In this talk we will be discussing how we can analyze sunspots and solar flares through image-processing tools using a python package called sunpy . A small example Locating Solar Spikes in the solar Map Original observed AIA image After locating such regions Extras More examples - SunPy Gallery Machine Learning with Solar Data", - "Last Updated": "22 May, 2018", - "Prerequisites": " Knowledge of Python (Beginner/ Intermediate) Little bit knowledge about the sunpy package (not mandatory) Python modules like scipy and matplotlib since there is heavy use of this two modules. A lot of excitement and passion for open science", - "Section": "Data science", - "Speaker Info": "Prateek has been an open source enthusiast for the past 2 years with a deep love in the field of astronomy and helio-physics . He is currently an undergraduate in computer science also a GitHub Campus Expert working directly with GitHub Education to build open source communities and support them on campus. He is a core contributor to the SunPy project for around more than a year which is lead by researchers from different universities along with scientists at the NASA Goddard Space Flight Center", - "Speaker Links": " GitHub Profile - prateekiiest Twitter - prateekiiest Website - prateekiiest,github.io GitHub Campus Expert - prateekiiest @campus_expert Blog - Medium", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Prateek Chanda (~prateekiiest)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/predicting-sunspots-and-solar-flares-with-a-tinge-of-python~dBXQa/", - "title": "Predicting Sunspots and Solar Flares with a tinge of Python" - }, - { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Malware is a serious threat to all kind of Cyberinfrastructure. Since the first known malware (formerly or generally known as Virus) there have been malware detection techniques. There is the arms race between new incoming of Malware and defense against it. Traditionally, anti-virus software uses signature-based techniques to detect malware and protect the underlying system. Due to some critical limitations of signature-based techniques, anti-virus, and security agency looking for alternative techniques and investing in machine learning based techniques for malware detection.\nThis workshop aimed to train the participants through various steps involved in building malware classifier based on machine learning algorithms. Python is very suitable for the task due to its large number of useful modules suitable for each and every step. During this workshop, following topics will be explained with proper hands-on using Python. Explanation of the topic and draw out the various required steps. Data collection: How to collect Malware and Benign samples for the experiment. Pre-processing: How to carry out various pre-processing tasks\n (duplicate removal, file type identification etc.) to prepare the suitable dataset for the experiment. Labeling: How to label the sample i.e. malware v/s benign. (Required\n for supervised learning.) Feature extraction: How to extract features from the sample and\n build the proper representation of features to be used with various\n Machine learning algorithms. (We will restrict to static features\n for this workshop). Model training and Testing: How to train various machine learning\n algorithms and test their performance to select the best model. Making model persistence: How to make the selected model persistence\n to further use. ", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general. Required module/library:\n1. pefile\n2. androguard\n3. scikit-learn\n4. CS", - "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-malware-classifier-from-sample-collection-to-persistance-model-using-python~eEXWd/", - "title": "Building Malware Classifier: From Sample Collection to Persistance Model using Python" - }, - { - "Description": "The Talk will focus on the importance of satellite image processing with main focus on the utilisation of GDAL library to conduct various operations on satellite data. Datasets will include Optical imagery and Synthetic Aperture Radar Imagery. The power of GDAL library alongwith numpy and matplotlib will be demonstrated. Brief analysis of satellite images using python will be given", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of numpy and matplotlib libraries", - "Section": "Data science", - "Speaker Info": "Shubham Sharma is a Junior Research fellow currently working on a collaborative project with Calibration and Validation Division of Space Applications Centre, ISRO, Ahmedabad. He has a rich experience in handling and processing of Synthetic Aperture Radar Images. Also, he has experience in building software tools in python for satellite Image analysis", - "Speaker Links": "https://in.linkedin.com/in/shubham-sharma-5468578", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "shubham_thb", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/satellite-image-processing-with-python~dJKKe/", - "title": "Satellite Image Processing with Python" - }, - { - "Content URLs": "will be sharing the slides after my talk as a Github repositor", - "Description": "AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment. CloudFormation allows you to use a simple JSON or YAML file to model and provision, in an automated and secure manner, all the resources needed for your applications across all regions and accounts. This file serves as the single source of truth for your cloud environment. In this talk, I will be using Python to generate the JSON and YAML files with which AWS CloudFormation can be done. During this talk I will be covering the below points What is AWS CloudFormation? Library in Python for AWS CloudFormation. What are S3 and EC2 AWS services. Creating basic S3(Simple Storage Service) and EC2(Elastic Compute Cloud) instance using Python. Installing MySQL in the EC2 instance. Code pipeline (Automatic Deployment from Github to production server)", - "Last Updated": "25 May, 2018", - "Prerequisites": "Basic Understanding of Python and how to use Libraries", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Mohan currently working as a Software Engineer at Amzur InfoTech Visakhapatnam.I have been in to Python Programming for the past 1 year. I have 2 years of experience as a Developer. I had worked on Data Migration. I am currently working on Data Science,MicroGrids Automation and AWS", - "Speaker Links": "www.linkedin.com/in/mohan-pavan-kumar-bailapudi-5628a296 https://github.com/MohanBailapud", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Mohan Bailapudi (~mohan57)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-cloudformation-with-python~dL1De/", - "title": "AWS CloudFormation with Python" - }, - { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Python is a versatile, powerful, and general purpose language, its easy and clear syntax makes it very popular for the beginner as well as the advanced programmer. Malware is one of the top threats to today's digital society. Due to heavy financial loss along with other infrastructure losses, the software industry is investing hue money for malware research and at the same time due to the wide need of effective and efficient anti-malware solution, the anti-virus industry is emphasizing on malware research.\nThis talk will focus on the array of python resources (script, modules, library, frameworks etc.) available for various dimensions of malware research. During the talk, I will share my experience with various tasks or problems related to malware research and how with the use of Python, those were solved. This talk will try to draw a parallel connection with various tasks related to malware research and suitable Python resources available for achieving those tasks. The talk will be supplemented with the brief explanation of concepts and python snippets for the same. \nSome of the modules and topics that I will touch upon are: yara Accessing VirusTotal API with Python Cuckoo-sandbox Androguard pefile pyew file type filtration ClamAV and pyClamd etc.", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general", - "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-arsenal-for-malware-research~dGXKe/", - "title": "Python Arsenal for Malware Research" - }, - { - "Content URLs": "I'll share my slides after my talk as a GitHub repository", - "Description": "This talk is for Python enthusiasts who are interested in building test automation framework and test suites for REST API functional testing. It would throw a light on how to write useful, business-oriented and maintainable functional API test suites in Python on top of existing test frameworks like lemoncheesecake . Contents: About myself REST API and it's testing - A quick introduction Choosing a test framework to write your tests on Making API requests from Python Writing suite configuration and teardown code Introduction to the \"component-tests\" model for structuring the test code JSON parsing, use of matchers, asserts for writing test case validation criteria Importance of logging and reporting - How logs and readable reports can ease the job of debugging bugs found using tests Bringing everything together", - "Last Updated": "24 May, 2018", - "Prerequisites": " Python basics REST API basics Basics of test frameworks like pytest Passion for test automation", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm currently working as a SDET Lead with AgroStar, India's largest agri-tech platform for the Indian farmer. I'm passionate about technology and automation, I'm willing to contribute in building robust software test frameworks accompanied with some of the best industry practices like CI/CD that would help ensuring the best possible software quality from time-to-time. The \u201calways exploring and learning\u201d attitude is something that keeps me going", - "Speaker Links": " LinkedIn Facebook Twitter", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Akshay Maldhure (~akshay61)", - "created_on": "24 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rest-api-functional-testing-with-python~aK7Ga/", - "title": "REST API functional testing with Python" - }, - { - "Content URLs": "Fo now, I just have a gist: But I will create a proper package before the event: https://gist.github.com/dhilipsiva/3d7586e7bb941919f28afa70ccc39dd", - "Description": "Microservices are fun. But what would make them even more fun to work with, is if we can avoid duplicating the data layer across your micro-services. Django ORM is amazing. Let's share the joy of Django ORM with other languages. I have written a tool to automatically expose Django ORM to other languages and which can also generate respective client libraries in other languages. I heavily rely on Protobuf and gRPC and a lot of AST parsing", - "Last Updated": "25 May, 2018", - "Prerequisites": "You will need to know basics of: Django ORM Protobuf gRPC (or cap'n proto or any other RPC framework) Microservices", - "Section": "Developer tools and Automation", - "Speaker Info": "Wannabe Astrophysicist. Full Stack + DevOps. I code for fun and profit. Mostly in Python. FOSS. Dad of 2. Environmentalist. Atheist. Story Teller", - "Speaker Links": " http://dhilipsiva.com/ https://twitter.com/dhilipsiva https://github.com/dhilipsiva/", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "dhilipsiva Dhilip (~dhilipsiva)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automagically-exposing-djagno-orm-over-grpc-for-microservices-written-in-other-languages~aMKmd/", - "title": "Automagically Exposing Djagno ORM over gRPC for microservices written in other languages" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "The era of Artificial Intelligence is moving quite rapidly across the globe. It's being used in almost every application we know , from medical diagnosis to self driving cars and it's use is still growing exponentially. But should we blindly trust AI ? Is this technology robust enough? Are we capable enough to handle it's power? In this talk we will step back for a moment and look forward about the security issues and robustness of this technology. I'll be discussing the problems we can face , the precautions we have to take, etc. with the help of a famous problem, known as One Pixel Attack ", - "Last Updated": "25 May, 2018", - "Prerequisites": " A bit of Python Some knowledge of Machine Learning And a broader perspective ", - "Section": "Data science", - "Speaker Info": "The speaker, Srajan Kant Jha, is a final year B.E. student who has been working on Machine Learning and Data Science from quite a while now. Nonetheless, he pivoted from C/C++ to Python and during the transition, has also developed some projects on the same. He used to blog at his leisure time and is still on a venture to provide the knowledge of ML and Data Science to enthusiasts through a project site. Srajan is also the City Ambassador (and one of the speakers) of AI-Saturdays, which is a community of over 5000+ students(over 100+ cities) that helps people try their hands on Deep Learning and Artificial Intelligence, free of cost. Inspite of this, he still has a lot to discover in this growing industry. (Follow him on social media to know more", - "Speaker Links": " LinkedIn : https://www.linkedin.com/in/srajan-jha Github : http://github.com/srajan23 (not much updated) Facebook : https://www.facebook.com/srajan23", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Srajan Jha (~srajan)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-robust-is-artificial-intelligence-ai-using-python~dNK2e/", - "title": "How ROBUST is Artificial Intelligence ? ~ AI using Python" - }, - { - "Content URLs": " Github reposistories: Keras_aud Audio-Vision Drive links: Content link : (Slides to be uploaded soon)", - "Description": "In this workshop, we will try to teach how to understand Deep Learning, various paths to follow, Domains to explore and the most important part- how to start with the paper selection and implementation. We will also learn how to deploy a simple model into production. This workshop aims at providing the attendees of all level a foundation of research and further prospectives in deep learning. Contents Paths and prospects in Industry and Academia (10 minutes) Difference between AI, ML, and DL. (5 minutes) Introduction to Deep Learning frameworks (Hands-on) (5 minutes) Paper selection (10 minutes) Implementation (Hands-on) (60 minutes) Understanding the dataset Feature Extraction Model Selection Data Formatting Comparison Demonstration of our work (General Overview) Audio Tagging Acoustic scene classification Visual Question Answering Publish/Deploy (Hands-on) (30 minutes) Stay Motivated Opportunites to explore The participants should have interest in Research. Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first-time learner\u2019s of AI to comprehend", - "Last Updated": "27 May, 2018", - "Prerequisites": "Preferred Basic Python concepts Basic knowledge about Machine Learning Algorithms. Preferred (but not necessary) Interest in working on Research problems Installed libraries: Keras Theano or Tensorflow", - "Section": "Data science", - "Speaker Info": "Aditya Arora and Akshita Gupta are currently final year semester exchange students at Indian Institute of Technology, Roorkee. They have been working on research problems using deep learning specifically in Audio processing and visual Q&A. Aditya is a member of various open source societies such as rust-community while Akshita has experience in Academia research and is a selected as an Outreachy intern at Mozilla 2018. They have been working in python for the past 4 years and have been moving forward working on Computer Vision and Audio processing problems", - "Speaker Links": " Twitter : https://twitter.com/imaarora Twitter : https://twitter.com/akshitac8 Linkeldn: https://linkedin.com/in/aditya-arora145/ Linkeldn: https://www.linkedin.com/in/akshita-gupta152/ Github : https://github.com/channelcs Blog : http://channelcs.github.io/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Akshita Gupta (~akshitac8)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-into-the-world-of-deep-learning~aOXRb/", - "title": "Deep Dive into the world of Deep Learning" - }, - { - "Content URLs": "The repository where I have implemented concepts related to this talk https://github.com/tanayseven/http_quiz Contents for the presentation for the talk https://github.com/tanayseven/pycon_2018_python_web_app_tes", - "Description": "Abstract One of the first projects that I worked in the industry was in Flask . This talk is based on my experiences in the project with respect to the test suite and different things that I learnt in that. On the bases of those learnings, I started my own open source project on Github and enhanced on those ideas on how all the things necessary for testing are done. This is based on Flask as the web framework and all the ideas are implemented in it. The topics it covers are those things that you can do to achieve a robust set of tests in your code. Outline of the talk Pushing for 100% code coverage Making your test execution fast! The evil of \u2018over mocking\u2019 The necessity of using dependency injection Test Pyramid or Test Cone? TDDing while making changes Layers that make the web app architecture How does this map to UI testing", - "Last Updated": "27 May, 2018", - "Prerequisites": "Although most of the things are implemented in Flask, it is not necessary to know it, although it is very much recommended to know some web framework or having some knowledge of web app programming", - "Section": "Web development", - "Speaker Info": "A passionate developer with Python as his primary language. Have worked with Flask in the industry in the past. Passionate about testing and writing the code in a way that is very clean and maintainable. A strong believer in TDD and massive test coverage", - "Speaker Links": "https://tanayseven.com https://github.com/tanayseven https://www.linkedin.com/in/tanay-prabhudesai/ https://twitter.com/tanayseve", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanay PrabhuDesai (~tanay)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/having-a-robust-test-suite-for-your-python-web-app~dPKAb/", - "title": "Having a robust test suite for your Python web app" - }, - { - "Content URLs": "https://en.wikipedia.org/wiki/OpenFlow\nhttps://www.openvswitch.org/\nhttps://3vf60mmveq1g8vzn48q2o71a-wpengine.netdna-ssl.com/wp-content/uploads/2014/10/openflow-switch-v1.5.1.pd", - "Description": "Networking is a key aspect of any cloud infrastructure solution. All the VMs and containers\nspawned in a cloud deployment should have seemless layer 2 and layer 3 connectivity. All this is\npossible because of virtual switching and virtual routing. This session talks about what is OpenFlow specification, OpenvSwitch (which implements OpenFlow)\nand how it is used as an important SDN layer in cloud infrastructure solutions (taking OpenStack and OVN as an example)", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of networking", - "Section": "Networking and Security", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": "https://numans.blog/about/\nhttp://stackalytics.com/?metric=commits&release=all&user_id=numansiddique\nhttps://github.com/openvswitch/ovs/commits?author=numansiddiqu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-introduction-to-openflow-and-openvswitch~aQKGd/", - "title": "An introduction to OpenFlow and OpenvSwitch" - }, - { - "Content URLs": "https://tools.ietf.org/html/rfc7047\nhttps://github.com/openstack/ovsdbapp\nhttp://www.openvswitch.org/support/dist-docs/ovsdb-server.1.htm", - "Description": "OpenvSwitch is an OpenFlow virtual switch implementation. It has its own database implementation based on JSON-RPC (https://tools.ietf.org/html/rfc7047) to store its internal state and data.\nThis session gives an overview of this database implementation and how it used in OVN, an SDN controller from the OpenvSwitch community and in OpenStack networking. This session will look\ninto how it is different from other traditional SQL databases and the python clients available to interact with the OVSDB server and the APIs it provides to carryout the CRUD operations with the OVSDB server", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of databases", - "Section": "Core python and Standard library", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": " https://numans.blog/about http://stackalytics.com/?metric=commits&release=all&user_id=numansiddique https://github.com/openvswitch/ovs/commits?author=numansiddique", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/openvswitch-database-based-on-json-rpc~dRKVe/", - "title": "OpenvSwitch Database based on JSON-RPC" - }, - { - "Content URLs": "I will share the slides on my github repo for the evaluation by the team in some days.\nOther content will be shared on github after the talk", - "Description": "Training a machine learning / deep learning model is one thing and deploying it to a production is completely different beast. Not only you have to deploy it to a production, but you will have to retrain the model every now and then and redeploy the updates. With many machine learning / deep learning projects / POCs running in parallel with multiple environments such as dev, test prod, managing model life cycle from training to deployment can quickly become overwhelming.\nIn this talk, I will discuss an approach to handle this complexity using Docker and Python.\nRough outline of the talk is, Introduction to the topic Problem statement Quick introduction to Docker Discussing the proposed architecture Alternative architecture using AWS infrastructure Demo", - "Last Updated": "28 May, 2018", - "Prerequisites": " Basic Python Basic Docker", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company.\nI have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures.\nSince past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "saurabh1deshpande", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-devops-and-ab-testing-using-docker-and-python~bWKEb/", - "title": "Machine Learning DevOps and A/B testing using docker and python" - }, - { - "Content URLs": "https://speakerdeck.com/aravindputrevu/introduction-to-application-performance-monitorin", - "Description": "Often late, the time to debug that particular bug/issue occurring in production with respect to your application is increasing. It might also cause business disruption and affect your organization financially. In this talk, I'd explain how you could use Application Performance Monitoring to understand your application. Application Performance Monitoring (APM) is a solution built on Elastic Stack. APM helps you to build/store data points in Elasticsearch and visualize. It automatically collects information from your python application/service. This talk mainly targets at introducing the solution, why it is needed and what you can do with data. It ends with once data is stored within Elasticsearch, what else you can use the same data for (ex. Infrastructure Monitoring, Machine Learning)? Agenda What is APM?\nWhy APM?\nWhat it can do to your Application?\nDem", - "Last Updated": "28 May, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "Aravind is a loquacious person, who has something to talk about everything. He is passionate about evangelising technology, meeting developers and helping in solving their problems. He is a backend developer and has six years of development experience. Currently, he works as a Developer Advocate At Elastic and interact with developer community in South East Asia and India. He has deep interest in Machine Learning, Security Incident Analysis and IoT tech. In his free time, he plays around Raspi or a Arduino", - "Speaker Links": "https://aravindputrevu.in will have links to all my social accounts. I have been doing community work for last 3 years. Presenting the same talk at PyCon Bangkok on June 16-17. https://th.pycon.org/talks/#monitoring-your-python-applicatio", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aravind Putrevu (~aravind34)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-your-python-application~eV2ze/", - "title": "Monitoring your Python Application" - }, - { - "Content URLs": "https://github.com/hasura/gitkub", - "Description": "Gitkube is an open-source project that brings the developer experience of Heroku, on your own kubernetes vendor within 60 seconds . This means that you can take your python app, deploy it with a git push & scale it massively all on infrastructure you own at a fraction of the cost on Heroku. After a brief introduction, this talk will be a live-coding demo + tutorial. \nAudience members are encouraged to bring their own laptops with python apps and follow along in the talk to deploy their app. Permitting time, the talk will cover how gitkube works and how developers can contribute", - "Last Updated": "29 May, 2018", - "Prerequisites": "Python\nGi", - "Section": "Developer tools and Automation", - "Speaker Info": "Tanmai runs a startup, Hasura, where they're building tools to make it easier for developers to move to GraphQL and Kubernetes. \nThey were early adopters in the container ecosystem (pre-1.0 adopters for both Docker and Kubernetes) and have grown and contributed to the ecosystem as a company especially in India. Before this, Tanmai ran a consulting firm where their work included everything from MVPs for startups to helping one of the largest banks in the world migrate from legacy monoliths to containerised microservices. Tanmai has been building applications for over 8 years with a variety of frameworks. He is a firm advocate of democratising the power to develop applications and is the proud teacher of one of the largest tech MOOCs in India, imad.tech", - "Speaker Links": "Kubecon talk on gitkube: https://www.youtube.com/watch?v=gDGT4Gf_4JM Hasura: https://hasura.io LinkedIn: https://www.linkedin.com/in/tanmaig/ Twitter: https://twitter.com/tanmaig", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanmai Gopal (~tanmai)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demo-tutorial-git-push-to-deploy-your-python-app-to-kubernetes-heroku-style~e1pZd/", - "title": "Demo + tutorial: Git push to deploy your python app to kubernetes - heroku style!" - }, - { - "Content URLs": "https://docs.microsoft.com/en-us/python/api/overview/azure/?view=azure-pytho", - "Description": "Python SDK for Azure is natively available. We would explore how this SDK can be used for automation and management of Azure. Python makes it easier for IT Pros and Developers to build a rock solid DevOps pipeline with simple script", - "Last Updated": "28 May, 2018", - "Prerequisites": "Basic understanding of Azure or any cloud\nBasic Python knowledg", - "Section": "Developer tools and Automation", - "Speaker Info": "Wriju works for Microsoft as Cloud Solution Architect. He is with Microsoft for more than 13 years and total of 17 years of industry experience. He is one of the first to play with Azure in its very early stage back in 2008. His day to day job is to help a big Oil and Gas Enterprise to adopt cloud as the strategic platform. His key area of focus is to help customer migrate their line of business applications to Microsoft Azure. Application modernization is another aspect. This involves designing and implementing Serverless workflow and Microservices. He helps Architects to design and implement the solutions which are cloud scale", - "Speaker Links": "Twitter handle: @wrijugh\nBlog: https://blogs.technet.microsoft.com/wriju\nLinkedIn: https://www.linkedin.com/in/wrijughosh", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Wriju Ghosh (~wriju)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-and-automating-azure-with-python~eXXve/", - "title": "Managing and Automating Azure with Python" - }, - { - "Content URLs": "Slides Repositor", - "Description": "I'll be sharing how Python has been of help in my transformation from a hobby developer to a researcher.\nCoding and in particular, simulations are used extensively in the field of research to verify results and sometimes serve as experiments when it is physically not feasible. I'll describe step by step, how to design a real-time simulator using the example of an aerial swarm of drones in a survivor rescue scenario with the help of common Python libraries", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic understanding of Python classes and objects Enthusiasm to learn something new Love for Python", - "Section": "Core python and Standard library", - "Speaker Info": "Aniq Ur Rahman, Final year undergraduate student from NIT Durgapur. Summer '18 Research Intern at CERN GSoC '17 Intern at RoboComp Summer '17 Research Intern at SWAN Labs, IIT Kharagpur", - "Speaker Links": "Linked In Blo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aniq Ur Rahman (~Aniq55)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-research~eZGQa/", - "title": "Python and Research" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "Artificial Intelligence is spreading in the modern world and it has changed the face of technologies in past several years, especially Information technology. Today we are much engaged with using and developing so-called intelligent computing systems and devices. This paradigm has evolved in many sub-areas likewise Machine Learning, Deep Learning & Neural Networks. These sub-areas of AI have a greater role in solving Vision problems( e.g. image recognition, object & activity detection etc.), Speech problems( e.g. ASR, trigger word detection, language translation etc.) and many more complex problem domains with help of robust algorithms & models. this talk will be focused on Sequence Neural Models used for solving the Speech and text problems and we will be introduced to real-world applications. topics covered during the talk Introduction Recurrent Neural Networks Word embeddings Attention Models(Trigger word detection) Real World Applications", - "Last Updated": "29 May, 2018", - "Prerequisites": "Machine Learning\nBasics of Neural Networks\nPython Programming Machine Learning( Basics) Basics of Neural Networks Python", - "Section": "Data science", - "Speaker Info": "The speaker, Prashant Kumar Rai, is a final year M.C.A. student at Department of Computer Science (Pondicherry University, Puducherry) who has been working on Machine Learning and data science for quite a while. he pivoted from C to Python in his first year of Master's and currently using this for his projects. He used to blog at his leisure time. Prashant is also a course mentor for 'Sequence Models' part of Prof. Andrew Ng' s Deep Learning Specialization on Coursera, where he helps learners who need in-course assistance and feedback to successfully complete a course", - "Speaker Links": "Github Twitter Quora LinkedIn Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "PRASHANT KUMAR RAI (~pkraison)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/follow-the-sequence-in-deep-way-introducing-sequence-models~bYYAb/", - "title": "Follow the Sequence in Deep way - Introducing Sequence Models" - }, - { - "Content URLs": "Content will be shared on github after the workshop. I will share detailed plan for the workshop in a while for the review", - "Description": "Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero ( https://deepmind.com/blog/alphago-zero-learning-scratch/ ). \nOpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms. In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding. Content Introduction to Reinforcement Learning (~ 15 mins) Introduction to Reinforcement Learning algorithms (~ 15 mins) Setting up OpenAI Gym and other dependencies Implementing simple algorithm using one of the atari games from OpenAI Gym (~ 1 Hr 15 mins) Quick overview of deep reinforcement learning and important papers in the area (~ 15 mins)", - "Last Updated": "29 May, 2018", - "Prerequisites": "Participants must be well versed with python. Some exposure to analytics libraries in python such as numpy, pandas, keras, tensorflow, pytorch would help", - "Section": "Data science", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company. I have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures. Since past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "saurabh1deshpande", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-reinforcement-learning-using-openai-gym~b2qMa/", - "title": "Introduction to reinforcement learning using OpenAI Gym" - }, - { - "Content URLs": "I'll be sharing the slides after my talk as a Github repository. Soon will be sharing a gist", - "Description": "Abstract One of the feature people love about Python is how it\u2019s dynamically typed. A lot of people are very reluctant on hearing this idea of static typing, they will come back bashing on what's the use of Python then when we introduce static typing in it. With the torch bearers of Python in the industry like Google, Quora, Instagram, and a lot of others retaining their stack on Python and introducing static checking there have to be some non-superficial benefits, which are worth discussing. This is Python class Employee(NamedTuple):\n name: str\n id: int = 3\n\ndef fib(n: int) -> Iterator[int]:\n a, b = 0, 1\n while a < n:\n yield a\n a, b = b, a+b Contents of the talk What's static typing Need of static typing Static typing in Python 3.6 Type checkers Demo mypy vs pytype Pros and Cons QnA and discussion", - "Last Updated": "29 May, 2018", - "Prerequisites": "Basic Python knowledge and a little overview of what is dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Harshil Rastogi is working as a backend software engineer @Innovaccer, previously he has worked as an NLP Scientist @Evalueserve", - "Speaker Links": "Find me on github , ohh you like QnA forums stackoverflow . Oops were you looking for a professional platform? Okay, LinkedIn it's", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harshil Rastogi (~harshil9968)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/static-typing-with-python-what-why-and-why-not-to~e3rAd/", - "title": "Static typing with Python. What? Why? and Why not to." - }, - { - "Content URLs": " https://fasttext.cc/ https://github.com/PacktPublishing/Learn-fastText https://github.com/facebookresearch/fastText/tree/master/python", - "Description": "FastText has been open-sourced by Facebook in 2016 and with its release, it became the fastest and most cutting edge library in Python for text classification and word representation. It is to be seen as a substitute for gensim package's word2vec. It includes the implementation of two extremely important methodologies in NLP i.e Continuous Bag of Words and Skip-gram model. Fasttext performs exceptionally well with supervised as well as unsupervised learning. The tutorial will be divided in following four segments : 0-10 minutes: The talk will begin with explaining common paradigms that are present right now. Are deep learning really necessary? 10-15 mins: what are word representations 15-25 minutes: The code will be shown and explained line by line for both the models (CBOW and Skip-gram) on a standard textual labelled dataset. Showing how you can do fast prototyping with minimal code. 25-30: How to use the pre-trained word embeddings released by FastText on various languages and where to use them. Why python3 is the best language for multi-language support and a note on general deep learning using fasttext. 30-40 minutes: For QA session. ", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic python knowledge. Some Knowledge on common NLP techniques.", - "Section": "Data science", - "Speaker Info": "Joydeep is a machine learning engineer/python developer and is a Principal Engineer at Nineleaps. 5 years back he saw the Zen of Python, fell in love with Python and has been in love with it since then. Apart from his day to day work is involved in blogging and podcasting on medium and flawcode. Teaching is another passion of his and he is a python/ML trainer at tecmax", - "Speaker Links": " Medium: https://medium.com/@joydeepubuntu/latest Github : https://github.com/infinite-Joy LinkedIn : https://www.linkedin.com/in/joydeep-bhattacharjee-934a1157/ Machine Learning Podcast: https://flawcode.com/episode/show/12 twitter: https://flawcode.com/episode/show/12", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Joydeep Bhattacharjee (~infinite-Joy)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cutting-edge-nlp-classifiers-in-one-hour-with-python-and-fasttext~b4v7e/", - "title": "Cutting edge NLP classifiers in one hour with Python and fastText" - }, - { - "Content URLs": "https://github.com/aj-jeste", - "Description": "Google Cloud Platform Deployment Manager (GCP DM) allows you to codify your infrastructure with minimal setup, just need to download the gcloud library and you're off to the races. While its simple to get started with GCP DM, its a whole 'nother ball game to write extensible and reusable DM code. In this talk I will show you how to scaffold your code into two distinct groups: configs and templates. By separating these out you can reuse the same templates across multiple deployments with different configs and make your codebase a little bit smaller. How to write a basic DM deployment. Convert the basic DM deployment into a template. Launch multiple deployments with different configs but same template. Create custom helper functions in DM Best practices when using DM", - "Last Updated": "30 May, 2018", - "Prerequisites": "Understanding of Google Cloud Platfor", - "Section": "Developer tools and Automation", - "Speaker Info": "As a freelance Site Reliability Engineer and Cloud Architect, AJ has traveled all over the world helping startups setup and manage Cloud infrastructure. He has also architected and deployed large Hybrid on-prem/cloud infrastructure for existing well established companies that wanted a taste of the cloud but needed to keep their physical data-centers as well. This is his 11th year as a SRE/CA and has automated, scaled and monitored infrastructure anywhere from 150 to 3500+ nodes, both physical and virtual. Currently he is looking for his next challenge, perhaps its this pycon talk. Brought up and currently lives in New York City but travels all over the world in search of the best train journeys and awesome foods which seems to bring him back to India again and again", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "aj", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-cloud-platform-deployment-manager-scaffolding~b8zje/", - "title": "Google Cloud Platform Deployment Manager Scaffolding" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1PZ56AYSH6GZ8s-V8rfxHuZ16UCmDg03Y1L2EiTCBiUs/edit#slide=id.p \n(Subjected to changes, not final one)", - "Description": "Talk is about how python is useful in web development, what are the most powerful and popular python frameworks used i.e., Django, Pyramid, Flask and how they are used in making web applications. My talk covers : What a web framework means Why to choose python frameworks over the normal other frameworks Explanation on Django, Pyramid, Flask. Which framework should be chosen based on dependencies. Starting Web development with python. Django, Pyramid, Flask will be explained in short with the help of small code snippets. Examples of organizations using these frameworks will be given. Uses of one framework over the other will be told in detail", - "Last Updated": "29 May, 2018", - "Prerequisites": "No prerequisite is required. Desire to learn is enough to attend this talk", - "Section": "Web development", - "Speaker Info": "About Me I am Jameer, a third year Computer Science and Engineering undergrad at Amrita Vishwa Vidyapeetham, Kerala, India. I love to code in Python. So, I started my open source career by contributing to Coala organisation. Due to my open source enthusiasm, I started learning how python is useful in Web development and using Django, Flask etc., I am also an OSFY author and published an article related to how Hadoop is being used in Big Data Analysis. I am also a ACM-ICPC Regional participant at Amritapuri. I also have a keen interest in Chatbots", - "Speaker Links": "https://github.com/JameerBabu https://www.linkedin.com/in/jameer-babu-0199a2137", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Jameer", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-web-development~e5wYb/", - "title": "Python - Web Development" - }, - { - "Content URLs": "I will share the slides after my talk as a Github repository", - "Description": "If you are working in the field of research than you might be wondering about symbolic solutions which must be needed while working in such arduous fields like Mechanical Engineering or Computer Science or Quantum Mechanics. Sympy is the solution for that. Sympy deals with the computation of mathematical objects symbolically. This means that the mathematical objects are represented exactly, not approximately, and mathematical expressions with unevaluated variables are left in symbolic form. This talk will cover Introduction and Uses of Sympy Library", - "Last Updated": "30 May, 2018", - "Prerequisites": "Basics of Python is good. \nDon't know Python? It's still okay. You will definitely find something new", - "Section": "Core python and Standard library", - "Speaker Info": "Nikunj Parmar is a Sophomore year student at Nirma University. His major field is Flexible Robotics. He has been working with Python for last 2 Years as a Researcher. As a Junior Undergraduate student, He has worked on many projects focused on Robotics, Machine Learning, and Core OS Programming. His interests lie in the fields of Robotics, Design and Control Engineering, Computational Engineering, and its applications in a broad range of circumstances", - "Speaker Links": "https://www.linkedin.com/in/nikunj-parmar-b87739138/ https://github.com/nikunjparmar82", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Nikunj Parmar (~nikunjparmar828)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sympy-symbolic-computation-with-python~b6xOe/", - "title": "Sympy : Symbolic Computation with Python" - }, - { - "Content URLs": " https://github.com/errbotio/errbot http://errbot.io/en/latest/", - "Description": "The wikipedia definition of ChatOps is, a collaborative, conversation-centric way of working that brings people, discussions, bots, tools and files together in one central location: the workplace messaging app. That's it! That's what exactly I am gonna talk about. I am gonna talk about Chatops bot, Errbot which is written in python and can be used across various messaging apps like Hipchat, Slack, telegram, skype, etc. Using chatops one can automate the tedious, boring tasks and let the bot do the work for you. It also enables various engineering teams to collaborate and exchange information easily at one place: their official messaging app. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce chatops - culture, uses, possibilities. I will talk about the possible scenarios where we could use chatops in our daily tasks. I will then introduce Errbot and its plugin architecture. Tell audience about various features of errbot and its builtin plugins. Demonstrate errbot to audience by creating a command and using it in Slack. How to set up a alternate storage for errbot. I will conclude the talk explaining the ACLs(Access control List) in errbot.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic Python Passion for automation Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatops-using-python-bringing-developers-and-operations-together-making-tasks-easier~e9AJe/", - "title": "Chatops using Python - Bringing developers and operations together, making tasks easier!" - }, - { - "Content URLs": " https://www.djangoproject.com/ http://www.celeryproject.org/ https://sensu.io/", - "Description": "Monitoring is a key aspect for any business. It enables us to find and be notified about the problem way ahead our customer notices it, which enables us to keep our businesses running and making customers happy. I will be talking about how we SREs at Opentable Inc, tries to solve the good old monitoring problem, sensu with puppet, using Django, Sensu and Celery. If you are fed up with the limitations of what current monitoring tools offer, this is the talk you wanna look out. At the end of talk, audience would have an alternative approach for monitoring using python. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce monitoring and how we use currently at Opentable Inc. Describe limitations we have with our previous monitoring stack. Alternate new generation monitoring architecture using python tools Django and Celery, keeping sensu intact. How we developed a site using Django, which help us to maintain the checks and add new check definition. How we used Celery distribution system to run checks on multiple worker nodes and send results to sensu. I will talk about how we scaled celery worker nodes by setting up different queues, and prioritising the tasks and by using Flower.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic knowledge of Sensu. Basic knowledge of Django and Celery. Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-infrastructure-and-application-using-django-sensu-and-celery~e0o5d/", - "title": "Monitoring infrastructure and application using Django, Sensu and Celery." - }, - { - "Content URLs": "The Magenta Project Music Composition using Recurrent Neural Network", - "Description": "Music is mainly an artistic act of inspired creation and is unlike some of the traditional math problems. But, a sequence of specific chords and notes can be observed when we listen to music. With the recent advancements of the AI tech, sequence models are used invariably in innumerous fields, one such sequence model, LSTM( Long Short Term Memory Networks) can be used to generate melodies and beats. So, this talk is about how deep learning models, specifically LSTMs were used to produce music - catering particularly to the Electronic Dance Music Industry. CONTENTS AND ORDER OF THE TALK Learning how LSTMs help in generating music, and the concepts behind it. Preprocessing the MIDI data for the melodies and beats using MIDI packages created by the Python community. Building the LSTM network using Keras with Tensorflow as backend and understanding it. Train the network with the melodical data to create the LSTM network for melodies and same thing for beats. Generating melodies and beats(using pretrained model) and combining the two to create different type of genres of music. I am including a piece of music generated by an MIT alumnus, but I will be explaining the steps from scratch . Generated Techno Beat", - "Last Updated": "30 May, 2018", - "Prerequisites": "Tensorflow, Keras, Recurrent Networks and a Good taste in music ;", - "Section": "Others", - "Speaker Info": "I am Kumar Abhijeet, a sophomore from RV College of Engineering, Bengaluru and an AI enthusiast. I am a budding EDM producer and a python programmer as well(no doubt in that). I have worked with small AI startups in building their frameworks. I am an open source contributor and a GSOC aspirant. I have always loved the idea of mixing technology with regular phenomena, which I will be doing with music. I love going to meetups and meet different kinds of communities to learn from them", - "Speaker Links": "LinkedIn ID Github Lin", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kumar Abhijeet (~kumar80)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-beats-and-melodies-with-lstms-using-python-and-tensorflow~ejgya/", - "title": "Generating beats and melodies with LSTMs using Python and Tensorflow" - }, - { - "Content URLs": "https://github.com/radhikascs/cryptography-pytho", - "Description": "This talk is meant for the end users who aspire to learn basics of cryptography and its implementation in real world projects. \nThis tutorial is also useful for networking professionals as well as hackers who want to implement new frameworks instead of following traditional approach", - "Last Updated": "31 May, 2018", - "Prerequisites": "It is expected that the end user should know basics of cryptography and algorithms. The knowledge of cryptography algorithms becomes a cakewalk for a user who reads this tutorial", - "Section": "Core python and Standard library", - "Speaker Info": "A pinch of optimism with a blend of hard work and focus defines Radhika Subramanian. She works as an Academic Writer and Tutor with various organizations. She has completed MSc(CA) from Symbiosis International University. She also includes a passion for research work in Artificial Neural networks and it's technologies. She is currently working as an Author with BPB Publications and Apress Media LLC", - "Speaker Links": "https://www.linkedin.com/in/radhika-subramanian-486a771a/ https://www.unanth.com/tutor/radhika-subramanian-14135", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Radhika Subramanian (~radhika14)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cryptography-and-python~elkjd/", - "title": "Cryptography and Python" - }, - { - "Content URLs": "Slides: https://docs.google.com/presentation/d/1z-pWhSOERi-vl_wPLVsdCNpl54G3IA0D8K7ve13HFZI/htmlpresent Source code for the examples: https://github.com/minhajuddin/collaborative-canvas-demo", - "Description": "Outline/structure of the Session\n1. An introduction to Elixir\n2. An introduction to Phoenix\n3. Outline and design overview of our canvas app\n4. Implementing our app\n5. Deploying it to a server\n6. Q&A Learning Outcome\nLearn how easy it is to use Elixir and Phoenix to create real time applications at a massive scale", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic understanding of the web applications", - "Section": "Web development", - "Speaker Info": "I am a very passionate programmer. I am also the CEO of a Micro ISV, Cosmicvent Software. I have been in the software industry for 10 years.I love writing code and have worked with Elixir, Golang, Ruby, .NET and Javascript among other technologies", - "Speaker Links": "Follow me on twitter https://twitter.com/minhajuddin Follow me on GitHub https://github.com/minhajuddin/ My Blog: https://minhajuddin.com/ Previous presentation: https://www.youtube.com/watch?v=WabGxSZhPE", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Khaja Minhajuddin (~minhajuddin)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-collaborative-canvas-using-elixir-and-phoenix~enl5b/", - "title": "Building a collaborative canvas using Elixir and Phoenix" - }, - { - "Content URLs": "To get a feel of Numba see - first step", - "Description": "Thinking parallel is an art, applying it is another. While applying it, the first hurdle for us is to move to another language like C or C++ to get performance gains. \nWhat if we write simple python code and someone magically helps us gain C like performance? Sounds like a dream, it ain't ! . Enter Numba :) In this workshop you will - Witness how Numba help you get insane performance gains to your code without changing a line of it. Learn to harness the power of your GPU/CPU for performing math intensive computations. See how it compares to other libraries like Numpy , etc. and how they can complement it. Use Numba to parallelize the very famous Particle Swarm Optimization Algorithm Flow of the workshop - Where to use Numba in your code - (time profiling, small examples) The wow of Numba in my life, a small example of how it helped in my research Introduction to jit complier, internals of Numba Introduction to the Particle Swarm Optimization (this is where the fun starts :) ) Code up basic PSO Profile PSO to find pain areas Try to speed up the pain areas using Numba Kick up a hierarchical swarm (just for fun, if time permits) QA Session", - "Last Updated": "31 May, 2018", - "Prerequisites": "numpy, matplotlib, jupyter, ipython, numba, line_profiler , llvmlite. A more specific description is available her", - "Section": "Others", - "Speaker Info": "Hi, I am Shubham Bhardwaj. I am currently a Research Intern at Jio CoE for AI/ML and a final year undergrad at VIT University, Vellore. I am a die-hard pythonista. \nMy daily work involves developing and implementing algorithms for interesting problems in AI. Apart from this I am also an organizer at GDGVIT, I love dev :) and contribute to various open source organisations, organise workshops, promote python whenever I can", - "Speaker Links": " LinkedIn Github", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Shubham Bhardwaj (~shubham0704)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/leveraging-the-power-of-your-gpucpu-for-math-intensive-computations-with-python~bkjJa/", - "title": "Leveraging the power of your GPU/CPU for math intensive computations with python" - }, - { - "Content URLs": " Postman Jmeter Burp", - "Description": "API testing is fun! For a small team of 7 (Dev + QA), having dedicated resources to do functional, Security and Performance of the APIs is close to impossible.\nHence, We came up with a framework which automates the process of API testing covering the basic functionality, Security, and Performance so that we don't miss out testing any of these layers. I would cover up the basics of Postman, Burp and JMeter components used for the framework", - "Last Updated": "31 May, 2018", - "Prerequisites": " Interest in automating the Webservices testing :)", - "Section": "Developer tools and Automation", - "Speaker Info": "A tech enthusiast who has 7+ years of experience in the Software Testing in Startups. I love to explore new technologies and automate mostly everything which takes more time. A strong believer in processes. Love testing Webservices. Would love to share the experience we had in building the framework for API testing", - "Speaker Links": "https://www.linkedin.com/in/sarala-v-620b0b1a/ https://twitter.com/saralaVeerann", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sarala V (~sarala)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-rest-api-testing-for-functional-security-and-performance-testing~bmkRe/", - "title": "Automating REST API testing for functional, security and performance testing" - }, - { - "Content URLs": "https://www.py4e.com/\nhttps://www.coursera.org/specializations/pytho", - "Description": "This session will take a look at the \u201cPython for Everybody\u201d series of courses on the Coursera platform. This course has impacted over 1.3 million students over the last five years. We will look a the history and goals of the course and how the course works to create a learning community. We will show how the free open educational resources (OERs) and book associated with the course have been used by teachers, students, and courses around the world to form a network of educational activities centered around Python. We will also cover briefly the Tsugi (www.tsugi.org) software that is used to build the learning assessments and distribute the OER materials in a way that enables maximum reusability of the materials for other teachers", - "Last Updated": "31 May, 2018", - "Prerequisites": "No pre-requisite", - "Section": "Core python and Standard library", - "Speaker Info": "http://www.dr-chuck.com/\nhttps://www.si.umich.edu/people/charles-severance\nhttps://twitter.com/drchuck/\nhttps://github.com/csev\nhttps://www.sakaiproject.org\nhttps://www.tsugi.org\nhttps://www.slideshare.net/cse", - "Speaker Links": "http://www.dr-chuck.com/dr-chuck/resume/index.htm Charles is a Clinical Professor and teaches in the School of Information at the University of Michigan. He is the Chair of the Sakai Project Magament Committee (PMC). Previously he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project and worked with the IMS Global Learning Consortium promoting and developing standards for teaching and learning technology. Charles teaches ten popular MOOCs and two specializations to students worldwide on the Coursera platform: Internet History, Technology, and Security, Web Applications for Everybody, and Python for Everybody and is a long-time advocate of open educational resources to empower teachers. Charles was the editor of the Computing Conversations column in IEEE Computer magazine from 2011-2017 that features a monthly article and video interview of a computing pioneer. Charles is the author of several books including: Python for Everybody, Sakai: Building an Open Source Community\", \"Using Google App Engine\", from O'Reilly and Associates and the O'Reilly book titled, \"High Performance Computing\". Charles has a background in standards including serving as the vice-chair for the IEEE Posix P1003 standards effort and edited the Standards Column in IEEE Computer Magazine from 1995-1999. Charles is active in media as a hobby, he has co-hosted several television shows including \"Nothin but Net\" produced by MediaOne and a nationally televised program about the Internet called \"Internet:TCI\". Charles appeared for over 10 years as an expert on Internet and Technology as a co-host of a live call-in radio program on the local Public Radio affiliate (www.wkar.org). Chuck's hobbies include off-road motorcycle riding, karaoke and playing hockey. Charles has a B.S., M.S., and Ph.D. in Computer Science from Michigan State University", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Charles Severance (~charles)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/inside-the-worlds-largest-python-course-on-coursera~bomYe/", - "title": "Inside the World's Largest Python Course on Coursera" - }, - { - "Content URLs": "---In progress, will be ready to share by July last week can make it to July first week if urgent--", - "Description": "Signal processing is a fundamental part of ECE and is also used in many other fields. Students for years have been using expensive Matlab for learning this skill. The talk/workshop/interactive session can be used by students to get a better understanding of signal processing and implementing it with python. The use of python language in signal processing is preferred as it is portable, easily available and fast to deploy Topics covered include but are not limited to Sound and Signals Noise Fourier Transform Filtering Modulation Sampling LTI Systems The talk will be at a simple level so that even a high school student can understand signal processing and implement it. If time allows another session on using python to solve electrical networks and visualizing them can also be implemented", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic knowledge of python and Signals and systems (WikiPedia knowledge is enough.) NumPy (Used for array manipulation ) SciPy (For computation) matplotlib (For plotting various signals etc.)", - "Section": "Others", - "Speaker Info": " Speaker is a 3rd year ECE student with experience in python for numerical computations, web development and most importantly signal processing , and electrical networks Interested in using python in modern electronics like the pyboard and raspberry pi and advocates the use of python over expensive software. An avid python user, always tries to find a way to implement given task in python and believes that where there is a task to be done there is a suitable python library.", - "Speaker Links": "LinkedIn Faceboo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Abel Joseph John (~abel91)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/digital-signal-processing-with-python-and-applications-in-audio~epnQb/", - "title": "Digital Signal Processing with Python and Applications in Audio" - }, - { - "Content URLs": "https://github.com/vivekaris/firebase-io", - "Description": "Now Days Internet of Things are Trending technology for every makers. Lets Build Python based Automation controller for any Hardware (tested on Raspberry Pi and Node MCU).\nWe will use firebase as a data storage and Action handling.\nWith the help of Firebase Realtime Database ,we can control hardware from any geographical location", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Keen to learn Basic of Python Knowledge of PIP Knowledge JSON Basic Knowledge of C for Arduino(Node MCU Programming) Laptop with Linux/Mac/Win 7 onwards. Node MCU v3 2 LED with 4 Jumper Wire Internet Connectivity Google Account enter code her", - "Section": "Web development", - "Speaker Info": "I am opensource tech lover", - "Speaker Links": " https://github.com/vivekaris https://twitter.com/vivdroid http://makerspacekanpur.com/blog/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-firebase-build-amazing-iot-application~erp2b/", - "title": "\"Python and Firebase\" Build Amazing IoT Application" - }, - { - "Content URLs": "Kubernetes Docker Azure Kubernetes Service aka AK", - "Description": "Kubernetes is considered as the new Kernel of the Cloud. It's a distributed computing platform letting users not have to care about infra and helping them concentrate mainly on business logic. By having your web app deployed on a kubernetes cluster you can make sure your app is highly available, and can fail-over when there's a problem. One of the main goals of the Kubernetes project is to democratize distributed computing. With Kubernetes being open source, Companies do not have to redo the mundane task of writing a distributed computing platform to achieve high availability, automated deployment, scaling and management of your applications. Kuberentes will take care of that for you. Kubernetes is also considered as a container orchestrator, as it manages containers to achieve the above said goals. In this talk: We will first write a basic python web app. Next, We will go through what a container is Containers are becoming the de-facto way of deploying applications as they remove the complexities of dependency management,etc. Running apps on Individual Containers provide the isolation almost to that of a Virtual Machine without having the overhead of having individual Kernels as they all share the host kernel. Isolation is provided by using kernel level features like cgroups and namespaces. We will containerize the application using docker and push it to a Container Registry. Once we have the image deployed to a registry, this image will be used to create instances i.e containers of the web app. We will next create a kubernetes cluster on Azure, all along going through what a Kubernetes cluster is, and its components. We will then deploy our python web app onto the cluster. Now As we have our python web app up and running, We can then do some experiments on how Kubernetes self-heals the application when a node goes down,etc. After that I will run down some points on where Kubernetes is being\n used, its impact. To Finally answer the question, Is Containers and Kubernetes worth all the Hype ? This talk will be demo focused, But before going to a demo we will have some slides explaining the overview of the components and how they work. By the end of the talk, Audience will have a brief overview of what containers and kubernetes are, and how to deploy a web app on Kubernetes. From this overview, Audience can start digging deeper online and know more", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Understanding of Python. Basic Understanding of Deployment of a web app. It's good if you already have some basic understanding on what containers and kubernetes are", - "Section": "Developer tools and Automation", - "Speaker Info": "Tarun Pothulapati is currently pursuing his B.Tech in Computer Science and Engineering in Hyderabad.\nHe is a Tech Enthusiast and codes mostly in Python and C#. He is very much interested in distributed computing platforms like Kubernetes and Microsoft's Service Fabric which are trying to democratize \nthe technology which was before only a privilege of the Big-Tech firms.\nHe spends most of the time learning about it and trying to contribute to their repositories. He is also very enthusiastic about sharing the knowledge about these cutting edge technologies.\nTarun has also worked on many projects on chatbots, Web apps etc and have won some\nhackathons held by IEEE, IBM & Amazon and he was one of India's 40 finalists of AICTE's \nStartup Contest 2017", - "Speaker Links": "Twitter Github Linkedin Websit", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Tarun Pothulapati (~Pothulapati)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deploying-a-python-web-app-onto-a-kubernetes-cluster~bqo7e/", - "title": "Deploying a Python web app onto a Kubernetes Cluster" - }, - { - "Content URLs": "share here soon", - "Description": "Flutter is Google\u2019s mobile app SDK for crafting high-quality native interfaces on iOS and Android in record time. So lets create web services for Flutter app using python/Flask framework", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Basic of Python Knowledge of Webservices REST and JSON Hello world Knowledge of Mobile App. Familiar with Android Studio and Pycharm", - "Section": "Web development", - "Speaker Info": "I am opensource lover. I love to explore opensource technologies for mankind. I am organiser of \"Arduino and IoT ,Kanpur\" . I teach kids under coderdojo program", - "Speaker Links": " https://twitter.com/vivdroid https://github.com/vivekaris", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/write-python-web-services-for-flutter-app~avw8b/", - "title": "Write Python Web services for Flutter App" - }, - { - "Content URLs": "Programs in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=", - "Description": "Mention of \u201cCancer\u201d evokes words like tumor, chemotherapy, hair loss, vomiting and pain. Interestingly our knowledge and thereby cancer treatment has changed radically in the past few years and is changing rapidly every passing day. In 2003, human genome was sequenced and for the first time we could read entire human DNA from end to end. Interestingly DNA and cancer are deeply connected. Scientists deciphered that always a change in DNA (mutation) led to cancer (oncogenic mutation). Cigarette smoking, alcohol, pollution etc only led to such DNA change (oncogenic mutations). This led to numerous diagnostic companies starting to extract and sequence tumor DNA, to detect the root cause of each patient tumor. While drug companies formulated new drugs that targeted specific DNA change (mutation). These were called targeted therapies which were very different from chemotherapy in being very precise, less toxic, less side effects and they could be taken orally just like any regular pill. Thus, an oncologist (cancer doctor) could treat a cancer tumor effectively if s/he knew the precise location of mutation in the entire patient tumor DNA and the drug that targeted it. Suddenly oncologists in India and elsewhere, found themselves struggling to comprehend tumor DNA and the technology around it. Already burdened with tomes of ever changing patient treatment guidelines, now they were needed to integrate tumor DNA information to make accurate treatment decisions. For eg. NCCN (National Comprehensive Cancer Network, USA) which publishes treatment guidelines for all cancer for oncologists across the world, published lung cancer guidelines that is 271 pages long. To this, add the complex data of patient\u2019s tumor DNA, various mutation databases, clinical trials and research papers. Modern day oncologist are often overwhelmed. They need tools to simplify and hasten their decision making. I am a molecular biologist who understands the tumor DNA and the technologies around it. As Chief Scientist (molecular oncology) of Neuberg diagnostic lab, I also write patient DNA reports that guide oncologists to take treatment decisions. While meeting various oncologists and marketing them different DNA tests for different type of cancers, I got acutely aware of the problems oncologists faced. To simplify their decision making, I created algorithms that combined patient\u2019s clinical history, histo-pathology data, molecular test decisions, mutational databases and NCCN guidelines. Subsequently I coded these integrated and complex decision algorithms as Python programs that can be executed from a browser. They are available for free and oncologists are/can use it.\nPrograms in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=0 \nMy article on need of Python programing for cancer treatment: https://sites.google.com/view/molecularpathology/programming/is-it-time-for-precision-medicine-app?authuser=", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Interest in using programing to resolve healthcare problems in India", - "Section": "Others", - "Speaker Info": "I am a PhD in Biochemistry with significant research experience at the University of North Carolina at Chapel Hill, in the areas of molecular oncology, cardiovascular biology and biology of infectious diseases. Currently, I prepare molecular diagnostic reports for cancer patients as Chief Scientist (Molecular Oncology), Neuberg Center of Genomic Medicine, Ahmedabad", - "Speaker Links": " Molecular pathology of cancer: https://sites.google.com/view/molecularpathology/home?authuser=0 The DNA Labs: https://sites.google.com/site/thednalab/ , https://www.facebook.com/TheDNALab , https://www.youtube.com/channel/UCf2HKt1vgjhe8MXbvMSwELg/feed", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "siddharth srivastava (~siddharth40)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/helping-oncologists-to-take-complex-decisions-in-treating-cancer~axylb/", - "title": "Helping oncologists to take complex decisions in treating cancer." - }, - { - "Content URLs": " Initial version of slides (will update regularly and mark it complete once done)", - "Description": "Abstract Being one of the most used collaboration tools used by software engineers and data scientists, \"Jupyter Notebooks\" are transforming the way \"data science\" is happening in the industry. Started as a smart Python interpreter, the Jupyter project has grown into a common platform that supports the development of data science and scientific computing tools across multiple programming languages. This talk is aimed at understanding the technical internals of Jupyter project. Agenda A brief introduction to Jupyter How is it different from IPython Component architecture Kernel Frontend Communication protocol used between a frontend and kernel How does a kernel work Magic commands How to create one Let's create a Jupyter frontend Wait! What if you can use Slack as a Jupyter notebook? Jupyter, Interactive computing, and possibilities What will you learn Process that powers an interactive Jupyter session Do you know how does the tab-completion work? Extending the capabilities offered by Jupyter ecosystem for a custom use-case We will learn how to create magic commands and frontend Black magic", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Basic understanding of Python, comfortable with functions/classes Experience working with Jupyter/IPython notebooks (Optional) Interested in knowing how stuff works", - "Section": "Data science", - "Speaker Info": " Tech & Product at Vernacular.ai Data-driven journalism practitioner Featured in Tech in Asia and Global Investigative Journalism Network Contributor to Go programming language", - "Speaker Links": " Website GitHub Twitter", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pravendra Singh (~pravj)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyter-notebooks-internals-and-extension~dyz6e/", - "title": "Jupyter Notebooks: Internals and Extension" - }, - { - "Description": "The goal of this talk is to explain this quote : \u201cYou shall know a \u2018word\u2019 by the company it keeps!\u201d In this talk, we will go through as to how to build a model for text summarisation (from scratch) and its possible applications in the real world scenario. An intuitive explanation will be provided (the talk would not be all mathematical!) as to how to do the data preprocessing for a large dataset and provide a reasoning as to why we choose a specific model for training. We will also talk about how certain Python libraries make it easier to structure a machine learning pipeline. We will also walk through the best practices and various caveats while building these kinds of complex models and how to circumvent these", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "The prospective audience should have a basic understanding of neural networks and natural language processing", - "Section": "Data science", - "Speaker Info": "Harshdeep is currently a student at the University of Manchester pursuing his Bachelors in Artificial Intelligence and is interested in Natural Language Processing. My experience with Python started at IBM Bristol where I worked for a year developing the compliance automation tool. After that, I worked on my final year research project using Python which was based on finding summaries and sentiment of news articles. I have previously spoken at PyCon APAC in Malaysia last year in August which was a talk about the basics of Neural Networks. After university, I will be working with some early stage startups in India related to AI and Aviation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harshdeep Harshdeep (~harshdeep)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/text-summarisation-made-fun~azAqe/", - "title": "Text summarisation made fun!" - }, - { - "Content URLs": "Slides will be updated soon. Django2 release note", - "Description": "Django is one of the most used Python framework in the world of Python and is even used more than Tensorflow(Stack Overflow 2018 Developer Survey). Django is an excellent web-application framework to build scalable, extensible and high-performance web applications that can serve hundreds of thousands of requests per second -- while keeping the development cycle optimal and maintaining the sanity of developer mind-space. The latest version of Django 2.0 has been just released this year. The new Django 2.0 begins a new era without any backward incompatible changes except the removal of Python2.7 in the latest version and it aims to completely remove Python2 support for Django environment when LTS Django 1.11 expires in 2020 with Python2 . This release also starts the Django using the loose form of semantic versioning. Django 2 has introduced a lot of major changes like : SImplified URL routing syntax Performance optimisation and improvements Mobile Friendly Admin site Newer functions like Windows and more modified aggregate functions\n-Stricter schema Made Mysql isolation as read committed Talk Outlines What is Django and why use Django? Django design patterns - MTV kind of MVC How does Django work? Simplified URL routing syntax in Django2 Other new features in Django2 When should you move your old project to Django2 and Django release Cycle Tips on converting your legacy code to Django2 This talk aims to provide some general insights on Django and latest Django2 version. Apart from being a talk focussed exclusively on Django, the talk aims to give an introduction to what server-side programming is and in general to Web Development", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Python Django (preferable) After all, this is a Hitchhiker\u2019s guide, this talk will focus on a general introduction to Django and don\u2019t be afraid all the noobs in Python and Django will be welcomed and be accommodated in this tal", - "Section": "Web development", - "Speaker Info": "Kurian is currently in his sophomore year, pursuing an undergraduate degree in Computer Science from Govt. Model Engineering College, Kochi. He has interned in multiple startups like Entri.me, WiM as a product intern developing products using Python and web frameworks like Django. He is also a Open source Enthusiast and have contributed to multiple organisation like Zulip , FOSS Asia. He is an active member of FOSS club in his college(FOSSMEC) and of Kochi Python Club(Python Meetup Group of Kerala)", - "Speaker Links": "Github LinkedIn Medium Twitte", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kurian Benoy (~kurianbenoy)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-hitchhikers-guide-to-django-2~aAr9b/", - "title": "The Hitchhiker\u2019s Guide to Django 2" - }, - { - "Content URLs": "We will share the Github repository for the workshop here couple of weeks before the conference", - "Description": "\"Our Business Is Our Business None Of Your Business\u2026\" Yes, they wish, but we want to know everything about Bollywood! Who is more popular, Katrina Kaif or Deepika Padukone ? Do you think you look like a Bollywood celebrity? Does deep learning thinks the same? :) What movie is the most similar to PK based on the storyline? Which city in India is home of the most active actresses and actors? And lots of other questions. Do you want to know the answers? And even better, would you like to discover them yourself by using Python and popular libraries such as pandas, Gensim, scikit-learn and pytorch? And cutting-edge data science techniques? Join us for a workshop full of insights where you will be able to answer your own questions while learning the most advanced Python libraries and algorithms. The workshop is designed for Python programmers new to data science. Everybody is welcome, but data analysts and people experienced with pandas will find some parts basic. What will we cover? Loading, merging, cleaning and analysing your data with pandas Advanced data visualisation with Bokeh Embeddings and natural language processing with Gensim Basic machine learning with scikit-learn Deep learning building a face extractor and a classifier with pytorch All this while answering the questions above, and letting you answer your own questions", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Laptop with Anaconda3 installed Clone of the workshop repository Knowledge of Python Good knowledge of Bollywood desirable :)", - "Section": "Data science", - "Speaker Info": "Simmi Mourya is a researcher at IIIT Delhi in collaboration with All India Institute of Medical Sciences. Her work involves developing end to end deep learning pipelines for Multiple Myeloma detection from histopathology images. Simmi is a regular speaker at Python conferences, including PyCon India and Europython, and other conferences like Fossasia Open Technology Summit. She is also a regular open source contributor, including as a Google Summer of Code Student. She is a huge Irrfan Khan fan. Himanshu Awasthi is the organiser of Kanpur Python and PyData Kanpur. Free and open source software enthusiast, and passionate about Python and data analysis, He is currently working for KanpurFOSS organization which organize free technical workshops in India. Yai Workshop\u2026 Data Analysis Ke Workshop Hai\u2026 Kisi Ke Data Analysis sikha kar He Khatam Hoge... Marc Garcia is a pandas core developer. He has worked as software engineer and data scientist for companies like Bank of America, Tesco, Unilever or NTT Communications. He is a regular organiser of sprints, and speaker at PyCon and PyData conferences. His favourite actor is Aamir Khan, but wouldn't mind teaching Python to Asin", - "Speaker Links": "Simmi : https://twitter.com/simmimourya | https://github.com/simmimourya1 | https://www.linkedin.com/in/simmi-mourya-34406886/ Himanshu : https://twitter.com/IHackPY | https://www.slideshare.net/HimanshuAwasthi14/ | https://speakerdeck.com/johim9493 Marc : https://twitter.com/datapythonista | https://www.linkedin.com/in/datapythonista/ | http://datapythonista.github.io", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Marc Garcia (~marc)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decoding-bollywood-with-python-data-science-and-deep-learning~eEyWe/", - "title": "Decoding Bollywood with Python, data science and deep learning" - }, - { - "Description": "With the advent of Tableau and languages like Python and R, converting raw data into meaningful insights is much easier and convenient than before. Tableau is a tool used to visually represent data and is powerful enough to analyze the given data at any required level. At an industry perspective, the tool comes handy in finding the trends in marketing and sales with a click of a button. Introducing Python to Tableau using TabPy can help define calculated fields in Python, thereby giving it the power to leverage a large number of Machine-learning libraries right from the visualizations. This widens the scope of its applications to any field that deals with big data and its analytics. Optimisation and cross-sharing of data models facilitated by TabPy immensely enhance the efficiency and usability of the tool. With just a few lines of code, we can churn out predictive models and increase the accuracy of future predictions. The talk will primarily focus on: An introduction to data manipulation and visualization using Tableau. An overview of the steps to leverage TabPy in Tableau. The impact and advantages of Tableau-TabPy combination in the real world.", - "Last Updated": "03 Jun, 2018", - "Prerequisites": "A rudimentary understanding of Data Science and Python scripting", - "Section": "Data science", - "Speaker Info": "I am a sophomore undergrad in computer science from Amrita School of Engineering, India of which I am a part of an intra-college FOSS initiative called FOSS@Amrita. Developing small but useful things that improve lives of the common and affects the open-source community has always been my passion. I believe that with the right technology applied, it can do wonders for the lives of people. Furthermore, I have completed the Google Summer of Code\u201917 with The Wikimedia Foundation and was also a Google Code-In mentor for the same community. Worked on the project that aimed at the improvement and enhancement of the ProofreadPage Extension and Wikisource , through important bug fixes that are left as backlog and implementation of significant features that would make it more user-friendly. This was done so that the extension and Wikisource become easier to use and are raised to the contemporary Mediawiki standards. Apart from this, I'd love to \u200bexpress\u200b \u200bviews\u200b on\u200b \u200bcontemporary\u200b \u200bworld issues,\u200b \u200bget\u200b to know\u200b \u200bthe\u200b \u200bdifferent dimensions\u200b of\u200b \u200bit and analyze the\u200b \u200bmultiple\u200b\u200b ways\u200b \u200bin\u200b\u200b which\u200b \u200bthe\u200b \u200bproblems\u200b \u200bcould be rectified", - "Speaker Links": "Linkedin Blog Gerrit GitHu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Amrit Sreekumar (~amrit95)", - "created_on": "03 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-leveraging-python-in-tableau~dGAKa/", - "title": "Data Analysis: Leveraging Python in Tableau" - }, - { - "Content URLs": "Brief content is here: https://github.com/yashug/Pandas Actual workshop will cover more inf", - "Description": "The Goal of this workshop is to make you more fluent at pandas to answer data science questions. Python has long been great for data munging and preparation, but less so for data analysis and modelling. pandas help fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R", - "Last Updated": "04 Jun, 2018", - "Prerequisites": " Laptop with Anaconda installed Basics of Python", - "Section": "Data science", - "Speaker Info": "Yaswanth is a Senior Software Engineer, currently working in ZeMoSo Technologies and Graduated from IIT Guwahati. Free and open source software enthusiast, and passionate about Python and Machine Learning", - "Speaker Links": "Linkedin | Githu", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Gosula Yaswanth (~yashug)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-pandas-for-better-data-science~aKGGa/", - "title": "Using Pandas for Better Data Science" - }, - { - "Description": "The Jupyter ecosystem of tools lets you interleave code and stories for a literate computing experience, where you can visualize your data as html, plain text, svg and images. You could also view the same rich displays in multiple environments - on the web, on your desktop, in your shell or even your IDE . But how is this possible without duplicating logic, re-inventing the wheel multiple times? How do visualization libraries like Bokeh, Plotly work across frontends - like jupyter notebook, jupyterlab and nteract? This talk explores Jupyter's display system and how it handles multiple display formats in multiple environments. We will see how this idea is applied in some open visualization libraries. After this talk, you will know how to integrate your python objects better with the notebook. You will also get an idea of how to create a visualization library that works across the Jupyter ecosystem of tools. Duration 45 mins (Content can be modified to fit into 30-minute slot too) Outline - Setting some terminology for the rest of the talk (what is a frontend, kernel, displayhooks) (5 mins) - How to use Jupyter's display hooks for your python objects with the notebook (10 mins) - The Jupyter messaging protocol - specifically, the display_data and update_data messages (5 mins) - Custom mime-types (and this is the secret to Jupyter's display system!) - separating what to display from how to display it (10 mins) - Examples of custom mime-types in the wild (a look at altair , vdom , plotly and more) (10 mins) Additional notes This proposal might seem to overlap with another - Jupyter Notebooks: Internals and Extension - which explores how jupyter works under the hood and how to create alternative frontends. My talk's focus will be different, and will dive into a very specific part of Jupyter - the display system - in depth", - "Last Updated": "04 Jun, 2018", - "Prerequisites": "Some experience using either the jupyter notebook or jupyterlab ", - "Section": "Others", - "Speaker Info": "I am a software developer at D.E.Shaw, Hyderabad. I've occasionally contributed to projects in the jupyter ecosystem - the notebook, ipywidgets, hydrogen, nteract", - "Speaker Links": "Github Twitte", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Madhumitha psg (~madhumitha)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyters-rich-display-system~dJ1Kb/", - "title": "Jupyter's Rich Display System" - }, - { - "Description": "Considering the fact that businesses these days make a lot of money by recommending customers the things that match their likes, knowing how to build a Recommendation System would be of great use to many aspiring Deep Learning enthusiasts. This workshop is all about understanding and implementing Auto-Encoders. Auto-Encoders are the Unsupervised Deep Learning Models which are widely used for Dimensionality Reduction and Feature Discovery. New types of Auto-Encoders have enabled us to build very nice Recommendation Systems. The talk will focus on understanding Auto-Encoders, their types, and building a Recommender System that Predicts Rating (1 - 5) using PyTorch. The flow of the workshop will be as follows: Self Introduction Introduction to Unsupervised Deep Learning Diving DEEP into Auto-Encoders (Theory, Architecture, and Working) Introduction to Sparse Auto-Encoders Introduction to Denoising Auto-Encoders Introduction to Contractive Auto-Encoders Introduction to Stacked Auto-Encoders Understanding the Deep Auto-Encoders Training Auto-Encoders Building a Recommender System that Predicts Ratings (1 - 5) Understanding the Problem of Overcomplete Hidden Layers End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras, TensorFlow, or PyTorch will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-auto-encoders-using-python~aOGRa/", - "title": "Understanding and Implementing Auto-Encoders Using Python" - }, - { - "Content URLs": "Will share the code, slides, and resources as a GitHub repository after the talk", - "Description": "Automatic Visual Speech Recognition comes very handily in scenarios that have noisy audio signals. A video image of a person talking is analyzed and shapes made by the lips are examined which are then turned into sounds by comparing to a dictionary to create matches to the words being spoken. In this talk, we will use a VGG+GRU network which is based on CNN+LSTM layers to predict the text spoken by the speaker and classify it into 20 classes from audio-less videos, consisting of 10 words and 10 phrases. This will be done on the audiovisual MIRACL-VC1 dataset. The talk will cover how a CNN+LSTM can be used to recognize a sequence of shapes formed by the mouth and then match it to a specific word or sequence of words spoken from Visual Feed. It will include data-preprocessing, creation of CNN and LSTM layers using Python and applying them on the dataset", - "Last Updated": "06 Jun, 2018", - "Prerequisites": "Basics of Python Syntax, Tensorflow, Keras, Neural Network", - "Section": "Data science", - "Speaker Info": "Kanika Modi holds a Bachelor's in Computer Engineering from Netaji Subhas Institute of Technology, University of Delhi. Having finished her coursework, she will join Amazon as a Software Development Engineer(SDE). She is an open source enthusiast and has contributed to organizations such as Systers, Fossasia, etc. She is also a Google Summer of Code'18 mentor at Systers, a GirlScript Summer of Code'18 mentor and mentor at RightApprise. Her interests also extend to the fields of artificial intelligence and machine learning. She prefers Python as her weapon of choice", - "Speaker Links": "Link to LinkedIn Link to GitHub Link to Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "kanika_96", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-lip-reading-system-to-recognise-visual-speech-using-python~dNG2e/", - "title": "Building A Lip Reading System To Recognise Visual Speech Using Python" - }, - { - "Content URLs": "PyCon India 201", - "Description": "What's a good way to Set up many development version(s) ? Developers need consistent isolated development environment, running exact same container(s) as what runs in production , automated test tools, package, ship & deliver. Let's touch features of docker to make it run for Python programs/web apps. Outlines First 5 minutes, I'll be talking about current developers need and present solution. Next 5 minutes, what is docker and how it can solve these problems. Next 10 minutes, I'll be demonstrating, how I use docker for in my Python development tasks (Python library, Python web app). After 20 minutes I will have delivered the enough knowledge for the docker, and next 5 minutes I will let the audience know about the some advance features in docker that they can learn from various resources, to get the maximum power of docker. Q/A along with this. Detail description Basic terms of docker Docker Container Docker Image Dockerfile Docker Compose Docker Repository and Docker Hub Docker Daemon, Docker Client and Docker Engine Docker Swarm Docker Machine Docker for Developers Reproducibility and Developer teams Isolation Security Environment Management Continuous Integration Creating Custom Images and Containerizing Your Application Sample Dockerfile to build an image of an small python program. We will run the image and play with this container. Using Docker Compose in development adds an important constraint: your services are not on the same machine anymore. Container Logs Learn how you can see or capture the logs of the container(s) and services. Docker for Python developers In this section I will demonstrate, how you can setup a development version of real world software.\nI will setup the development version. After creating an image and running it in a container, I will show volume sharing techniques as well. Audience will understand how I have created an consistent isolated container, integrated CI which is easy and fast to ship. Docker for Python Web applications Django and Flask web app will be run under the docker container, different environments in one system. We will learn how to use microservices and advantages of making services using docker-compose. Advance and new features of docker Now audience have understood the docker and they can learn many more powerful features of docker. I will share some good resources and let them know about docker swarm, docker machine, Dealing with Logs, etc ", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "Prior experience with docker is not a necessity but having some exposure to Python development, version control system, Unix System is recommended. At the starting talk basic developers need, basic docker features will be covered. So starting point, anyone (entry/intermediate) can understand the docker concepts. Slowly moving to docker for developers, expert Python developers will get ideas to use docker in their development system and how they can solve most of the development conflicts because of using having multiple environments", - "Section": "Developer tools and Automation", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/containerizing-your-application-is-the-solution~dBvQd/", - "title": "Containerizing Your Application is the solution" - }, - { - "Content URLs": "I delivered a talk on Recurrent Neural Networks at GeoPython 2018, Switzerland. The proposed talk will be enhanced version of my previous talk. This time, I will be covering more topics to make it a more detailed talk.\nLink to my previous talk: https://github.com/greatdevaks/GeoPython_Basel_201", - "Description": "Recurrent Neural Networks (RNNs) have become famous over time due to their property of retaining internal memory. These neural nets are widely used in recognizing patterns in sequences of data, like numerical timer series data, images, handwritten text, spoken words, genome sequences, and much more. Since these nets possess memory, there is a certain analogy that we can make to the human brain in order to learn how RNNs work. RNNs can be thought of as a network of neurons with feedback connections, unlike feedforward connections which exist in other types of Artificial Neural Networks. The flow of the talk will be as follows: Self Introduction Introduction to Deep Learning Artificial Neural Networks (ANNs) Diving DEEP into Recurrent Neural Networks (RNNs) Comparing Feedforward Networks with Feedback Networks Quick walkthrough: Implementing RNNs using Python (Keras) Understanding Backpropagation Through Time (BPTT) and Vanishing Gradient Problem Towards more sophisticated RNNs: Gated Recurrent Units (GRUs)/Long Short-Term Memory (LSTMs) End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras or TensorFlow will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-recurrent-neural-networks-using-python~dPGAb/", - "title": "Understanding and Implementing Recurrent Neural Networks using Python" - }, - { - "Description": "In Data Science, Garbage In = Garbage Out. Feature engineering is one of most of the important yet most neglected step in life cycle of Machine learning projects. Kaggle competitions have showed us that top Kagglers spend more than half of their time in feature engineering. Through various experiments, its also proved again & again that better features with simple model triumphs even advance models. In this talk I am planning to discuss basic as well advance feature engineering techniques which can be used by everyone in their projects Outline What is Feature Engineering ? Techniques for Numerical Variables Techniques for Categorical Variables Techniques for Textual data Advance techniques Feature Selection & Dimensionality reduction QA", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic knowledge of Python & Machine learning", - "Section": "Data science", - "Speaker Info": " Sudarshan Gadhave is a Data Science ,Data Engineering & Data\n Integration professional with over 8 years of experience working on\n Machine Learning , Data Engineering , Data Visualization and Data\n Warehousing Projects. Currently he is working as a Specialist Data Scientist in Analytics R&D team of\n Nice Actimize ( Nice Systems) working on developing Anomaly & Fraud detection models. Earlier experience of working in Advance Analytics & Data Warehousing\n teams of NEC, Japan & John Deere (Deere & Company). Pythonista & expert in Python Machine learning stack (Numpy,Pandas,\n Scikit-Learn, Matplotlib) Active & Core member of Python Pune meetup group.Presented several\n talks on Python & machine learning in meetups, conferences and\n colleges all over Pune.", - "Speaker Links": " Github:- https://github.com/sudarshan1413 Linkedin:- https://www.linkedin.com/in/sudarshan-gadhave-73567b23/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "sudarshan1413", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/art-of-feature-engineering-for-machine-learning~eVWza/", - "title": "Art of Feature Engineering for Machine Learning" - }, - { - "Description": "Data Wrangling involves detection, correction, removal, or otherwise dealing with inaccurate and corrupted data. The most common file formats in which data can be stored are CSV, JSON, and XML. However, many times, the data is not available in the desired format and rather is available in some unconventional file formats like PDF or PPT. Parsing PDFs may seem like a daunting task to many as it is quite an unpredictable format. Simply stated, PDF is a hard-to-parse format. This workshop will help you understand the concept of Wrangling PDFs in an easy and fun way. Following will be the flow of this workshop: Self Introduction Brief Introduction to Data Wrangling Why prefer CSV, JSON, or XML? Why avoid using PDFs? Basics of RegEx based Pattern Matching Parsing PDFs Programmatically using \"slate\" and \"pdfminer\": Getting hands-on Inefficient Parsing? Consider Data Cleaning Exploring PDF Wrangling with \"pdftables\" Where to go from here? Question and Answers Session The End :) Key Takeaways: Gain confidence in Data Wrangling using Python. Get familiar with the daunting PDF Parsing task. Get hands-on with popular PDF Wrangling libraries in Python: \"slate\", \"pdfminer\", and \"pdftables\". Understand the concept and importance of Data Cleaning.", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Basic knowledge of programming in Python language. Familiarity with wrangling CSV, JSON, or XML files will be good but is not necessary.", - "Section": "Core python and Standard library", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/wrangling-unconventional-file-formats-with-python-playing-with-pdfs~aQXGe/", - "title": "Wrangling Unconventional File Formats with Python: Playing with PDFs" - }, - { - "Content URLs": "A few topics I will be covering, I would not be covering everything in detail, but hope to highlight important aspects from these links over the talk session: http://openmusictheory.com/ https://in-thread.sonic-pi.net/ https://github.com/gkvoelkl/python-sonic http://www.daveconservatoire.org/course/introduction-to-sonic-pi By the end of this talk, I aim to instil a much better idea about Live Coding and Programming Musi", - "Description": "Sonic Pi: An open-source live coding platform developed by Dr Sam Aaron aims to explore and teach programming concepts based primarily on the process of creating new sound.\nWe will venture deeper into the live coding platform and produced different genres/styles on music while coding live and dwell further into performing algorithmic music on a wider scale. I have tinkered with different styles of tones and sounds in sonic-pi and Python and re-created a rendition of popular 21st century music, only through algorithmic-generation, and seek to promote appreciation about open-source software such as sonic-pi and aim to demonstrate it's applications, along with the use of Python over the course of a thirty minute-talk and demo, in the rendition of producing Algorithmic-Music Live , during the course of the talk. By the end of the session, I aim to establish a better understanding of Live-coding, Programming Music and Intelligent-dance music Artists such as Aphex Twin. The flow of the talk will be as follows: Self Introduction Introduction to Music-theory and Sound Generation Introduction to Live Coding and Python-sonic Understanding the algorithmic workflow Diving beyond: Guitars, drums and Piano Produce an algorithmic-track! End of talk Q&A Session We shall also fiddle with a physical midi-controller if we find time, and demonstrate various interesting forms and styles of music; \nWe will also be producing a popular 21st century track from scratch ", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " A curiosity for algorithmically-produced music, Python and open-source software. Basic Music theory knowledge is appreciated, but anything relevant will be covered during the talk.", - "Section": "Others", - "Speaker Info": "My name is Sushen Kumar. I am a currently pursuing a Bachelor of Engineering in Computer Science at Sir M Visvesvaraya Institute Of Technology, Bangalore. Over the course of my academia I have dabbled into a few open-source projects, as well as contributed to open-source organisations on GitHub: Attended several hackathons around India: (Winner-ValuePitch Hack, Runners' up- IESA Makeathon) Given talks and held beginner sessions on Creative Coding in Python and sonic-pi. Completed three grades in hindustani-classical music-theory, with 8+ years of experience in playing the Guitar and Harmonium. Received 3 Honours and Awards (National level). I absolutely love Music and Coding, and aim to merge this passion and demonstrate the applications of Python and open-source frameworks in Music Production by means of this talk :)", - "Speaker Links": " https://github.com/nehsus https://www.linkedin.com/in/sushenk/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Nehsus (~nehsus)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-algorithmic-music-and-melodies-with-python-sonic~dRXVa/", - "title": "Generating Algorithmic Music and Melodies with Python-sonic" - }, - { - "Content URLs": "Slides : https://docs.google.com/presentation/d/1zNFGNy2BMBYQvZypkH8Iql-WRx--6Ddg8Ft33intWjM/edit?usp=sharin", - "Description": "Large Python codebases can be hard to maintain. If we make it easier to understand our code bases, we make everyone more productive and help each other write fewer bugs. Static typing is one of remedies that can improve readability and maintainability of the code. That's why Python now features optional static typing as described in PEP-484 , implemented as Mypy . Mypy is an experimental variant of Python that let's you add optional type annotations to type check your Python code. And it works great on both Python 2.7 and 3.3+. Adopting static typing is easier that you think, you can start on a small set of code and move on to bigger pieces. In this talk I'll share about, PEP-484 and Introduction of type annotations in Python 3.5 Use cases of Mypy and how to use it with Python 2 and 3 Project typeshed and how to leverage it Lessons I learned by type hinting the project Twine We\u2019ll also discuss how to make it a seamless part of your project; what order to approach things in; and some powerful new packages that make it even easier today to add static types to your Python codebase than ever before", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of Python Difference between dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Wasim is a Senior Software Engineer at Zemoso Labs, Hyderabad. He's an open source fanatic who loves to create meaningful software and contribute to open source projects. Some of his contributions are included in projects like Sendgrid, Warehouse, Twine and Hazelcast. Apart from programming he also tweets . You can find him interesting on his GitHub profile ", - "Speaker Links": "Article on Medium about Mypy Stub file for the project Texttable Open source contributions can be found at my GitHub profile ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Wasim Thabraze (~waseem18)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mypy-optional-static-typing-for-python~bW1Ee/", - "title": "Mypy: Optional Static Typing for Python" - }, - { - "Content URLs": "https://github.com/Laneone/askfm-pytho", - "Description": "Hey everybody! Ever tried to webscrape? Ever faced a \"No robots allowed! No web scraping allowed!\" message from a favorite site? This talk is for meant for you. Usually when you're done building a fancy web scraper and begin running the homebrew'd tool on your favorite site there's chances you'll face a block on your IP address preventing your computer from accessing more resources and therefore downloading the contents of the website. Your tool maybe fast, it might be scalable, it might be the best written scraper out there, but with just one IP address under your belt, it's easy for giants to block your ip address and prevent you from getting that precious data, especially if you've built a threadsafe and multi-node webscraper. Enter The Onion Router, The ToR project, allows you to use the the internet vis-a-vis a proxy and visit the same website under a different endpoint ip address, but that's just for one instance of ToR. What if you ran, say 200? at once? 200 ip addresses > 1 ip address. With 200 endpoints and the latest update to the requests library, you can now use your multi-threaded and resource hungry webscraper and it can(not) be stopped! Whatever your rate of data collection, you can 200x it! The stack is simple, you open a SOCKS5 proxy per ToR endpoint, connect it to a request with it's own port number and you're good for that one request, same for multiple requests. You can build a task scheduler to orchestrate the url to scrape and the port number the tor endpoint is on and have the entire application running on a cloud service provider to ensure you face no bandwidth issues. The demo centered around the talk will attempt to rapidly and quickly scrape users from the famous social network Ask.fm which is known to restrict users from retreiving from their site if you attempt to download more than 4 users in under a second, but with the hack in place, you'll be retrieving close to maximum efficiency on a DigitalOcean droplet , but this can be applied to virtually any website and any cloud provider. Never pay for webscraping again! Thanks and see you at PyCon! \n-Lokesh Poovaraga", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic concepts of web scraping, Regex, Task scheduler, ports and proxies", - "Section": "Developer tools and Automation", - "Speaker Info": "Hi I'm Loki! (Lokesh Poovaragan) A full-stack developer from Dayananda Sagar, Bangalore, and I love to code in python! In my free time I love to web scrape and gather good amounts of public data and encompass them into json format for data(sentiment) analysis. I also build prototypes of interesting combinations of technology to solve unique problem statements. I love exploring new and interesting areas of work and I love to play with code", - "Speaker Links": "Blog: http://laneoneblog.blogspot.in GitHub: http://github.com/Laneon", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Laneone (~Laneone)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-intermediates-guide-to-theoretically-unlimited-webscraping-with-python-using-requests-lxml-tor~e1MZe/", - "title": "A Intermediate's Guide to (theoretically unlimited) WebScraping with Python using Requests & lxml & ToR" - }, - { - "Content URLs": "This one is the essence of it but closed source and in java: https://lifehacker.com/how-to-build-your-own-amazon-echo-with-a-raspberry-pi-1787726931", - "Description": "Voice is the new touch. It's not going to be too long before the likes of Alexa or Google Home take over our day to day life like the Internet and the mobile phones have. There are countless tutorials on how to hook up a home automation system using a Raspberry Pi like here and here . Pair that up with voice capabilities and you can basically tell your lights to turn themselves off or the TV to change the channel. In this talk I'll cover the following: Hook up a microphone to a raspberry pi and be able to capture wav files on python. Use an online API like Google's Speech API to convert the wav to text. Give a background on what intents and entities (slots) are. Installing open source software like Snips Encoding our intents and example sentences and training the open sources software Calling a functions to do particular activities At the end there'll be a cool demo", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of what a Raspberry Pi and Python is. And maybe played with an Alexa, Siri or Google Home. Yup, low barrier of entry", - "Section": "Embedded python", - "Speaker Info": "I am Ved. I have a masters in Computer Science/Data Science from IIIT-Bangalore and I work on NLP/Linguistics at Slang Labs. My goal in life is to sit down and have a conversation with a computer at a bar coffee shop. Maybe we won't get there soon, but at least maybe I can make it reserve my seat for me", - "Speaker Links": " vedmathai.com https://github.com/vedmathai/ https://www.linkedin.com/in/vedmathai/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ved Mathai (~ved47)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/create-a-voice-conversational-agent-for-your-raspberry-pi-home-automation-system~eZgQa/", - "title": "Create a voice conversational agent for your raspberry pi home automation system" - }, - { - "Content URLs": "Shall be updated soon", - "Description": "Here, We will talk about how you can make a bot to help you automate your life and make your very personal Assistant, and maybe you will end up making something better than Google Assistant or Siri. We will be using modules to perform a task, so you can keep making them as you go and your assistance will keep becoming more powerful and yes all this will be done in python. In this talk: - We will start with setting up project creating simple python GUI. - Making some modules to perform a simple task. ~ Composing email with speach ~ Some other cool modules - Explaining what else we can achieve with this. ~ Let's make, its personality using tensorflow for talking stuff - Showing my work and explaining how it works Here, Is in early development phase Then we will end with some questions and how they can continue with this project", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic Understanding of Python", - "Section": "Developer tools and Automation", - "Speaker Info": "He is a student, a self-taught programmer loves to dig deep and know more about the computers. Fell in love with python and now loves to Automated things with python. He is GSoC aspirant. He is an active volunteer at PyDelhi and ALiAS . When he is not automating things he loves to contribute to open-source and closing issues", - "Speaker Links": "Website: omkar.site Github: @omi1085", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "omkar yadav (~omkar10)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/superpybot-your-personal-assistant~bYZAd/", - "title": "SuperPyBot: Your Personal Assistant" - }, - { - "Content URLs": "https://www.artima.com/weblogs/viewpost.jsp?thread=214235 http://www.dabeaz.com/python/GIL.pdf -slides tb", - "Description": "Python is an amazing language, known for its vast standard library and use in rapid prototyping. When we were trying to build a robotics system that is primarily modular and upgradeable, we ended up using Python to power the brain of the project. In this talk, we'll discuss how we designed the event loop, responsible for controlling the mechanical actions and state of a robot snake. Animating multiple motors concurrently at different speeds to different positions. Foreground and background tasks. Interrupting ongoing tasks. We will discuss best practices when performing asynchronous actions in Python, and how to ensure actions are completed within a bounded time.\nFinally we touch one of the lesser known 'features' of Python, the Global Interpreter Lock. GIL is a mutex that protects access to Python objects, preventing multiple threads from executing at once. Two threads calling a function may take twice as much time as a single thread calling the function twice. We'll discuss some of the real world implications of the GIL, along with some considerations that must be taken while writing highly synchronous Python code", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Knowledge of common Python syntax would be great", - "Section": "Core python and Standard library", - "Speaker Info": "Hi, I'm Pranith, a final year undergrad student at NMIT, Bangalore. I'm a robotics enthusiast with a passion for cypherpunk, virtual reality, and generally, the future. Apart from the usual frameworks, I've used Python across the field, ranging from web technologies implemented on raw CGI to microPython on the ESP8266. I try to apply Python in odd ways to bridge various layers of the stack, and as a result have a fair amount of experience breaking it", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pranith Hengavalli (~prnthh)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/robot-snakes-and-the-global-interpreter-lock~eXPve/", - "title": "Robot Snakes and the Global Interpreter Lock" - }, - { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "In today's Era, the IT sector is moving more and more towards automation. Now every company is trying to provide its users with the facility to perform their task without the need for any human intervention.\nIn this talk, we are addressing a similar problem of automating the vehicle parking systems. Problem description: Automated license plate recognition(ALPR) is a well-known problem where we try to extract the license number from a cars number plate using machine learning algorithms. The scope of its real-world application ranges from highway toll plaza to automated parking and charging of future electric cars.\nThis problem has been targeted with a variety of algorithms like traditional template matching to advance deep learning algorithms like YOLO . Here we will be presenting a combination of little template matching clubbed with some deep learning to solve this problem in the most simplistic way", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations", - "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saqhas", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-license-number-recognition-in-python~e33Ae/", - "title": "Automated License number recognition in python" - }, - { - "Content URLs": "Would update soon after feedback", - "Description": "Most machine learning algorithms require feature vectors as inputs. In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object (image, text, sound). Feature engineering, the practice of extraction of features from objects is a combination of art and science; it requires the experimentation of multiple possibilities and automated techniques with the intuition and knowledge of the domain expert. Automating this process is called \"feature learning,\" where a machine learns the features itself. One way to obtain features is to use the 'Bag-of-Features' model, the idea behind which is to simplify object representation as a collection of its subparts. Originally used for representing text data, the \"Bag-of-Words\" methodology can be extended to different types of objects resulting in models such as \"Bag-of-Visual-Words,\" \"Bag-of-Audio-Words.\" The significance of these models in the age of self-learning deep networks still holds because of their ability to work with limited data. The contents of the talk are: Introduction to Feature Engineering Working with Text Data Understanding 'Bag-of-Words' Example: Text Classification Working with Image Data Introduction to 'Bag-of-Visual-Words' Example: Image Classification Comparing the performance to CNN Overview of 'Bag-of-Audio-Words' Generalizing 'Bag-of-Features' This talk primarily discusses Bag-of-Words, Bag-of-Visual-Words through an example of text classification and image classification respectively. It also covers the concepts that generalize to models other than Bag-of-Features. The goal is to acquaint the audience who have previously worked on numeric data with some ideas to get started with text and multimedia data", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Intermediate knowledge of Python Familiarity with classification problems Familiarity with basic NLP/CV is helpful (but not necessary)", - "Section": "Data science", - "Speaker Info": "I'm a fresh graduate in Computer Science & Engineering. I am passionate about Data Science, and I spent most of my time learning about skills required to excel in the domain. Outside of my professional interests, I am fond of rock music and reading", - "Speaker Links": " Blog: https://pranavsuri.com GitHub: https://github.com/pranavsuri LinkedIn: https://linkedin.com/in/suripranav Twitter: https://twitter.com/pranav_suri", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pranav Suri (~pranavsuri)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bag-of-features-representing-text-image-data-as-numerical-vectors~b2XMe/", - "title": "Bag-of-Features: Representing Text & Image Data as Numerical Vectors" - }, - { - "Content URLs": "Part 1 Part 2 Github Rep", - "Description": "Websites and blogs have become a common trend amongst professionals to display not just their resumes but also their daily work items. Static blog generators have gained popularity over the last few years . People who have been using Wordpress, Blogspot or Blogger are now shifting to Pelican , Jekyll etc. One major annoyance was that Wordpress had a huge attack surface. Everytime someone found out a Wordpress exploit, your site was at risk. When comparing Blogger vs Pelican, the Slant community recommends Pelican for most people. In the question \u201cWhat are the best solutions for a personal blog?\u201d Pelican is ranked 10th while Blogger is ranked 14th. Python is becoming more and more popular amongst programmers and so is Pelican . \nPelican is a static blog generator and supports several formats like Markdown , ASCII etc . It turns Markdown and some Jinja templates into the Full Stack Python site. Its beauty lies in its simplicity and even a non programmer can get started with Pelican in just a few lines of code and plain text . Over the past few years people have shifted from Wordpress to Pelican .This is because a static site has basically no attack surface, and can be hosted on free or inexpensive hosts like Github Pages .\nThis talk is focused on introducing a simple static site generator to beginners and even avid bloggers who aren't coders . This talk will cover:- Basic installation of Pelican Writing a blog post with Pelican Changing themes of a blog/site Comparison between Jekyll and Pelican The main aim of this talk is to familiarize people with the concept of edifice . I have met a lot of non coders who have asked me about creating a basic website for personal use . This talk is also targeted to all those you are interested in blogging and everyone out there has something to say and something to blog ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "Absolutely nothing ", - "Section": "Web development", - "Speaker Info": "Anumeha Agrawal is a Pythonista and an open source enthusiast . She is in her third year of undergraduate program in Information Technology at NITK Surathkal . She is also a Google Summer of Code 2018 student at Systers . In her project at Systers , she has used python to write scripts to retrieve data from GitHub API and use it in her MEAN stack project . She uses python scripts to simplify most of her work like API data collection and web scraping . Python was the first language she was introduced to when she began programming and it is her weapon of choice . Owing to the simplicity of python syntax, she also used python to code her algorithms for her talks and workshops at college . Apart from being a full stack developer ,she is also a Data science enthusiast and employs python for designing most of her Deep Learning models and algorithms ", - "Speaker Links": "Link to Github Link to Linkedin Profile Link to Medium Blog Link to GSoC projec", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anumeha Agrawal (~anumeha)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pelican-magic-for-beginner-bloggers~e5MYe/", - "title": "Pelican - Magic for beginner bloggers" - }, - { - "Content URLs": "http://click.pocoo.org (Cool power-point and Github repo coming up", - "Description": "Who hasn't used Git in the terminal? An absolute beast of a tool. But did you ever have an idea to build your own cool Command Line tool for something you believed could simplify life for other devs but you didn't because you were too lazy to research? Worry not! I present to you Click! Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It\u2019s the \u201cCommand Line Interface Creation Kit\u201d . It\u2019s highly configurable but comes with sensible defaults out of the box. In this talk, I'll go through the process of designing a simple (or complex) Command Line Interface called thanos which tells you whether you survived the SNAP or not. I'll be taking you through the process of designing, building and publishing our thanos package. We'll then upload it to the Python Package index so that you can do pip install thanos from any system worldwide and find out if you perished or not. Outline What is a CLI ? Building our own CLI called Thanos , to find out whether you survived the snap or not. >>thanos snap\n You didn't make the snap. Creating complex commands using beautifully decorated code. Exploring arguments, flags and options within the CLI. What's PyPI, and why do we need it? Uploading your new Thanos package to Python Package Index. QA", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Should have seen or used a terminal before. (Mandatory) Basic Python knowledge preferred.", - "Section": "Developer tools and Automation", - "Speaker Info": " Adarsh is a visionary who strives to build amazing tools for people. He is currently pursuing bachelors in CSE. Currently he is Google Summer of Code Intern at CloudCV , an organisation which works on making reproducible AI research, where he is building a versatile CLI for EvalAI project. He was one of the youngest speakers at FOSSASIA International Summit 2018 in Singapore for his work on Python based NLP POSTagger. Worships Open Source software and have contributed to multiple organisations like FOSSASIA, Zulip where he was also a mentor for Google Code-In 2016 .", - "Speaker Links": "https://www.youtube.com/watch?v=TzIr9THCUJg https://2018.fossasia.org/event/schedule.html#s-4267 https://github.com/isht3/ https://www.linkedin.com/in/guyandtheworld", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "isht3", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-your-own-command-line-application-and-upload-it-to-pypi~b427e/", - "title": "Build your own Command Line Application and upload it to PyPI!" - }, - { - "Content URLs": "Will be sharing soon", - "Description": "Your introduction to concurrent programming in python. This talk is dedicated to a developer to enable him/her get started in asynchronous programming. The contents that will be covered in the discussion are as follows. What is asyncio? Why should we bother? Multi Threading vs Multiprocessing vs asyncio understanding the differences. All about what an event loop is with examples Futures Tasks and coroutines Streams Multiple Coroutines. Scheduling Calls Synchronization primitives Queues Working Example with a few notes on sockets and summary. The talk provides preliminary insight and a simple explanation to programmers who wish to explore asyncio and/or concurrent programming. ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Basic understanding of python syntax. Some OS concepts like differences b/w multiprocessing and multithreading. Understanding UNIX (not mandatory).", - "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-asyncio~b6MOa/", - "title": "Introduction to Asyncio" - }, - { - "Content URLs": "Slides TBD Code repository TB", - "Description": "Abstract Today, massive systems are running on microservices communicating with each other using REST APIs. REST is easy to get started, loosely structured and does good job in exchanging messages. But it's convenience comes with a performance trade-off, which takes us back to other optimal alternative: gRPC Description In this talk we will see what gRPC is and how it is different from REST. We will get started with GRPC by generating stubs for python and \nbuild a simple gRPC API server. We will try to find out the advantages of gRPC over REST by doing a side by side comparison of our APIs. We then deploy our server in Kubernetes and discuss how we could scale our microservices. Outline Introduction to gRPC (3 min) gRPC concepts (5 min) Designing the APIs REST-fully (3 min) Going the gRPC way (5 min) Generating python stubs Duel: gRPC vs REST python servers (4 min) Demo (4 min) Deploying our gRPC apis in kubernetes Summary (3 min) Q & A (3 min) Key take aways to audience Audience will get a practical introduction to gRPC and protocol buffers. Now the audience will know an alternative to HTTP/REST. This allows them to design better microservices\nbased on their use cases. Bonus: Deploying and scaling python microservices in Kubernetes. Links Companies using gRPC in production Protocol buffers ", - "Last Updated": "09 Jun, 2018", - "Prerequisites": "This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners", - "Section": "Web development", - "Speaker Info": "Naren is a Product Engineer with specific focus on building robust backend systems. Past 5 years, he has built dozens of microservices and scalable systems using Python, Go and AWS cloud. He is an open source enthusiast who loves speaking at tech conferences and currently works as Senior Software Consultant at Tarka Labs. In his industry experience he\u2019s worn plenty of hats- like the one of a Trainer, Embedded Engineer, Product Engineer and Consultant and sometimes even helmets- while he\u2019s out cycling.\nWhen he\u2019s not stirring up code, you can find him whipping up a delicious gluten-free treat or training for cycling races.\nHe also blogs about software, productivity and goes by the handle DudeWhoCode across the internet", - "Speaker Links": "Past 5 years I have been architecting and building scalable backend systems using Python. I have built a dozen of microservices at scale. Recently I built a production infrastructure in Python that handles 20+ millions of API calls per day. At one point of time, I realised I should know some alternatives other than REST to communicate between the microservices. Out of curiosity I explored and used gRPC in few of my microservices. Since then, I wanted to share the knowledge so that developers will get to know other options while architecting their infrastructure. This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners. I have spoken in various conferences, my recent one was PyCon Singapore 2018. Below are some of my previous talks and speaker portfolio: Speaker Portfolio Featured talk 1 Featured talk 2 Featured talk 3 portfolio blog Github", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Narendran R (~narendran)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-better-python-microservices-using-grpc~e9jJa/", - "title": "Building better Python microservices using GRPC" - }, - { - "Content URLs": "I will upload slides soon", - "Description": "Object-Relational Mapper (ORM) is one of the powerful feature of Django. It allows us to interact with database without writing long complex SQL queries. The contents that will be covered in the discussion are as follows. Introduction to ORM, How it works ? What is queryset ? how it works ? Explaining use of values, values_list, only and defer to run ORM query efficiently How to use select_related and prefetch_related to optimize queries Some examples to show, how to query very complex data using only ORM What not to do while using ORM to avoid slow performance", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic knowledge of Python and Python web framework (Django) Some experience in quering relational databases", - "Section": "Web development", - "Speaker Info": "My name is Hiren Patel. I am working at Aubergine solutions pvt ltd and I have been doing full stack web development there from last 2.5 years. While working on some web projects, I have always focused on learning django in more detail and try to optimize APIs to return response faster", - "Speaker Links": " Github: https://github.com/hirenalken LinkedIn: https://www.linkedin.com/in/hiren-patel-046672ab/ StackOverFlow: https://stackoverflow.com/users/3553279/hiren-patel?tab=profile Medium: https://medium.com/@hirenpatel_38103 I had presented a talk on this same topic in meetup organised by Ahmedabad based meetup group. here is the link to meetup: lin", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Hiren Patel (~hirenalken)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/efficient-use-of-django-orm~b8gja/", - "title": "Efficient use of Django ORM" - }, - { - "Description": "This workshop is dedicated to discuss and extrapolate on the core of Object Oriented Programming its finer details and nuances. The objective of the talk is to introduce concepts that will ensure OOP becomes second nature to a programmer. What you will gain after this session Detailed overview of Object Oriented Programming Intuition on the finer nuances of Object Oriented Programming. Tips on keeping the OOP code clean and readable. Expanding your horizon by understanding some lesser known concepts in Python. The session will focus on the following aspects with examples Inheritance and everything about it. Method Resolution Order Method Types Custom Base Object, Collections, and Dict Objects Extending Built-in Types Data Models Meta Classes and where they help Decorator and Class Decorators. Factory Design pattern Singleton Things to remember while writing code Conclusion", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic Python syntax Some understanding of Object Oriented Programming", - "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-object-oriented-programming~e7MQb/", - "title": "Advanced Object Oriented Programming" - }, - { - "Content URLs": "Any related material will be shared soo", - "Description": "Natural language processing(NLP) is a branch of artificial intelligence concerned with automated interpretation and generation of human language. From keyword search to Virtual Assistants, from spell checkers to language translators and from sentiment analysers to Chat bots, NLP finds its applications in most of our day to day applications.\nThis workshop aims at delivering a basic Hands on tutorial to get started with NLP in Python. It commences with an introduction to NLP, discussion on various applications and a linguistic breakdown of Language (English). By the end of this workshop you will be able to : Install relevant packages such as nltk, gensim and pattern . Applying text processing techniques such as Tokenization, Stemming, Lemmatization and Chunking . Forming a Document Term Matrix using Bag of Words Model . Building a simple Spam/Ham classifier using Bag of Words Model . Generating Word Vectors using Gensim Word2Vec module. Building a Sentiment Analyzer . This workshop provides preliminary insight and a simple explanation to enthusiasts who wish to explore the field of Natural Language Processing.\nIt enables you to talk to your computer!", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of Python. Any knowledge of Python modules such as Numpy, Pandas etc. is and add on.", - "Section": "Data science", - "Speaker Info": "Hello, I am Osheen Nayak, working as a Software Engineer at Texas Instruments Bangalore. I belong to Delhi Technological University batch of 2017.\nI am a Machine learning and Data Science enthusiast and I have been actively driving various Machine Learning activities. I have delivered few talks on Machine Learning in the past one of them including \"A primer on Machine Learning and Artificial Intelligence\" in the IEEE forum to and audience of 50 people. I am an avid football fan and also an amateur player.Also, I like to play video games, cricket and chess", - "Speaker Links": "Connect on LinkedIn : https://www.linkedin.com/in/osheen-nayak-31022a10b", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "osheen nayak (~osheen)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-talk-to-your-computer-a-101-on-natural-language-processing-with-python~e0M5a/", - "title": "How to talk to your computer - A 101 on Natural Language Processing with Python" - }, - { - "Content URLs": " http://github.com/vaideesg/omsdk http://github.com/dell/omsdk", - "Description": "Abstract Ever wonder creating your own super-type-manager leveraging the python's own type constructs? Ever explored alternatives to APIs for integration? In this talk, we will cover our experience in building a new type manager (as part of developing open source OpenManage(tm) Software Development Kit) leveraging pythons own type constructs and explore how this new type manager provides a credible alternative to APIs, especially in those information-heavy environments like Device Management. Description Devices (like Servers, Switches, Telecom Switches) are data-intensive systems. Their information model is so intensive, that practically all operations (health, inventory, metrics, configuration) on the device ends up in primarily as CRUD operations on the information model they expose. Only a paltry few operations are exposed as APIs. When building an API for managing these devices, we realized that providing classic function-style APIs only degraded the user experience. What we realized was there was significant information available on the Servers, and providing an API for exposing traditional CRUD (Create, Retrieve, Update and Delete) for all information nuggets was just exploding the API sets. It was not necessarily covering all the scenarios that could be possible for management and did not seem to scale. Our approach was to take this information model within the devices and expose them as a huge navigable data structure representing the entire spectrum of the device and provide a language native experience. We created a new type manager leveraging the python class special operators ( getattr (), setattr (), le () etc.) to create a whole new type manager that provides additional controls and safeguards. Some of the safeguards include: Not allowing edits to read-only components Allowing only applicable changes only (ranges, enumerations) Providing native python experience for special types (IP Address Types etc.) Providing mechanisms to validate cross-attribute validations Providing custom indices for arrays (like Virtual Disks, Users) Providing mechanism for tracking changes to configuration Apply changes to the device optimally Provide mechanisms for identifying configuration drifts Outline : Outline of the presentation: Introduction Device Configuration - Aspects & Peculiarities Pitfalls of API approach for Device Configuration Type Manager - introduction Super Types - Enumerations, Fields, Classes and Arrays Bringing in Native Type Experience Data as API - Enriched user experience Demo Q&A Key takeways to audience Audience will get an exposure: How to create your own type manager by overloading python type constructs Exposure to alternative approach to creating APIs for data-heavy systems & explore benefits Learn how type manager simplifies your life as well as the life of your consumers. Secrets of the python inbuilt __ operators - and how you can leverage them to provide native type experience even for your own custom classes How you can create a better user experience for customers in a simple way How you can incorporate Object Oriented SOLID principles", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " General familiarity with type concepts (fields, arrays, classes, enums) is needed Exposure to in-built operators like ( getattr etc. will help) Exposure to Systems Management would be useful.", - "Section": "Core python and Standard library", - "Speaker Info": "Vaideeswaran Ganesan, Senior Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and data center products. His passion is compiler design, analytics, systems management, networking protocols and automation. Ajaya Senapati, Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and storage products", - "Speaker Links": "Vaideeswaran Ganesan\n 1. My Github Repository 2. My Linkedin Article which I wrote while implementing this Fun with Python Code Generation Ajaya Senapati\n1. Lin", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Vaideeswaran Ganesan (~vaideeswaran)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-as-api-building-a-type-manager-with-python~egyrb/", - "title": "Data as API: Building a Type Manager with Python" - }, - { - "Description": "Fog and haze (referred to as the atmospheric light) are the main cause of distortions, degradation in the quality of images clicked during foggy situations. But with the advancement in technology, thanks to Python and OpenCV libraries and brilliant minds of people out here in this small world, recovering almost a fog-free image has been made possible in recent times. And now we are moving towards making this algorithm more optimized so that it can work in real time for videos and live camera feed. Different mathematical models have been presented over the time for this algorithm but there are very few real-life implementations in any particular programming language, so here the Python implementation of this algorithm will be discussed. Basic steps and the ideas implemented will be discussed in a brief and different implementation will also be shown in the session", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of the numpy functions. An idea about the OpenCV computer vision libraries and the different filters implemented there. Love for Python", - "Section": "Developer tools and Automation", - "Speaker Info": "Speaker: Vivek Modi Final Year undergrad at NIT Durgapur Tech Head at GNU/LINUX USERS' GROUP NIT Durgapur Summer Intern at DRDO (Integrated Test Range) Contributor in the project: Soumam Banerjee Final Year undergrad at NIT Durgapur", - "Speaker Links": "modiher", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vivek Modi (~modihere)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-and-opencv-for-removing-fog-and-haze-from-an-image~ejBye/", - "title": "Using Python and OpenCV for removing Fog and Haze from an Image" - }, - { - "Content URLs": "Will be uploading soon !", - "Description": "My philosophy has been : If you haven't build it you don't know it. So lets build a hadoop clone and see how it works . This workshop is basically about building your distributed processing system . It will take you through some basics of distributed system and we will try and build our very own distributed system in python ", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Google \"what is hadoop\" Google \"what is a distributed system", - "Section": "Networking and Security", - "Speaker Info": "class Pankesh (human)", - "Speaker Links": "class Pankesh (Human): def __init__ ( python=\"Python3\" ) :\n\n super.name = \"Pankesh gupta\"\n\n super.age = 25\n\n curiosity = True\n\n experience = 2\n\n education = \"Thapar University , Patiala", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lets-build-a-hadoop-clone-in-python~bm6Rd/", - "title": "Lets Build a Hadoop clone in python !!" - }, - { - "Content URLs": "-> How does a web framework work -> WSGI basics -> Getting hands dirty with coding More information will be uploaded soo", - "Description": "Build your own web framework using python .\nLets unleash the power of python by building a web framework from scratch . \nIt will help you understand what actually happens under the hood in most famous web framework", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Web development basics\nCuriosity\nTrust in python :", - "Section": "Web development", - "Speaker Info": "Not so useful BTech ( biotechnology ) from Thapar University\n2 years of experience working in pytho", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-our-own-web-framework-like-flask-in-python-from-scratch~el0je/", - "title": "Building our own web framework like flask in python from scratch" - }, - { - "Content URLs": " Will have own slides. Link will be shared with all This GitHub Repo contains some of the content that will be delivered during the course of the talk. A lot of other websites from where I pick a point or 2", - "Description": "Everyday we listen to this word \"DATA\".\nBut after listening to that word, some questions might pop up in your mind. WHAT IS DATA? WHY DOES ANYONE NEED TO WORK WITH DATA? HOW TO UTILISE AND WORK WITH THIS DATA? Data is now one of the most important things for any business to run. From small startups to large companies, everyone looks at data to improve their business.\nEveryone looks at data to increase their profits. Everyone looks at data to understand why they failed and where they failed. Everyone looks at data to understand how a product gained success in the market. Basically Data is everything today for companies. Data is available everywhere now and it's become more important than ever to actually work with data and luckily we have great modules to work with data in Python. I'll be focusing on these modules and the power that data possesses. My primary focus here would be about the power of data. I surely will be talking about how to use this data in Python to make the most out of it, but before that I'd like the entire crowd to know what the power of data is. This would be a good talk for beginners honestly. Even if you have no idea about how data could be used or what is data, after this talk, you'll get a decent idea about it. Through this talk the 3 questions mentioned above in bold will be answered. The talk would progress in the following manner : Self introduction (3 minutes) Introduction about the topic (2 minutes) What is data? (3 minutes) Where is this data? (2 minutes) How to make the most out of data? (3 minutes) How Python helps in this process? (2 mins) Name and explain about different Python modules like Pandas, Numpy, Matplotlib and Seaborn in brief (10 mins)", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "No prerequisites required. This talk will deal about everything from scratch and will give you a basic understanding of what modules could be used in Python. So you could research on those modules after the talk, but for the talk, no prerequisites required", - "Section": "Data science", - "Speaker Info": "Hey everyone, I'm Rahul Arulkumaran, a B.Tech 3rd year Student pursuing my major in Computer Science Engineering from Mahindra \u00c9cole Centrale, Hyderabad. I'm an open source and data science enthusiast. Coding is one thing I love doing all day and all night. Never feel like quitting.\nPython is my go to language. Anything I think of developing comes to life using Python. I have a very strong connection with Python as it was the first programming language I learnt. I'm also a full stack developer and perform data science on various datasets. I'm a Contributing and Managing Member in the PSF. I also am the President of the Computer Science Club in my college. Apart from that, I head the website development team for TEDxMahindra\u00c9coleCentrale and the Marketing and Promotions team for Aether (the techno cultural fest of MEC). I'm the Co-Founder and CEO of a startup which goes by the name FreeFlo. It is a product based company that looks at developing products related to Machine Learning, Blockchain and other related fields. I'm also currently interning in IIIT-Hyderabad in the Machine Translations and NLP Lab in the field of sentiment analysis. It might seem although I'm not interested in the non tech aspects of businesses, but I actually love working in teams related to business development and marketing. So that's mostly about it. Looking forward to interact with all of you out there ", - "Speaker Links": " GitHub My Blog Facebook LinkedIn Twitter Telegram Gmail ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/power-of-data-and-working-with-it-using-python~bkgJb/", - "title": "Power of Data and Working with it using Python" - }, - { - "Content URLs": "https://www.slideshare.net/mobile/karx01/micro-python-pycon-india-2018-proposal-kartik-aror", - "Description": "This session will aim to achieve 2 objectives Introduce you to (in a fun and practical way), what is microPython. equip you to be up and running to build your own systems!", - "Last Updated": "13 Jun, 2018", - "Prerequisites": "Must know a guy who owns a raspberry Pi", - "Section": "Embedded python", - "Speaker Info": "Hello World. I am Kartik Arora, founder at Akriya Technologies . Before starting my journey in the wild, I worked for Rivigo for a few months, and in Bing Team during my 2 years at Microsoft", - "Speaker Links": "https://twitter.com/karx_brb https://www.facebook.com/karx01 https://www.linkedin.com/in/karx01 https://github.com/kar", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kartik Arora (~kartik53)", - "created_on": "13 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/micropython-time-to-get-building~av58e/", - "title": "MicroPython : time to get building" - }, - { - "Content URLs": "Will be updated on github before the conference", - "Description": " It is always essential to understand the genesis of evolution or the roots of revolution. Keeping in mind the above saying, in this workshop, I will provide a hands-on understanding of Blockchain technology using Python. There are multiple resources to get a firm understanding about this domain, but the best way to understand it is by using the concept of \"Learning-By-Doing\" . Following are few reasons why I want to willingly contribute to this domain: Blockchain is the underlying technology behind most of the\n cryptocurrencies and it has a potential of changing the way we work\n and communicate, making it more secure, efficient, and trustworthy. There is a immense amount of speculation going around in this domain\n with the rise of Bitcoin. What\u2019s happening with blockchain\n technology, I would say, is similar to the great American gold rush\n that happened in the mid 1800s. Innovators, investors, entrepreneurs, technologists all are hovering\n over the same underlying idea on how these cryptocurrencies work and\n how could blockchain be leveraged to create use-cases beyond\n crypto-systems. Also, I would love to mention few quotes to support the escalating phenomenon of Blockchain : The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping\neverything along its way by the force of its progression. -- William\nMougayar Over the next decade, there will be disruption as significant as the Internet was for publishing, where blockchain is going to disrupt\ndozens of industries, one being capital markets and Wall Street. -- Patrick M. Byrne I will help people in understanding the bits and bytes of this domain, including the basic cryptography concepts, algorithms and how to utilize the power of Python language to build their own blockchain. As we progress, we would engage into more advanced concepts pertaining to scalability and deployment once we build a minimalist prototype of aforementioned. Using on-the-go learning while developing will serve as a pivotal entry point for all the people who are willing to enter into this space and planning to build smart-contracts or invest in cryptocurrencies. Agenda for workshop : Introduction to Blockchain: Existing problems, what is Blockchain, why it matters, gist of few use-cases, related concepts. Python revisited: Functions, libraries, object-oriented programming terminologies, basic data structures, basics of zen of python. Blockchain under the hood: Cryptography 101, underlying data structure and algorithms, conceptual terminologies. Python and Blockchain amalgamated: Create blockchain using python. User-friendly front-end: Integrating the scripts in previous section with a basic front-end. Discussion regarding scalability methods and resources. Generating self-help focused Pypi library called pymyblockchain . (optional) Q&A session. Note: The above agenda is subject to change. It is tentative for now. Any changes will be updated here itself", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basic python: Functions , Classes and Objects , Use of Libraries *No prerequisites apart from aforementioned. Even a person who is new to python will be able to grasp everything in workshop", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchain-by-implementing-it-from-scratch-in-python~bq57b/", - "title": "Understanding blockchain by implementing it from scratch in Python" - }, - { - "Content URLs": "My python script", - "Description": "Information is being generated at an exponential rate everyday. There are multiple sources generating information. It becomes really tedious for a person to go and visit all the sources to obtain information. It could be of great help to the person if there can be a single source which cumulatively providing all the links of news generated by different newspapers. This is where web scraping and automation comes into picture. In this talk I want to explain how to scrape webpages hassle free , gather information and represent the gathered content in a easy to visualize format. By executing just a single Python file we can get all the data what we want from the web. Its not just about collecting the data, it is to reduce the repetitive work which a person does again and again to achieve the same goal. We can put repetitive work into a module and leave it upon the computer to do the same. This in turn will help us channelize our time more on the information rather than gathering that information. Agenda of Talk: Introduction: Web scraping, automation tools, parsing and scraping python libraries. How it helps in learning python extensively: My experience with web scraping and various use-cases on which I utilized. Q&A session.", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "None", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping-and-automation-for-novice-users~er52d/", - "title": "Webscraping and automation for novice users." - }, - { - "Content URLs": "Any related material will be shared soo", - "Description": "Financial data is difficult. It is sensitive to many unknown factors. So we need a good strategy for trading with deep learning. That's where reinforcement leaning comes in. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over.\nBy the end of the talk, you will learn:- What trading is? Why it's hard? How Can Deep Learning solve the trading problem? Why is reinforcement learning an effective solution?", - "Last Updated": "11 Jun, 2018", - "Prerequisites": " Willingness to learn Basic python", - "Section": "Data science", - "Speaker Info": "I have always been amazed by computers and how much you can do with soo little. Curiosity lead to passion. Passion lead me to work on some amazing things. AI is the buzzword around and I have been working on AI for quite some time and it's been a really great journey, challenging but rewarding. Recently, I started working with some startups. Currently, I'm working for a Silicon Valley startup, who has been working on making serious predictions on small data. I have also been interested in Fintech data. I started with simple fraud detection models and now I'm working on solving the trading problem with reinforcement learning", - "Speaker Links": "Connect on Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Himanshu Singh (~himanshu61)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-trade-with-reinforcement-learning~enX5b/", - "title": "Learning to Trade with Reinforcement Learning" - }, - { - "Content URLs": "https://www.tensorflow.org/ https://github.com/aymericdamien/TensorFlow-Example", - "Description": "Hey everybody!\nIf you have ever heard of this thing called as neural network , than this workshop is definitely for you .Neural networks are not new they been there for a long time . but they have become quite famous recently\ntensorflow is consisdered one of the best frameworks for getting started with neural networks and deep learning . About TensorFlow TensorFlow\u2122 is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google\u2019s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. We will also try and build an image recognition model using deep learning from scratch . Tensorlfow helps getting started with deep leaning and building neural networks ", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basics of python and an open mind to learn new things ", - "Section": "Data science", - "Speaker Info": "Python lover . Machine learning enthusiast . Currently working on BIG ML ( training machine learning models on big data ) and efficient deployment of machine learning models on production ", - "Speaker Links": "Contributor at https://github.com/polyaxon/polyaxo", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-build-neural-networks-from-scratch-using-tensorflow~boKYb/", - "title": "Learning to build Neural networks from scratch using tensorflow" - }, - { - "Content URLs": "GitHub More content will be updated soon", - "Description": "What is Transfer Learning? Transfer Learning is the method of reusing our existing knowledge developed for one task to solve a similar task. Say, you want to detect cars on night-time images and instead of learning from scratch we could reuse our existing knowledge from a model which has been trained on day-time images. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. I believe Transfer Learning is a major achievement in our quest for Artificial General Intelligence (AGI) as Transfer Learning allows us to generalize our knowledge which is something we humans excel at. Andrew Ng, ex-chief scientist at Baidu, co-founder of Coursera and professor at Stanford, said during his widely popular NIPS 2016 tutorial, \u201cTransfer Learning will be the next driver of ML success.\u201d Training Deep Neural Networks from scratch is an expensive process. Not only does it require a lot of compute resources and time, deep Learning models require a huge amount of data and it is a major bottleneck when it comes to start-ups and niche areas of research like health care. What you will learn :- How to build an image classifier in a few minutes using Transfer Learning When and how to fine-tune pretrained models Freezing layers of a pretrained model depending upon the scenario Using ConvNet as a feature extractor Using differential learning rates Constraints of using pretrained models Transfer Learning : Beyond Computer Vision Cross-Lingual Domain Adaptation : Using the knowledge we have learnt from one language and applying our knowledge to another language is another application of transfer learning with huge potential. Cross-lingual adaptation methods would allow us to leverage the vast amounts of labeled data we have in English and apply them to any language, particularly languages with very less labeled data such as Indian languages. Reinforcement Learning and Learning from Simulations : Training an agent (in Reinforcement Learning) to achieve general artificial intelligence directly in the real world is too costly and hinders learning initially through unnecessary complexity. It is better to train an agent in a simulated environment such as the OpenAI Gym before deploying it in the real world. Eg: Self-driving cars Agenda 1.Introduction to Computer Vision (3 min) 2.Introduction to Transfer Learning (3 min) 3.Why should you use Transfer Learning? (2 min) 4.When to use Transfer Learning? (2 min) 5.Build an image classifier in minutes using Transfer Learning (2 min) 6.Effective Transfer Learning techniques (6 min) 7.Feature Extraction using pretrained models (3 min) 8.Constraints of using pretrained models (1 min) 9.Transfer Learning beyond Computer Vision (3 min) 10.Transfer Learning : A right step towards Artificial General Intelligence (AGI) (2 min) 11.Q&A session (3 min", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of deep learning Love for Pytho", - "Section": "Data science", - "Speaker Info": "Hi! I\u2019m fascinated by AI and it\u2019s applications particularly in art and culture - generating art, fashion styles, music, literature, etc. I\u2019m a 3rd year student at SRM Institute of Science and Technology, Chennai studying Computer Science Engineering. I\u2019m also part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in AI, Blockchain, Computational Biology, Electrical Systems, Internet of Things, and Mixed Reality. I'm also a part of a club which organizes PyData KTR . I will be talking about \"Abstract Art using Compositional Pattern Producing Networks\" in the next meet-up which is scheduled on 14th July, 2018. I\u2019m currently working as a Computer Vision intern at Cogknit Semantics, Bangalore. I'm working on a fashion recommender system which analyses images of clothes and suggests matching clothes to go along with it. Eg: Suggests matching pants and shoes if the input image is a shirt. I love Python because of it\u2019s simplistic philosophy and lucid coding style which allows me to think more about model architectures rather than fixing bugs in my code", - "Speaker Links": "Connect with me on LinkedIn Find me on GitHub Follow me on Twitter E-mail me at : niladrishekhardutt@gmail.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "niladri99", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-subtle-art-of-effective-transfer-learning~dw5ra/", - "title": "The Subtle Art of Effective Transfer Learning" - }, - { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "Problem description : Deep learning algorithms have shown great results in speech recognition domain, So here we have used deep learning techniques to enable the machines to read the lips from a video without sound better than humans. By analysing the movement of lips of a person we are trying to predict what that person is trying to speak.\nAutomated Lip reading can be helpful in many ways. Some of them are: Silent dictation in public spaces. Covert conversation. Helping the people with speaking ade in talking to other people. Improved hearing aids. Speech recognition in a noisy environment. The talk will be focused on : How the problem should be tackled. Discussion of different phases Algorithms and python libraries used for implementation.", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations Basic understanding of Recurrent Neural Networks : An excellent resource to understand this is Understanding LSTM Networks . Similar to CNN the motive should be to understand the basic working of Recurrent Neural Networks. The coding part will be discussed in the talk.", - "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saqhas", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-lip-reading-using-convolutional-neural-networks-in-python~ejMvd/", - "title": "Automated Lip reading using convolutional Neural Networks in python" - }, - { - "Content URLs": "GitHub Repo: https://github.com/sleebapaul/gospel_of_rnn.git Google Colab Notebook: https://drive.google.com/file/d/1qh94MdQr9SeTLxGkMJc6kZGguRID8LqW/view?usp=sharing Blog: https://sleebapaul.github.io/rnn-tutorial", - "Description": "Language modeling was a complex task of previous days. But advancements in Deep Learning has solved this problem very effectively. Using Recurrent Neural Networks architecture, I've built a language model which can effectively generate the fifth gospel of bible by learning from four existing gospels. This model is also able to divide verses and chapters along with meaningful passages", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Recurrent Neural Networks basics Deep learning basics Language modeling basics Familiarization with PyTorch", - "Section": "Data science", - "Speaker Info": "Sleeba Paul is a Power System graduate and published researcher who loves intelligent machines. He currently works as a Machine Learning Engineer at Refly; an AI startup in India where he works on content enhancement and video analytics", - "Speaker Links": "Personal website: http://sleebapaul.github.io/ LinkedIn: https://www.linkedin.com/in/sleebapaul/ Github: https://github.com/sleebapau", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sleeba Paul (~sleeba)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gospel-of-lstm-how-i-wrote-5th-gospel-of-bible-using-lstms~elLMe/", - "title": "Gospel of LSTM : How I wrote 5th Gospel of Bible using LSTMs" - }, - { - "Content URLs": " Research Paper Github repository of project with over 100 stars: pyCAIR Beta release on PyPI: pyCAIR Docs: pycair.readthedocs.io", - "Description": "In this talk, I will speak about a simple yet very powerful image manipulation mechanism. The naive user utilizes the services of any standard toolkit, be it a web service or a remote application for image manipulation. The black box approach to this process is: A user provides an image and other parameters as input to the toolkit which in turn produces the results and returns it back to the user. Often these results are not up to the mark. The image sometimes gets distorted, misaligned or blurred. Deviating from the standard mechanisms, I would like to talk about a technique called as Content aware image resizing . The primary factor in this technique is the content . It is the content which drives the entire technique. The image is cropped, enlarged or modified keeping in mind the primary factor. I will talk about an algorithm called as Seam Carving which is used under the hood to achieve the aforementioned technique. It is this algorithm and the power of Python libraries , that makes this technique perform better than the standard mechanisms. Agenda of Talk: Introduction: Basics of seam carving, how the algorithm works Understanding energy concepts, basics of computer vision and dynamic programming Walk over the pseudo-code and dry run of algorithm Comparative analysis of this technique with standard mechanisms Q&A Session Conclusion", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pycair-understanding-content-aware-image-resizing-using-python~bkK6b/", - "title": "pyCAIR: Understanding Content-Aware Image Resizing using Python" - }, - { - "Content URLs": " Hello world of chatbots world - wordbot An Experiment with Opensource chatbot engine - RASA NLU ", - "Description": "Google Assistant and Siris\u2019 of the world have tickled our curiosity enough to deep dive and understand under the hood technologies that make a chatbot. Though we don\u2019t have Google level of data to create a generalized chatbot, we can use the existing NLP engines and create chatbots that produce valuable results in a specific domain. For eg., anything that goes in your FAQ page can be converted into content for a chatbot. In this talk, I\u2019ll share my 2-year journey with chatbots. Existing bot platforms and how to leverage it to build your own chatbots. I'll also share the internals of an opensource chatbot engine - Rasa NLU. Key Takeaways Chatbot\u2019s architecture (3 mins) Natural language Processing, Understanding, and Generation what and how it plays an important role in building chatbots(3 min) How to use existing chatbot engines to build a chatbot(6 min) Internals of a chatbot engine - Demystifying RasaNLU (15 mins)", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of Pytho", - "Section": "Data science", - "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape - Tech Enthusiast - Django & Chatbot specialist - Mentor/Speaker Build2learn , Chennai Geeks. Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", - "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavan", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Bhavani Ravi (~bhavaniravi)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatbots-101-by-demistifying-rasanlu~bm6Gd/", - "title": "Chatbots 101 - By Demistifying RasaNLU" - }, - { - "Content URLs": "Source code available on Github: https://github.com/Cheukting/Style-mimicking-text-generator Example slides: https://slides.com/cheukting_ho/pylondinium1", - "Description": "Computers are getting closer to speak like humans. But can we even make them speak in particular ways, like as Trump or Shakespeare? In this hands on talk we will see how this is possible with the latest deep learning techniques combined with word embeddings and other advanced NLP technique. In this talk, first we would introduce two neural network and machine learning mechanisms which in popular and widely used in NLP (natural language processing): Word Embeddings and Recurrent Neural Network. Word Embeddings is a way to extract the context of a word by \u201clearning\u201d its presence in a paragraph; while Recurrent Neural Network, including LSTM (long short-term-memory), enable us to \u201ctrain\u201d sequential data. After that, we will showcase how to implement these mechanisms in a neutral network. With that, we can \u201cbuild\u201d a machine to generate articles, plays or speeches in the style of the training corpus and have lots of fun. In the first half of the talk, concepts of how Word Embeddings and LSTM works will be explained. Audiences will understand why this is essential in the field of NLP and why we are using it. In the second half, a code demo will be used to showcase how to implement these mechanisms. Through an example, audiences will learn how Keras is used together with Tensorflow and Python to build a sequential neutral network. We will showcase generating a paragraph using Shakespeare\u2019s play and another one using Trump\u2019s speech. This talk is for people who have some experience with data science and understand the concept of how a neural network works, but would like to go deeper into the details of how does it applied to NLP to solve more complex AI problems. We used very simple code but did a complex task like text generation, that opens the door for a lot of people who wants to experiment with deep learning", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "Basic concepts of Neural Network like Stochastic Gradient Descent and back propagation, as it will not be covered in the talk due to time limit", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-keras-building-an-ai-that-talks-like-shakespeare-or-trump~enX7b/", - "title": "Deep Learning with Keras : Building an AI that Talks like Shakespeare or Trump" - }, - { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/seatgeek/fuzzywuzzy Source code available on Github: https://github.com/Cheukting/fuzzy-match-company-name Slides (not finalized): http://slides.com/cheukting_ho/fuzzy-matchin", - "Description": "Ever encounter a tricky situation of knowing there\u2019s names that are the same, but matching strings straight away leads you no where? All you need is FuzzyWuzzy, a simple but powerful open-source Python library and some wit. This talk will demonstrate how to efficiently fuzzy match company names. Matching strings should be one of the first natural language processing problem that human encounter since we start use computer to handle data. Unlike numerical value which has an exact logic to compare them, it is very hard to say how alike two strings are for a computer. One may compare them character by character and have an idea of how many characters in the pair of stings are the same. Unfortunately in most application we need computer to perceive strings like we do and therefore we have to use fuzzy matching. Fuzzy matching on names is never straight forward though, the definition of how \u201cdifference\u201d of two names are really depends case by case. For example with restaurant names, matching of words like \u201ccafe\u201d \u201cbar\u201d and \u201crestaurant\u201d are consider less valuable then matching of some other less common words. Also, do we consider company names that matches partly (like \u201cHappy Unicorn company\u201d and Happy Unicorn co.\u201d) are the same? In the first half of the talk Levenshtein Distance, a measure of the similarity between two strings, will be explained. Different functions in FuzzyWuzzy like \u201cpartial_ratio\u201d and \u201ctoken_sort_ratio\u201d will also be explored and compared for difference. It is very important to understand our tool and choose the right one for our task. Then in the second half, we will start tackling the example problem: matching company names, we will show that besides using FuzzyWuzzy, we have to also handle problem like finding and avoid matching of common words and speeding up the matching process by grouping the names. By combining all tricks and techniques that we demonstrate, we will also evaluate how efficient this method is and the advantage of using this method. This talk is for people in all level of Python experience who would like to learn a trick or two and would like to be able to solve similar problems in the future. Theory of how the library works will be explained and It is easy to be pick up even for beginners", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fuzzy-matching-smart-way-of-finding-similar-names-using-fuzzywuzzy~epKVd/", - "title": "Fuzzy Matching - Smart Way of Finding Similar Names Using FuzzyWuzzy" - }, - { - "Content URLs": "Project source code on Github: https://github.com/Cheukting/GCP-GPU-Jupyter Demo code: https://github.com/Cheukting/jupyter-cloud-demo Example slides: https://www.slideshare.net/CheukTingHo/pycon-israel-launch-jupyter-to-the-clou", - "Description": "There are lots of reasons using a cloud service is favorable, but how to make sure consistency between development and deployment? With Docker and Terraform, we can create the same environment on cloud easily. For example, we will deploy a Jupyter notebook on Google Cloud Platform using both tools. In this talk, we will use a task: hiring a GPU on Google Cloud Platform to train neural network, as an example to show how an application can be deployed on a cloud platform with Docker and Terraform. The goal is to have Jupyter Notebook running in an environment with Tensorflow (GPU version) and other libraries installed on a Google Compute Engine. First we will briefly explain what is Docker and what is Terraform for audiences who has no experience in either or both of them. Some basic concepts of both tools will also be covered. After that, we will walk-through each steps of the work flow, which includes designing and building a Docker image, setting up a pipeline on Github and Docker Hub, writing the Terrafrom code and the start up script, launching an instance. From that, audiences will have an idea of how both tools can be use together to deploy an app onto a cloud platform and what advantages each tool can bring in the process. This talk is for people with no experience in application deployment on cloud service but would benefit form computational reproducibility and cloud service, potentially data scientists/ analysts or tech practitioners who didn\u2019t have a software developing background. We will use an example that is simple but useful in data science to demonstrate basic usage of Docker and Terraform which would be beneficial to beginners who would like to simplify their work flow with those tools", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Developer tools and Automation", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/launch-jupyter-to-the-cloud-an-example-of-using-docker-and-terraform~boKXb/", - "title": "Launch Jupyter to the Cloud: an example of using Docker and Terraform" - }, - { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/networkx/networkx Slides (not finalized): https://docs.google.com/presentation/d/1y_Wmuv_hqs8OZTI8XLJ5ajvjEpllK7Xeifa52yTpw-k/edit?usp=sharin", - "Description": "When you make a search for a hotel room, do you know how many travel agents are searching for you at the same time? In this talk, we demonstrate how to use the millions of searches a sourcing company received to build a network of travel agents and finding the main hubs among them using NetworkX. Network analysis is getting more and more attention in Business Intelligence, people hope to get information out of the structure of an organization or a communication network. In this talk, we use the hotel room search requests from travel agents, including online public website, B2C, B2B and B2B2C, to build a relational network among them. By using this network as an example, we demonstrate how insights can be extract by studying network properties. In the first half of the talk, we will explain how the network is built using NetworkX, an open-source python library that is designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. When 2 agents are making the same search at the same time , a link ( or an \u201cedge\u201d in network analysts terms) is made pointing form the initial searcher to the subsequent searcher. Using a list of these searches, a directed graph is built. We will also demonstrate how to pick the biggest connected component out form the graph. In the second half, with the graphs created, we show how different functions of NetworkX can be used to study the graphs. By compare the graph properties of our graph to the other popular network graphs, we can get the insight of how the network was created. Also by studying the graphs, we can understand the behavior of the agents and can even figure out which agents are acting as main hubs in the network. This talk is for people who are interested in network analysis and would like to see how it can be used in a business case. Audiences with any level of python experience can learn some basic concept of network analysis work and how it can be applied to provide business insights", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-understanding-agent-connections-using-networkx~bq5pb/", - "title": "Case Study in Travel Business - Understanding agent connections using NetworkX" - }, - { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/welch/seasonal Example Slides: https://www.slideshare.net/CheukTingHo/pydata-amsterdam-2018-time-series-analysis-with-seasonal-data-9909335", - "Description": "For time series analysis, everyone\u2019s talking about ARIMA or Holt-Winters. But there\u2019s other models which could also break down a seasonal series into trend, seasonality and noise. We will use an open source Python library called Seasonal to analyse B2B worldwide travel data. Times series analysis is an important part of data analysis for lots of businesses. It is very often for stakeholders to be interested in the performance of the business by analyzing measurements of profit, cost, number of sale, number of searches etc over time. In this talk, we will do a case study of showing how we estimate the impact public holidays made on the travel business. The method of analyzing the time series by seasonal breakdown will be explored and the work flow of solving the problem will be explained. In the first half of the talk, an introduction about time series and its characteristic will be explained for audiences who is new to analysis on time series. The data we use will be from a business to business travel company. It has seasonality thought out the year, a weekly cycle and also a growing trend in business. As the company have clients around the world, data from different countries will shows different behaviors as well. Therefore, before we show the analysis, the complexity of the data will be explored. In the second half, we will introduce a open source Python library called Seasonal. Using this package, we will demonstrate how to break down the travel data and extract the fluctuation of the sale in different countries. By comparing the fluctuation and Google calendar, public holidays in different countries can be spotted and their impact on the business can be estimated. This talk is for people who are interested in time series analysis and its application in business. Audiences with or without experience would also found this talk useful in giving them insights in how a business could benefit in making use of the data and doing a proper time series analysis", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-time-series-analysis-with-seasonal-data~er5pd/", - "title": "Case Study in Travel Business - Time Series Analysis with Seasonal Data" - }, - { - "Content URLs": "Apache_Build_Monitor Jenkins' REST API & Pytho", - "Description": "As a build and release engineer, have you felt how good it would be to know the status of scheduled nightly builds before you reached office ? As a developer, have you wondered, while you were away from the desk, what's the status of quality gate builds that should be passed before the changes can be integrated to the mainline ? Intent of this talk is to outline what's offered via Jenkins's REST API and showcase some of the possibilities by consuming the API using Python", - "Last Updated": "16 Jun, 2018", - "Prerequisites": " Read-up docs on Python libraries XML, JSON Capability to follow and assimilate code snippets", - "Section": "Developer tools and Automation", - "Speaker Info": " Speaker works for a CyberSecurity firm in Bengaluru, India Likes being outdoors and reading books.", - "Speaker Links": "Linkedi", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ramanathan Muthaiah (~ramanathan)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/consuming-jenkinss-rest-apis-in-python~dw58a/", - "title": "Consuming Jenkins's REST APIs in Python" - }, - { - "Content URLs": " Code will be updated on github very soon.", - "Description": "There are many framework available in the market for free and with a lot\u2019s of feature like Django , Flask , Tornado . These framework help us to build web application and serving the files over the network without worrying about the low level details like how it works , how the files are being severed to the clients , web browser and how it handles the clients to be connected and serving the data to the lot\u2019s of clients with minimum amount of time with managed thread. So in this talk I\u2019ll share my knowledge how does the web server work and how we can build our own framework like other available framework and further enhance it , to make it big, and to handle the clients with multiple processes and threads. In this talk I will be talking about : What is a WebFramework and How does a web framework work? How we can make a simple web sever to serve the \u201chello world\u201d webpage to the browser How we can make the HTTP custom request header to tell the browser about the current status of request on the different situation like 200 , 404 , 500. how to server files like html, css to generate the advance webpages using socket to the browser. Getting the requested URL Params and serving the files over the network. Making a Download link and let the user to download the files over socket. Improvement of request and response time of the web server and optimising it so that the web server can handle more and more clients over the network. ", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "1. Basic python understanding. 2. Python installed on your system. 3 .Socket library (you can install it using the pip installer", - "Section": "Core python and Standard library", - "Speaker Info": "I am Nawneet Kumar, CTO at Elezire Technologies Pvt. Ltd. I have worked in Different Projects and in Different Languages in my past year. I have worked in era like IOT Development , Android Application Development , IOS Development and Web Development", - "Speaker Links": "Linkedin : https://www.linkedin.com/in/nawneet-kumar-77b64814b/ github : https://github.com/navSharma4", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "nav.sharma47", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-own-webframework-like-django-flask-tornado-to-serve-web-application-using-core-socket-programming~av55e/", - "title": "Building Own WebFramework like Django , Flask , Tornado to serve Web Application using Core Socket Programming" - }, - { - "Description": "We have a word for it now - Domotics . The fun started a year back when I laid hands on this beautiful device from Amazon, which could not only manage your music, reminders, lists but also make calls and send messages. Basically, a smart phone in the cloud to be used without hands. But a developer sees endless possibilities with this powerful tool. Although speech recognition technology itself is nothing new, Amazon Echo has made its way to the homes of regular consumers. This talk is specially focused on giving a head start to the attendees about building and using powerful applications in python using an Alexa device. Being a python developer for the past 10 years and working on alexa skills for the past year, I intend to share my experience with the python community and enthusiasts. Broadly, this talk will be covering the following topics: How the echo framework and Alexa skills work An introduction to creating alexa skills in python with flask-ask Handling requests , responses , contexts and sessions . Testing applications with ngrok and deploying to the cloud. A sneek peek into other home automation possibilities like micropython embedding with popular microprocessors. The talk would be illustration and example driven and will include demos of cool app(s) I have been working on", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "This talk is intended for developers who have a decent grasp on the basics of the python framework and trends, although you do not need knowledge of any specific packages or libraries. Just an enthusiastic mind is enough! The primary takeaway of this talk would be learning how to get started ideating and building applications for an alexa enabled smart home device and discuss some cool developer tips", - "Section": "Developer tools and Automation", - "Speaker Info": "Sonal Raj ( @_sonalraj ) has been an avid pythonista for 10 years. He has been working as an integral part of the financial technology industry for the past 4 years. Sonal holds a masters in Information Technology and has been a research fellow at the Indian Institute of Science, Bangalore. His domains of interest include distributed systems and graph databases, and he loves to explore new gadgets and develop new technology. He is also the author of the best selling book 'Neo4j High Performance' ", - "Speaker Links": " Talk at PyCon India 2014 Talk at PyCon India 2013 Real Time Computation with Apache Storm - IISc Bangalore Human Computer Interaction Systems : Slides Website Github Reasearch Profile", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sonal Raj (~sonal)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/alexa-enabled-smart-home-programming-with-python~dy5nd/", - "title": "Alexa enabled smart home programming with Python" - }, - { - "Content URLs": "http://github.com/gnsrikanth/simplelinuxbackdoor/ https://medium.com/@gnsrikanth/creating-a-tcp-backdoor-using-python-9edafc213f9", - "Description": "In this talk, we discuss how python scripts can be used in the world hacking. Python can be used to automate many tasks and we see network protocols using python. Programming isn't just codes, but it's a way of communication. This talk is more of an awareness about the possibilities of python can be used and hacking is one of them. We break down steps to hack a system and automate tasks using python. Topics covered: Sockets in python Using TCP, UDP protocols and creating a Server/Client A basic backdoor for windows Using HTTP protocol to steal users data Using encryption to obfuscate network traffic Subprocess module Pyinstaller to make binaries of malware Bypassing antivirus (we will test it by uploading .exe to virustotal) Using Sqlite3 to retrieve chrome passwords Emailing subprocess outputs with python Send data to google forms as POST Simple Ransomware code Other Python tools for hacking", - "Last Updated": "16 Jun, 2018", - "Prerequisites": "Basics in python, Operating system fundamentals, Networking basics", - "Section": "Networking and Security", - "Speaker Info": "I am Grandhi Srikanth, and truly passionate in cyber security. I hold C|EH, CCNA in Routing and Switching, Cyber Ops certification and interested in creating malware codes and as python makes it simple, I use python", - "Speaker Links": "Twitter: @gn_srikanth LinkedIn: https://www.linkedin.com/in/grandhi-naga-srikanth/ Github: https://github.com/gnsrikant", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Naga Srikanth Grandhi (~naga_srikanth)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/backdooring-windows-with-python~ax5Bb/", - "title": "Backdooring windows with python" - }, - { - "Content URLs": "A library for ANTLR that is being built by me is available here: https://gitlab.com/virresh/coala-antlr ANTLR's official page: http://www.antlr.org/ My blogs related to ANTLR in Python: https://virresh.wordpress.com/tag/antlr/ An example calculator: https://github.com/virresh/ANTLR4-Exampl", - "Description": "This talk aims at introducing ANTLR for python 3, and talk about Abstract Syntax Trees. It will present an overview of the process, the intricacies and will end with a concrete example to show the utility. ANTLRv4 is a tool that can generate parse trees for any compatible grammar, and provide tools to walk through that tree, so I will illustrate how to use that rather than dwelling more on the theory aspect of the parse trees and boost up the development of language tools. There is a speciality with ANTLRv4, we can separate context from the grammar (so we can get very close to the expectation that grammars are context free). I expect the session to be beginner friendly so no pre-requisites save some basic python expected. Also I will cover some basic examples, and also a demo of an actual language grammar to create a meta-program if time permits. The session is expected to have the following things: What is a grammar ? What are Parse trees and how do they compare to ASTs ? What is ANTLR ? (The parser generator and the runtime provided) How do we use a parse tree ? (dwelling on setting up the environment for ANTLR based development and a short, basic calculator building example) Visitors and Listeners A short real world example on detecting technical constricts in actual programming languages (probably Python itself)", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "A working knowledge of python basics and some familiarity with some sort of command line interface is ideal (best suited if you are familiar with any unix/linux based systems, simple script invocation etc", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm a student presently pursuing BTech in CSE at IIIT-Delhi, and am a GSoC student this year at coala.io and have been programming various stuff using python for around two years. I am developing a library to facilitate easy usage of ANTLR for building linting tools. I've worked on a large array of technologies in any area that I get to know about, ranging from Full stack development, to Systems programming to Language tools. I do my best to pick up and experiment with whatever technologies I can, and I love to learn ", - "Speaker Links": "GitHub: https://github.com/virresh Website: https://virresh.github.io/ Blogs: https://virresh.wordpress.com/ LinkedIn: https://www.linkedin.com/in/virresh", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viresh Gupta (~virresh)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-antlr-with-python~az5ye/", - "title": "Using ANTLR with python" - }, - { - "Content URLs": "Will be provided soo", - "Description": "Everyone need not to know everything to build something great. If you are a student and wants to build a major/minor or a professional level project without worrying about the DevOps/Servers and its cost. If you are a Data Scientist and works with files/data and want to make your analytical tool public but you don't want to get in Server handling and learning some web framework . If you are a Frontend developer or work in a fast paced organisation where shipping out fast, better, robust and always running services are required. If you want to prepare a POC or a working model API fast without the requirement of server engineer. Then, this Talk is the place which your are looking for. This talk will be focused on How one can build really scalable and robust web APIs without learning any web framework that too in a very very easy manner. We will be talking about a python package I have made called Lamlight which makes the process of building web APIs as simple as a Git push . This package provides a CLI tool and answers the limitations imposed by the services like AWS lambdas . Lamlight enables Developer to: Make web APIs without learning any web framework or DevOps. Just focus on the core business logic because everything else it will provide you. (Eg: full python boilerplate, CLI automation tool ) Live code Changes. Put large dependencies on your Serverless web api like Numpy, Scipy, Pandas. Save 80% of time by making the process as simple as Git push. Objective of the Talk: Problems faced in a Servered Architecture. Introduction to Serverless Web APIs. Why Shift to Serverless Web Architecture. Platforms providing these Services and their limitations. Get Faster and beat these Limitations. Problems solved by Lamlight. Explanation of its working. Live demo. Q & A The talk would be extremely beneficial for students, Algorithm developer, Frontend Developer, Data scientists and others who are not familiar with server side development and server technologies or want to save time of server handling but still want their work to be done", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Love for Python Linux AWS(Optional)", - "Section": "Developer tools and Automation", - "Speaker Info": "Hello I am Rohit Negi. I am a developer with 1 year of professional experience and +2 years of freelancing experience. I have a Bachelor's degree and I am currently working as a developer in Elucidata Corporation, where I work on making technical architectures for the system to get connected and work robustly , designing Server APIs, Working with Frontend technologies like Angular to make the robust Frontend apps. I am very passionate about creating new and better stuff", - "Speaker Links": " https://www.linkedin.com/in/rohit25negi/ Email: rohit25.negi@gmail.com", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rohit Negi (~rohit17)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lamlight-develop-webmobile-apps-without-learning-django-flask-and-any-other-web-framework~egKke/", - "title": "Lamlight: Develop web/mobile apps without learning Django, Flask and any other web framework" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1_hyRLHdITpIMzhAbpxuaTQkm6qop4ZWQt6ERGW4MFag/edit?usp=drivesdk&ouid=10471550379351873801", - "Description": "This is a simple talk about web scraping using python.In this lecture we going to have a clear picture of webscraping. \nBy the end of the lecture audience are going to have a clear picture of \nWhat is web scraping? \nWhat is the use of it? \nWhat are the useful libraries in python for web scraping? \nPros and cons of the libraries\nAnd mainly how to parse the Websites with practical examples", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "A little amount of python knowledge is useful but not mandatory. I'm going to explain right from the very beginnin", - "Section": "Others", - "Speaker Info": "I am a student of Vishnu Institute of technology, Bhimavaram. I am studying 2nd IT. I was fallen in love with coding when I listened to the 1st lecture of my academic about C programming. That day changed my life. I have been working on python from January 2018.\nI am a quick learner, self disciplined, self motivated guy. \nMy hobbies are coding and learning new thing", - "Speaker Links": "https://www.sololearn.com/Profile/495149", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Deepak Puppala (~deepak12)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping~bDrKe/", - "title": "WebScraping" - }, - { - "Content URLs": "Will share the Slides post my Talk through a proper channel", - "Description": "Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. Note: In this workshop all the implementation will be done using PYTHON Session Takeaways: How to use different features of AWS to create your Serverless Application. What is Serverless Computing and how \"Functions as a Service\" is a revolutionary way to develop applications. Understand AWS Lambda Functions, the FaaS offering on Amazon Web Services. Understanding of the AWS services - Lambda, S3, EC2, CloudWatch, API Gateway, RDS, IAM How to access the AWS services using Python libraries in the Lambda Function. Hands On Cloud Native Web Applications Development using AWS Lambda and other offering. Practical examples of how you can combine multiple services and events in AWS and develop applications rapidly using AWS Lambda Functions", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Python: Basic of Python Programming Basics of Python Libraries Usages (Imports) AWS Free Tier account - https://portal.aws.amazon.com/billing/signup?redirect_url=https%3A%2F%2Faws.amazon.com%2Fregistration-confirmation#/start", - "Section": "Web development", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ritu Mehra (~ritu86)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/serverless-application-development-using-aws-and-python~eEvga/", - "title": "Serverless Application Development using AWS and Python" - }, - { - "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. You can find the introduction slides here ", - "Description": "SymPy is a Python library for symbolic mathematics. It aims to be an alternative to systems such as Mathematica or Maple while keeping the code as simple as possible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.\nThe talk will highlight the following: SymPy, what it is and how it is different from others. What is symbolic computation and how SymPy achieves it. Power of SymPy: Symbolic manipulations Equation solving Calculus Linear Algebra ", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Basic mathematics, just enough to appreciate the manipulation done by the computer algebra system and Python. No prior knowledge of SymPy or other Python libraries is required", - "Section": "Data science", - "Speaker Info": "SymPy India developers will be conducting the talk: Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers module", - "Speaker Links": " Resource repository: https://git.io/sympy-pycon-india-18 SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://youtu.be/5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://youtu.be/nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://youtu.be/AqnpuGbM6-Q SymPy, SciPy 2014: https://youtu.be/Lgp442bibDM Symbolic Computing with SymPy, SciPy 2013: https://youtu.be/dAgShwIx72c", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Yathartha Joshi (~Yathartha22)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-sympy~dGxJe/", - "title": "Symbolic Computation with SymPy" - }, - { - "Content URLs": " Hydra Draft Book of Hydrus Hydra Ecosystem Wiki Hydrus Hydra Flock Demo Hydra CG homepage I'll be sharing my slides after the talk", - "Description": "Introduction 3rd generation Web APIs enables creation of truly RESTful services with all its benefits in terms of scalability, maintainability, and evolvability. This allows to create Generic Consoles and loosely coupled clients. The main objective of this talk is to provide an overview of Hydra and Hydrus and how we can create such APIs using Hydrus. Hydra Building Web APIs seems still more an art than a science. How can we build APIs such that generic clients can easily use them? And how do we build those clients? Current APIs heavily rely on out-of-band information such as human-readable documentation and API-specific SDKs. However, this only allows for very simple and brittle clients that are hardcoded against specific APIs. Hydra, in contrast, is a set of technologies that allow us to design APIs in a different manner, in a way that enables smarter clients. Hydrus Hydrus is a Flask server meant to build and deploy Hydra-based Web APIs in a straightforward and effective way. Hydrus utilises the power of Linked Data to create a powerful REST APIs to serve data. Hydrus uses the Hydra draft standard for creation and documentation of it's APIs. The flow of the talk will be as follows: My Introduction What is Hydra Draft? A detailed introduction to Hydrus How can Hydrus be used to create Semantic Web APIs easily? Some Use Cases A short demo Q/A session", - "Last Updated": "18 Jun, 2018", - "Prerequisites": " Python Basic knowledge of Web APIs", - "Section": "Web development", - "Speaker Info": "My name is Akshay Dahiya. I'm a Mentor and Organization Admin for Python Hydra in Google Summer of Code 2018 and I love working on Semantic Web and Artificial Intelligence-related projects. I also mentor a couple of students across various Udacity Nanodegree programs (FullStack Nanodegree, React Nanodegree and Deep Learning Nanodegree) in my free time", - "Speaker Links": " http://www.xadahiya.me/ https://github.com/xadahiya/ https://www.linkedin.com/in/xadahiya/ http://www.typingeek.com/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Akshay Dahiya (~xadahiya)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3rd-generation-web-apis-using-hydra-and-hydrus~dBpYa/", - "title": "Creating 3rd generation Web APIs using Hydra and Hydrus" - }, - { - "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. \nThe website for the workshop is here . \nYou can find the introduction slides here , the sphinx tutorial here and the exercises in form of IPython notebooks. Note: The notebooks are hosted statically, you can download from here and run locally to have an interactive session. See Also: Workshop content for PyCon conference in 2015 , SciPy conference in 2016 , 2014 and 2013 ", - "Description": "In this tutorial we will introduce attendees to SymPy, a computer algebra system (CAS) written in Python. We will show basics of constructing and manipulating mathematical expressions in SymPy, the most common issues and differences from other computer algebra systems, and how to deal with them. In the last part of this tutorial, we will show how to solve practical problems with SymPy. This will include showing how to interface SymPy with popular numeric libraries like NumPy. Attendees will take home an introductory level understanding of SymPy. This knowledge should be enough for attendees to start using SymPy for solving mathematical problems and hacking SymPy's internals (though hacking core modules may require additional expertise). SymPy is a pure Python library for symbolic computation. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. The tutorial will cover the following topics and more. Introduction What is Symbolic Computation? A More Interesting Example The Power of Symbolic Computation Why SymPy? Gotchas Symbols Equals signs Two Final Notes: ^ and / Basic Operations Substitution Converting Strings to SymPy Expressions evalf lambdify Printing Printers Setting up Pretty Printing Printing Functions Simplification simplify Polynomial/Rational Function Simplification Trigonometric Simplification Powers Exponentials and logarithms Special Functions Calculus Derivatives Integrals Limits Series Expansion Finite differences Solvers A Note about Equations Solving Equations Algebraically Solving Differential Equations Matrices Basic Operations Basic Methods Matrix Constructors Advanced Methods Advanced Expression Manipulation Understanding Expression Trees Recursing through an Expression Tree ", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "The tutorial will only assume a basic knowledge of Python. No prior knowledge of SymPy or other Python libraries is required, although it is suggested that attendees be familiar with the IPython notebook. A mathematical knowledge of calculus is recommended. We recommend that the attendees install the Anaconda Python distribution which includes SymPy, NumPy, and IPython. Once Anaconda is installed simply type the following in a terminal to install the necessary packages: $ conda install numpy ipython-notebook sympy Other alternative installation instructions can be found here: http://docs.sympy.org/dev/install.htm", - "Section": "Data science", - "Speaker Info": "SymPy India developers will be conducting the workshop: Shekhar Prasad Rajak : GSoC 2016 | Solvers Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers Module Ravicharan : IIIT Allahabad | Core Developer at SymPy, GSoC 2018 | Combinatorics module Jashanpreet Singh : TIET Patiala | Core Developer at SymPy, GSoC 2018 | Beam Bending module", - "Speaker Links": " Resource repository: https://git.io/sympy-pycon-india-18 SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://youtu.be/5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://youtu.be/nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://youtu.be/AqnpuGbM6-Q SymPy, SciPy 2014: https://youtu.be/Lgp442bibDM Symbolic Computing with SymPy, SciPy 2013: https://youtu.be/dAgShwIx72c", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Yathartha Joshi (~Yathartha22)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-python-using-sympy~aAold/", - "title": "Symbolic Computation with Python using SymPy" - }, - { - "Content URLs": "Coming soon", - "Description": "Do you know, your favorite superheroes in Avengers , cute characters of Kung Fu Panda and the epic wars of Baahubali were brought to screen with the help of python ? If you are into gaming , you need to thank python for the characters you have played and the world you have explored. Even the next generation technologies like AR and VR use python to deliver their magic to you in new formats. It won't be a overstatement if we say python is the backbone of the animation Industry In this talk we go behind the scenes and see how our favorite programming language is used in the animation industry, why it plays a huge role and the kind of applications built with it", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "A bit of curiosity and interest in learning about usage of python in various industries, usually less represented in the python community", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/amazing-world-of-animation-powered-by-python~dLDrd/", - "title": "Amazing world of animation - powered by python" - }, - { - "Content URLs": "Coming Soo", - "Description": "It's really hard to escape the 3D buzzword. You find it used in all sorts of places, right from the movies you watch, Games you play, 3D printing , webgl graphics in the browser and VR , AR applications. In this workshop we are going to cover the basics of 3D and do a hands on session on creating 3D Art using a professional open source application called Blender . Of course, python is a major part of blender and we will put your python skills to some good use. What is this workshop NOT about : This is not one of your boring programming workshops. We are not going to try improve your python knowledge ten folds in a matter of 2 hours. What is this workshop about : Come to this workshop if you want to be a kid again and have fun creating art in 3D using Blender and Python !!! Who am I : Hello, Sreenivas here! I am a 3D artist turned programmer. I work in the animation and VFX Industry and battle production issues with the power of python. I love art, technology and excited about combining both. I support open source by evangelizing Blender and Krita . Who are you : You are a person with an open mind, bitten by the curiosity bug and intrigued by how 3D Art is made. You have at least basic knowledge of python and ready to use your super powers to create 3D Art. Takeaway : By the end of the session\u2026 You will know a broad overview of 3D Art . Have a working knowledge of the professional open source 3D application, Blender . Get a deeper understanding of the workflow for creating 3D art. Use your python skills in the process of creating 3D Art.", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Laptop with a decent GPU (any modern laptop) A mouse with a middle click button (scroll which is clickable) Download and install Blender from https://www.blender.org/download/", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3d-art-using-blender-and-python~aKBxe/", - "title": "Creating 3D Art using Blender and Python" - }, - { - "Content URLs": "https://docs.openstack.org/infra/jenkins-job-builder", - "Description": "Jenkins job builder is an openstack project used for automation and reusing of templates in yaml and json to make jobs and subscribe them to Jenkins. People who like to save time on tedious details can use this open source software and live there life a little better", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Jenkins( a little bit )\nPython\nPip\nRelated libraries like PyYAML, Jinja etc", - "Section": "Developer tools and Automation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jenkins-job-builder-automating-jobs~aMgGd/", - "title": "Jenkins job builder - automating jobs" - }, - { - "Description": "Abstract: Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. The Big Question: \"Is everything Perfect in AWS Lambda?\" .... Well it depends on how you use it and this is what I will cover in my Talk. Note: This Talk will have some code references using PYTHON Outline: What will you learn from this session/talk: What are Lambda Functions . What are the different features of Lambda Functions. The famous Lambda Timeout . The Deployment and Resource Limits . The Cold Start issue and its workarounds. The Cost Factor Why do you need to know this: Helps develop decision making in the project design architecture The Case Study: Case Study in which you should/should not use Lambda Functions. Real Life project experience: The hidden learning with an on job project on the limitations to Lambda Function. Q&A ", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Python: Basics of Serverless Computing Basic of Python Programming Basics of Python Libraries Usages (Imports)", - "Section": "Others", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Ritu Mehra (~ritu86)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-lambda-with-python-dos-and-donts~dNjvd/", - "title": "AWS Lambda with Python : Do's and Dont's" - }, - { - "Description": "With examples build the concept of creating a language model using text data", - "Last Updated": "19 Jun, 2018", - "Section": "Data science", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "divya chowdhary (~divya69)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~aOkra/", - "title": "Language Model (Text Analysis) using Python from scratch" - }, - { - "Content URLs": "Github repository links will be updated soon", - "Description": "In this talk, I am going to talk about advanced concepts of Python related to Caching. A cache can be easily understood as a saved answer to a question. Caching can speed up an application if a computationally complex question is asked frequently. Instead of the computing the answer over and over, we can use the previously cached answer. Caching is an important component while scaling applications which are to be used by many users. It solves various problems related to cost and latency. Usually it takes more time to retrieve data from DB rather than cache. Using a cache to avoid recomputing data or accessing a slow database provides us with a great performance boost. I will describe in depth the different methods of Caching, their pros and cons. This talk will help developers focus on their code before scaling their applications. It will provide immense performance improvements with this simple concept. Outcomes: The novice audience will be able to understand basic Caching Mechanisms. They will be able to utiilize their knowledge which will serve pivotal while scaling applications Contents to be covered in talk: Local Caching: What is it, how to do it, example, built-in Python libraries: (using cachetools ), advantages, dis-advantages Memoization: What is it, pseudo-code algorithm, implementation using example, built-in Python libraries: (using lru_cache ), advantages, dis-advantages Distributed Caching: What is it, techniques: (using memcached , using pymemcache ) Agenda: Initial 10 minutes: Introduction to Caching and its various techniques. 10 - 20 minutes: Examples and code walk through for various techniques. 20 - 25 minutes: Comparative analysis of how caching is better than non-scaled applications. 25 - 30 minutes: Q&A session", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-caching-in-python~aQm9a/", - "title": "Understanding Caching in Python" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Note: This talk is co-presented by Koushik (me) and Shubham Rao Talk Summary: Bitcoin has become so mainstream these days. It unveiled the importance of decentralization. But how does Bitcoin work? It\u2019s because of its core technology called Blockchain. After the Internet, Blockchain technology is regarded as the next big revolution. This talk gives a hands-on demonstration of how Blockchain technology works by building a toy version from scratch. Outcomes: After this talk the audience should be able to understand the basic working principles of bitcoin. They will be able to leverage their knowledge as a starting point of open-source contributions to projects like Ethereum. This demonstration will consider three important features of Blockchain Technology. All these features are essential to blockchain technology and we will be building a minimal version in Python. Agenda: 0 - 5 mins:\n Blockchains are secure because they use SHA256 or SHA512 algorithm for cryptography. I will describe the logic behind these hashing algorithms and give some computational facts about them. 5 - 10 mins: \n I will use the Python library called \u2018hashlib\u2019 to implement the SHA256 algorithm in Python. This makes us to convert data into SHA256 hashes. 10 - 15 mins:\n The SHA256 algorithm is used to convert all the transactions and their details into a single hash. Once the everything is converted into a hash, this hash must be stored for future usage. After a new transaction is approved, this new transaction and its details are again converted into a new hash along with the previous hash. I will demonstrate the process of storing the hash and using it again for a new transaction. 15 - 20 mins:\n Here I will explain a basic working principle of blockchains and how linking the previous transactions with the new one helps in the their security. The hashes stored are called blocks and the process of liking the previous hash the new hash makes a chain like connection thus forming a Hyperledger. 20 - 25 mins:\n Later in the process of mining will be explained using the variable quantity called Nonce. This explains why bitcoin miners need high computation power to do Proof-of-Work. \nI will also cover a variety of essential terms and concepts through the course of the talk which haven\u2019t been detailed in the agenda. Also, I will use python module called 'TkInter' to build a basic GUI for our blockchain. Last 5 mins:\n Questions and further reading + code sharin", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Love for Python and acquaintance with its libraries", - "Section": "Core python and Standard library", - "Speaker Info": "Hi, we are Koushik and Shubham , two Computer Science sophomores with research interests in Decentralisation and Blockchains, also occasionally working in Artificial Intelligence and Machine Learning. As members of Next Tech Lab, QS Reimagine Award-winning, student-run lab from our University, we work in Satoshi Lab, which focuses on Blockchains. We regularly participate and give talks in paper-reading groups and meetups like PyData", - "Speaker Links": "Visit my profile on LinkedI", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "KOUSHIK BHARGAV M M Srinivas (~koushik_bhargav_m)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchains-from-scratch~dPl4d/", - "title": "Understanding blockchains from scratch" - }, - { - "Description": "for students,\nunderstanding data analysis with pandas, using ipython shell or terminal and jupyter notebooks", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "understanding of python scripts", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year B.tech(information science) student from Bangalore, Karnataka", - "Speaker Links": "https://github.com/pandyamaru", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marut Pandya (~pandyamarut)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-with-pandas~bWvxa/", - "title": "Data analysis with Pandas" - }, - { - "Content URLs": "Speaker will focus on when and how to use design patterns, rather than what are the design patterns available. Github repository for the talk", - "Description": "Having less time to design software and solving the design problems correctly, to create robust , modular and highly maintainable code is current challenge.\nMight be, you are aware of some of the design patterns but it will never solve your problems until you have deep understanding on the problem and right place to use design pattern. If you think, you need to design a very unique architecture, then may be you are missing powerful available design pattern that can provide you generic solution template. Let's learn ( and become expert), to speed up development process; guessing issues that can come up later development stages and selecting the right design pattern in the right stage of the software development in Python", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Coders and programmers who want to learn about software design and architecture", - "Section": "Others", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/i-would-have-known-this-software-design-techniques-before~eXwgd/", - "title": "I would have known, this software design techniques before.." - }, - { - "Content URLs": "Will be updated soon", - "Description": "Talk Summary :- Recently, there is a boom in concept of face recognition system with the introduction of Face ID by Apple in their iPhone X mobile phones. This was also incorporated by OnePlus for their mobile phones too. The most notable use of this technology is at Baidu, an internet company, are using face recognition instead of ID cards to allow their employees to enter their offices. Another place where this technology is prominently seen is in auto photo and video tagging feature of Facebook. In this talk we will build a Facial Recognition program using python library \u201cface_recognition\u201d and then we will dive deep in the behind the scenes action of this library and will try to build a One Shot Learning face recognition model using PyTorch. We will be implementing a Siamese neural network on AT&T Laboratories Cambridge dataset. We will also cover the basics of this neural network, triple loss function and and will discuss the reason for choosing this architecture. I will explain how the network models a relation between two images and relates them. Outcome of this Talk :- Attendees will be able to possess the power to implement state of the art Facial Recognition program in a few minutes. They will also get to know how facial recognition works when we have very small dataset. They will be able to make a state of the art One Shot Learning face recognition based on Siamese Network (the working force of face_recognition and implementation of Google\u2019s FaceNet). Agenda :- Introduction to Face Recognition [2 mins] Introduction of python library \u201cface_recognition\u201d [1 min] Building a face recognition program using \u201cface_recognition\u201d library\n (possible live demo of the output) [6 min] How \u201cface_recognition\u201d encodes faces [2 min] Introduction of Triplet Loss and Siamese Network and reason to choose one shot learning (which is used to\n encode faces) [5 min] Implementation of Siamese Network using PyTorch on AT&T Laboratories\n Cambridge dataset and its results [10 min] Q&A Session [3 min]", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basic Knowledge of Machine Learning and Neural Networks Love for Pytho", - "Section": "Data science", - "Speaker Info": "Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", - "Speaker Links": "Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Saurabh Ghanekar (~saurabh29)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-state-of-the-art-facial-recognition~eVrXe/", - "title": "Understanding State of the Art Facial Recognition" - }, - { - "Content URLs": "Slides Celery Documentatio", - "Description": "Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. Although it is most popular in the web development ecosystem, it has a wide area of usage from system management to IoT devices. With Celery, transforming a function into a task is quite easy and can add great performance & usability to the applications that we build. This talk aims to give attendants a general overview of Celery and its uses. We will walk through the core Celery architecture by introducing key components with the help of various real-world examples. This will also lead to an understanding of the task queue systems in general. Attendants will also gain knowledge about Celerybeat; a tool that focuses on scheduling tasks", - "Last Updated": "21 Jun, 2018", - "Prerequisites": " Basic knowledge of Python. Ready to learn", - "Section": "Others", - "Speaker Info": "Software Engineer at Essentia SoftSer", - "Speaker Links": "Linkedin Githu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "abhyudaypratap@outlook.com", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-celery~eZy5d/", - "title": "Understanding Celery" - }, - { - "Description": "Data proliferation is putting pressures on business leaders to become data-driven. Although, leaders have to rely on data analysts to run those queries and get insights out from data warehouses. Its a common principle-agent problem wherein data analysts only ask questions from data which they are directed to ask, but its never a one-way street. One has to flirt with data for a long time to get to know it and leaders get stuck in the loop of data analyst direction as leaders are not equipped with or don't have time to write SQL queries. This calls for a natural language query wherein a business leader can ask a question in simple plain English and data is spitting out either in a table or graph. This session is guided towards how Innovaccer has solved this problem and provides an architecture, knowledge base building, and natural language processing guidance to build one on your own. The session will also emphasize on the fact that accuracy of such a software will be very poor if it is industry agnostic as SalesForce and ThoughtSpot have tried in the past. Thus, one has to tame it to their own business context or vertical", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics knowledge on natural language processing, not even how to code it, but what are its basic components. https://www.nltk.org", - "Section": "Data science", - "Speaker Info": "Kanav Hasija is Co-Founder and Chief Product Officer at Innovaccer. He has developed a healthcare data platform with his team which helps connect to various healthcare IT systems to get a longitudinal view of the patient record and turn it into analytical insights on risk, cost, and utilization behaviour of patient to act on them and treat them before they get sick to reduce the cost of healthcare. The platform today has more than 10 million lives on the platform and an estimated $1 Billion has been saved till date in US healthcare costs while keeping people healthy with a quality of care bump of 15%. He is a coder and mathematics enthusiast since the age of 10, completed his bachelor in engineering from IIT Kharagpur and pursued higher studies in Intellectual Property Law from UNH Law in the US. He is recipient of various awards like Samsung-Stanford Patent Prize, Honorable Mention for Excellence in Technology, Best Graduate Student Award, and is also an author in a few publications like IEEE. Harshil Rastogi is a software development engineer at Innovaccer. He has worked on various enterprise-grade software components in the fields of data management, data transformation, and natural language processing", - "Speaker Links": "https://www.linkedin.com/in/kanavhasija/ https://www.linkedin.com/in/harshil-rastogi-3a754b65", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kanav Hasija (~kanav)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bringing-analytics-in-hands-of-leaders-natural-language-query-in-python~bYx2a/", - "title": "Bringing analytics in hands of leaders: Natural Language Query in Python" - }, - { - "Content URLs": "Docker Docker Swarm https://docs.docker.com/engine/api/v1.37/ https://www.elastic.co/products/elasticsearch https://www.elastic.co/products/kibana https://www.elastic.co/products/beats https://jmeter.apache.org", - "Description": "Summary: Knowing how Enterprise Server perform under load (% CPU, % Memory, Network, % Disk time) is extremely valuable and critical. This may limit the server performance and lead to enhancements or fixing before you go for production. Now any Load testing tools available comes with below problems Preparing the environment / infrastructure (installing various software dependencies) on multiple host systems to perform load test at times very tedious task. It requires maintenance and manual interventions to scale up and scale down load test. You have to write your own test codes, need some development effort. Most of the stress tools comes with their own format of reporting, very difficult to customize if it\u2019s really needed. Also it\u2019s difficult to view, analyze and compare test results real time across systems. Here in today\u2019s talk we are going to demonstrate how JAAS (JMeter As A Service) can be a one stop solution for all these problems. And how python is playing a crucial role in Delivering JAAS Solution. Tech Stack: Tech Stack behind JAAS Python: Python is at the core of JAAS. It is responsible for communicating across all individual components using Rest API. Python is also responsible for slicing and dicing the data for processing. Docker: For auto deploying of JMeter Apps, we use Docker containers (pre-packaged with all dependencies). This reduces manual interventions for maintaining the Load test environment / infrastructure. ELKB Stack: ELKB is the backend for JAAS. We store all logs, beats, JMeter results in Elastic Search. Logstash for data processing pipeline and Kibana for visualization. JMeter : JMeter is the load test tool for generating load. It\u2019s an open source software, Ease of Use, Platform independent and Robust Reporting. JAAS comes with a single window User interface where user will provide the Load test details like: System details Load Generation type Number of concurrent users Number of threads Using RESTFul API implemented in Python this info (including dynamic Test plan .jmx file for JMeter) will be stored in ES Backend and a new Docker service will be created. We use Docker container (prepackaged with all dependencies as a single app) for generating load on System. Usually a Docker container ships JMeter software and Beats (Data shippers for Elasticsearch ). Every time for a new load test request, we deploy a new instance of our app on the Docker Swarm cluster (a new Docker container).We maintain Docker swarm cluster (group of machines that are running Docker) for scalability and load balancing while performing load test. Each of this machines in cluster (both manager and worker) will communicate with each other and execute Docker command using Python Rest call only. Swarm managers can use several strategies to run Docker containers, such as \u201cemptiest node\u201d -- which fills the least utilized machines with containers. Or \u201cglobal\u201d, which ensures that each machine gets exactly one instance of the specified container. Swarm managers authorize workers to execute\\run the Docker container. Each Docker service will have specific input from user (stored in ES backend) for generating particular type of load on specific host system. Similarly user can scale up or scale down the load (number of users or threads) using the same UI form on the fly. This is the biggest advantage of JAAS over any other Load test tool available. In normal scenario there is no option but stop and start the tool, if you want to scale up or down. \nEach Docker container with its JMeter instance will keep generating the Load on specific host system and Beats will be responsible for pushing back the data/results into Elasticsearch. This entire implementation of data reading and writing to Elasticsearch is happening through Python. Once the load test specific data pushed to Elasticsearch , kibana will prepare the Visualization for you. This is real time, aggregated (in case of concurrent users are generating the Load) and available in a single dashboard which makes it very easy to compare and analyze", - "Last Updated": "20 Jun, 2018", - "Prerequisites": "Familiarity to Python, Docker, JMeter and Elastic Stack.\nPython and Modules(XML, JSON and Request) experience", - "Section": "Developer tools and Automation", - "Speaker Info": "Vishnu Murty K A Senior Principal Engineer at DellEMC Infrastructure Solutions Group, is an MS (Software systems) with a total experience of 13 years in Leading Product Qualification and Automation Development efforts. The domains Vishnu has worked on include Storage and System Management Software. Responsible of Delivering Zeno - Continues Test Automation framework, JAAS, ICEMAN and Automation Tools. Presented automation papers in Pycon (Python developer forum)\u00a0and STeP-IN Forum. Dibyendu Dutta A professional with over 7 years of experience in Core Java, PHP, Node.js, Python.\nHe is currently working as a Senior Engineer in Dell R&D Bangalore. He has designed, developed web applications for various MNCs across multiple domains.\nHe loves to be keep updated with all latest tech trends , cutting edge technologies", - "Speaker Links": "Vishnu Murty K https://www.linkedin.com/in/vishnu-murty/ Dibyendu Dutta https://www.linkedin.com/in/dibyendu-dutta-3b65581b", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vishnu Murty (~vishnu79)", - "created_on": "20 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/distributed-load-testing-using-python-jmeter-and-docker~dRnEd/", - "title": "Distributed Load Testing using Python, Jmeter and Docker" - }, - { - "Content URLs": "https://github.com/someshchaturvedi/customizable-django-profiler Will be updating slides soon", - "Description": "Django, as we all know, is an excellent framework for building high stable, scalable, extensible web apps. Django framework operates around middlewares. Do we really understand how a middleware works? What happens when the request comes in and response goes out? Which middleware is used for what purposes? Why is the order of middleware stack important? How can we implement a custom middleware? Benefits and complications of implementing custom middlewares My talk will cover all the above questions along with a live demo of a profiling middleware ( customizable-django-profiler ) which is used to track down the function calls associated with an API call taking more time for execution. Contents of the talk: Introduction : Introduction to middleware. Middleware architecture : I will talk about the middleware architectural design. It\u2019s basics and various use cases Implementation of middleware in Django : Explain how the request-response cycle works along with targeting above mentioned questions on the go. Live demo : I will demo the development of a simple custom middleware which can be used for profiling requests. Conclusion : Possible use cases for Django middlewares. Q & A session : Questions and answers session. In the end, the audience will have an understanding of Django middleware stack, middleware architecture, request-response cycle in Django and will be able to develop their own middleware for Django from scratch", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics of Python and Djang", - "Section": "Web development", - "Speaker Info": "I am recently graduated from IIT Roorkee. I have been working on web applications (especially Django for more than 3 years now). Selected for Google Summer of Code this year and working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API . My areas of interest are Web Applications, Artificial Intelligence and Computational Biology", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-django-middleware-stack-with-a-live-demo~e1qme/", - "title": "Understanding Django middleware stack with a live demo" - }, - { - "Content URLs": "Git Hub Repository : click here Demo: click her", - "Description": "The workshop will be escalating from a very beginner level and so I only require you to know the basics of python and if possible a glance of the OpenCV library. The workshop will be proceeding accordingly : Basics of Image processing. Image classification using Deep Learning ( CNN ). Deploying your own Emotion recognizer. ", - "Last Updated": "21 Jun, 2018", - "Prerequisites": " Basics of Python Please download and install the following libraries in beforehand : Pytorch OpenCV Fastai numpy matplotlib dlib imutilis We will be using all of the mentioned libraries to make the goings of the workshop easy to understand and implement. Additional Files : Please download from her", - "Section": "Data science", - "Speaker Info": "I am shaaran and my main aim is to take technology to everyone and spread my knowledge as far as I can, in a journey to fulfill my dreams I have went to many institutions and have conducted workshops and talks in Robotics and AI, I am currently a second-year student at VIT University and also a part of many organizations like Google Developers Group, RoboVITics and more , I have interned at Toshiba recently and have made a new AHU control system using IOT and AI", - "Speaker Links": "Github: click here Linkedin: click her", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "shaaran Lakshminarayanan (~devshaaran)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-your-own-emotion-recognizer-from-scratch~b2rzb/", - "title": "Building your own Emotion recognizer from Scratch !" - }, - { - "Content URLs": "A similar version of this talk was recently delivered at Pycon APAC2018 (Singapore). Video An attendee's review", - "Description": "Offensive / abusive content is a major issue for social-media and digital interaction platforms. In some jurisdictions (Eg: Europe), platform providers are required by law to remove such content within 24 hours of posting or risk hefty fines (upto \u20ac50M in Germany). In order to meet the governance mandate, we need to have systems in place that can automatically detect abusive content at scale. This talk is based on my practical experience of building an automated solution to solve this problem. This talk begins with discussing some of the approaches currently being employed for offensive content detection at scale: word filtering, rule-based systems and actual human annotation. The former two are restricted by the following: Offensive content is context specific. A given word (f*ck) can be used in both positive (that\u2019s f*cking awesome) and negative (that\u2019s f*cking terrible) contexts. Robustness to spelling variations (The word \u2018shit\u2019 can be spelt as \u2018sh*t\u2019, \u2018sh!t\u2019, etc) Failure to detect content that is offensive in idea but uses non-offensive words. (Eg: your mom is a fat cow, X people are inferior, etc) Manual human annotation is notoriously hard and expensive to scale. The talk presents a Deep neural network based approach to overcome the previously mentioned limitations. It introduces and discusses the building blocks of model architecture (deep convolutional networks, word embeddings, etc). The second half of the talk focuses on implementing the model to solve the problem at scale as a RESTful micro-service using python, Django, Tensorflow and Docker. This architecture can also be used to implement other text classification systems (eg: sentiment detection, user intent detection systems, topic-of-discussion classifiers, etc.), making the talk relevant for a wider user base. Attendees will: Gain insights into building deep learning based text-classification systems that can scale Learn the nitty gritties of the offensive content detection and text classification Learn about the basic concepts of Deep Learning and NLP (convolutional neural nets, multi-layer perceptron, word embeddings, etc.) Understand the scientific and software challenges involved in text classification and learn to overcome them Be able to apply the learnings from here to other text classification problems as well", - "Last Updated": "22 Jun, 2018", - "Prerequisites": " Elementary knowledge of Python Basic understanding of machine learning (nice to have, not mandatory) An open mind ;)", - "Section": "Data science", - "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. He is currently employed as a Machine Learning Engineer. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", - "Speaker Links": "https://www.linkedin.com/in/alizishaan-khatri-32a2063", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Alizishaan Khatri (~alizishaan)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/detecting-offensive-messages-using-deep-learning-a-micro-service-based-approach~e30Ra/", - "title": "Detecting offensive messages using Deep Learning: A micro-service based approach" - }, - { - "Content URLs": "The code is in this repo :\nhttps://github.com/KaustabhGanguly/Smile-Detector :", - "Description": "In this era of deep learning and machine learning , the beginners may get lost sometimes , as there is a steep learning curve involved with the process .\nWhen I was starting out on machine learning , I always wanted to get my hands dirty in the advanced stuffs but It was hard for me and there was no guidance .\nSo , in this talk and coding session I will guide you through how you can build your own facial recognition system and implement a smile detection very quickly and easily with the power of openCV and python . It will take 10 mins and any beginner with basic knowledge of python can grasp the concepts easily .\nI will not use convNet or anything ,but a model called HaarCascades . It's an old mathematical model which was/is mainly used where deep learning is not an option . I will guide you through the basics and tell you some quick things and facts and we will enjoy a lot . See you on pyCon 2018 ! kindly upvote if you want some quality 10 mins learning something new ", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic Python knowledg", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India .\nI'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 .\nI'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github :\ngithub.com/kaustabhganguly\nConnect with me on linkedin :\nlinkedin.com/in/kaustab", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quick-and-easy-implementation-of-smile-detector-on-your-webcam-using-python-and-opencv-from-scratch-without-any-neural-network-and-for-beginners~e5E8e/", - "title": "Quick and easy implementation of Smile Detector on your Webcam using python and openCV from Scratch without any Neural Network and for beginners ." - }, - { - "Content URLs": "A sample code can be found here :\nhttps://github.com/KaustabhGanguly/Recurrent-Neural-Networks-to-predict-Google-Stock-Pric", - "Description": "I will show you how to predict google stock price with the help of Deep Learning and Data Science .\nThe predictions are not realistic as stock prices are very stochastic in nature and it's not possible till now to accurately predict it .\nAs I'll only have 30 mins to talk , I can't train the data and show you as it'll take several hours for the model to train on google collab . So , I will show you : Basics of Recurrent Neural Networks and LSTM Basics of pytorch Coding line by line with describing every words Then starting to train the model and prematurely closing it and move forward to show you the results that I'll bring with me after training .", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "You should have basic pyTorch understanding but I'll guide you anyways through the basics .\nBasic understanding of LSTM or RNN is preferred but not required ", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India . I'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 . I'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github : github.com/kaustabhganguly Connect with me on linkedin : linkedin.com/in/kaustab", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-stock-price-time-series-prediction-with-rnnlstm-using-pytorch-from-scratch~b67Rd/", - "title": "Google Stock Price Time Series Prediction with RNN(LSTM) using pytorch from Scratch" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Dash is a Python framework for building analytical web applications, built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs to your analytical Python code. The workshop will include building interactive dashboard with Dash framework. How to visualise the data purely in python will be the key take away", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Python 3 Pip3", - "Section": "Web development", - "Speaker Info": "I am software engineer working at Juxt Smartmandate, who believes in creating products using open source technology", - "Speaker Links": "https://github.com/kapoorabhish https://www.linkedin.com/in/abhishek-kapoor-4b7b9295", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "kapoorabhish", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-interactive-dashboard-using-plotly-dash~e771e/", - "title": "Building interactive dashboard using Plotly Dash." - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1d061xK27vMdJ8Xjta8K3kuvA4-dbX8MrywzXQmZ1Ln4/edit?usp=sharin", - "Description": "Have you ever been amazed how efficiently and effectively tech giants are processing their data ? Do you want to build an analytics system that is capable of processing billions of records in a day ? For those of you who are wondering how to build a scalable, low latency system for running arbitrary SQL queries in Python, this talk is for you! This system is distinguished by being schema-independent, and processing queries with minimal latency I will describe how to architect this system using the powerful Lambda Architecture (an often used design pattern in big data) and Apache Kafka, how to process and format the raw schema-independent data, and introduce different online analytical processing (OLAP) systems and their respective tradeoffs. The end product will be an analytics engine capable of running arbitrary queries on billions of records. Finally, I will also discuss some exciting extensions of this pipeline, including applying machine learning algorithms and adding a monitoring system. The talks ends with benchmarks of queries made on billions of records followed by a Q&A session. This talk is intended for folks belonging to any of these fields: Involved in the process of revamping their data warehousing systems\n for arbitrary queries with minimal latency Those who want to build their own analytics layer from scratch Analytics enthusiasts", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " General Python knowledge Basic SQL queries Great Enthusiasm Little Familiarity with Databases", - "Section": "Data science", - "Speaker Info": "Shaik Asifullah is currently working as Senior Data Engineer at MoEngage, open source developer who previously worked at WalmartLabs and graduated from BITS Pilani, Goa. He got interested in learning more about Big Data technologies after he learnt about Columnar databases. He was also associated with faculty of University of Zurich & ETH Zurich in building a Sentiment Analyser and worked on predicting results of US 2016 Presidential elections with the model. His recent open source contribution is regarding building a distributed Python environment for building, simulating, and analysing models of biochemical networks, including gene regulatory networks and metabolic networks. He is also a great admirer of Freud Psychoanalysis & Andre Breton Surrealism", - "Speaker Links": "https://www.linkedin.com/in/shaikasifullah https://github.com/ShaikAsifullah/distributed-telluriu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shaik Asifullah (~shaik2)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/processing-billions-of-records-per-day-with-python~e97Db/", - "title": "Processing Billions of Records Per day with Python" - }, - { - "Content URLs": " Apache Beam : https://beam.apache.org/ Apache Beam Python SDK : https://beam.apache.org/documentation/sdks/pydoc/2.4.0", - "Description": "Data together with 3Vs characteristic, volume, variety and velocity is labelled as Big Data. Big Data and parallel processing have been hot topics since Google\u2019s paper on MapReduce and till today the era of different runners like Apache Spark, Google Cloud Dataflow etc. Apache Beam is a unified big data processing paradigm which enables the user to run batch and streaming data processing jobs on multiple execution engines like Apache Spark, Apache Flink, Google Cloud Dataflow etc. *Objective of the talk* : Overview of Apache Beam Python SDK Core SDK constructs like Pipeline , PTransform , PCollection etc. Creating custom DoFns and composite Transforms Creating a Pipeline with customizable options Running a pipeline on different runners like DirectRunner , DataflowRunner etc Unit testing a Pipeline with asserts Demo: StreamingWordCount example using Google Cloud Dataflow Q&A", - "Last Updated": "22 Jun, 2018", - "Prerequisites": " A little knowledge about Python 2.7 Enthusiasm for Parallel Data Processing Motivation to play with lots of Data", - "Section": "Others", - "Speaker Info": "I am Mukul Arora, working as a Software Engineer in Schlumberger India Technology Centre. I graduated from Delhi Technology University in May 2017. I am a Data Science and Big Data practitioner and have been highly involved in solving Computer Vision and Medical Imaging problems using Deep Learning Techniques. Currently, I am exploring efficient ways to solve Big Data problems on Cloud.\nI am an avid cricket fan and love to write poems", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/mukularoradce/ Github : https://github.com/codemukul95 YourQuote : https://www.yourquote.in/mukul-arora-ffds/quotes", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "mukul arora (~mukul11)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unified-and-portable-parallel-data-processing-using-apache-beam~b4Dxb/", - "title": "Unified and Portable Parallel Data Processing using Apache Beam" - }, - { - "Description": "Automation is something we all desire, may it be the twitter feed of a celebrity, or perhaps the latest price of bitcoin. For students, it can range from tracking assignment deadlines or message updates. For developers, it can be the tracking of an important issue or auto merging of pull requests. For management, deadlines for a work assignment or a due presentation. With Python, everything listed above is possible. The talk will feature how to start automating the small things that can prove highly productive. We will use simple libraries first, and this will be followed by using fully headless browsers like selenium and understanding the concepts of web crawling. Integration of API services like Google Calendar and Google keep, to sync all the data collected will be demonstrated. Finally, we will deep dive into an interesting open-source project I made, and how I have automated most of my college work.\nA simple breakdown of the talk is described as follows. REST API Introduction ( Totally 3 minutes ) Libraries we will use ( Totally 6 minutes ) The Requests library The BeautifulSoup library Web Scraping example for IMDb ( Totally 4 minutes ) Code and Logic walkthrough Running Example Automation Example ( Totally 10 minutes ) What we will be doing The Code Google API linking Cron/Scheduling The base logic Running Example Selenium ( Totally 5 minutes ) Introduction Example Conclusion and My work ( Totally 2 minutes )", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic understanding of REST APIs and Frameworks, and Beginner-Intermediate Level of Python Programmin", - "Section": "Developer tools and Automation", - "Speaker Info": "CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms.\nTechnical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-your-life-with-python~b873a/", - "title": "Automating your life with Python" - }, - { - "Content URLs": "Will come soo", - "Description": "Blockchain Technology is the talk of the town. Almost all articles published have some relation to Blockchain concepts.\nWhile Public Networks usually pertain to Cryptocurrency, Private networks pertain to business-level implementations. In order to develop with this technology as our base, it is important to understand the key features, as well as make implementations using the existing skillset, which happens to be the Python Programming Language. The talk will feature Complete in-depth explanation of Blockchain technology, and the working of Bitcoin as an example. Developing your personal Cryptocurrency with Python Introduction to Hyperledger Sawtooth, and understanding how and why to use Python with it. Best practices to consider in mind while developing for a blockchain. By the end of the talk, you will be able to Explain the concepts of Cryptocurrency and Blockchain technically. Understand Python's role in one of the most popular frameworks created by Intel, and implement your own ideas with the same.", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "General Pytho", - "Section": "Others", - "Speaker Info": "Hi, I'm Priyansh! Here's a quick bio. CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms. Technical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-with-python~e0yLa/", - "title": "Blockchain with Python!" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Your machine learning models might be intelligent enough to make predictions but may lack the wisdom to prevent bias. They may be as vulnerable as a child getting influenced by inappropriate sources encouraging racism, sexism or any unintended prejudice. Models learn exactly what they are taught. The more biased your data is, the more biased is your model. For instance, a text model by Google says how \u201cEngineer is to a Man\u201d is the same as \u201cHousewife to a Woman\u201d. This shows how incidental data can lead to unintended bias. Machines are given the power to judge so there is a need for us to ensure we prevent biased/unfair judgments. In this talk, we are going to discuss how to arrive at \"Engineer is the same for both man and woman\" [debiasing gender] by following the steps below : Intro to Machine Learning bias and word vectors? [10 min] Analyse bias from word vectors and it's problems [10 min] Debiasing algorithm [10 - 15 min] Questions [5-10 min] One Famous example of bias:", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Knowledge of python Knowledge of building machine learning models / Interest in building on", - "Section": "Others", - "Speaker Info": "I am a software developer, speaker, opensource contributor and a wannabe developer evangelist. I love everything python and NLP(Natural Language Processing) research. I have been volunteering with various local startup and tech communities to promote entrepreneurship and technology. I work at mroads and help them develop better a.i", - "Speaker Links": "Links: Linkedin: https://www.linkedin.com/in/poornagurram/ Github: https://github.com/poornagurram StackOverflow: https://stackoverflow.com/users/5443381/poorna-prudhv", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "G POORNA PRUDHVI (~poornagurram)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-fair-machine-learning-systems~egVkd/", - "title": "Building fair machine learning systems" - }, - { - "Content URLs": "Errbot's Website: http://errbot.io Errbot's GitHub Repository: https://github.com/errbotio/errbot corobo's GitHub Repository: https://github.com/coala/corobo The slides will be shared to the audience as a GitHub repo after the talk", - "Description": "Abstract The aim of this talk is to introduce you to Errbot, which is a chatbot that can be used to automate software development and operation tasks to facilitate faster development of code. Errbot is a chat bot which connects to your favorite chat service(Gitter, Slack, Telegram, Zulip, IRC, etc) and brings your tools into the conversation. It provides you with a rich and user friendly API, through which you can write your own plugins so you can make it do whatever you want: retrieving some information online, trigger a tool via an API, troll a chat room member, etc. The talk will include: Introduction to DevOps and ChatOps What is Errbot Guide to setting up you own bot Writing your first plugin Fun with the bot Automating GitHub/GitLab tasks right from the chat room - Introduction to corobo", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " Basic knowledge of Python and APIs Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "Nitanshu Vashistha is a 3rd Year Engineering Undergraduate in India studying Information Technology. He started learning how to code in his first year of engineering but little did he know that he was just playing with the syntax, which he realized in his second year and his journey as a developer began. His first working application was in Python and that got him interested to develop more using Python. Nitanshu is a Python developer and an open source enthusiast . He has mentored Google Code-In 2017 and is currently a Google Summer of Code 2018 student working on a project based on Errbot for coala . He likes writing about himself as third-person :", - "Speaker Links": "GitHub: https://www.github.com/nvzard LinkedIn: https://www.linkedin.com/in/nitanshu Blog: https://medium.com/@nitanshu.vzar", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Nitanshu (~nvzard)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-automate-development-tasks-an-introduction-to-errbot~ejVve/", - "title": "How to automate development tasks? - An Introduction to Errbot" - }, - { - "Content URLs": "Content will be updated soon", - "Description": "You all would have often faced the issue of not being able to recognize handwriting, either it is a Doctor's prescription or sometimes, even your friend's assignment. This problem might have caused some harm, maybe due to the delay in submitting the assignment or seeking chemists' that can recognize that particular handwriting.\nTherefore, in this talk, we will be focusing on how Python and Data Science can be used to recognize handwritten digits and character which will ease out the pain of recognizing haphazard writings. Topics to be covered: What is Handwritten Digit and Character Recognition? Why we need it and uses of it? How Python can help in achieving this? How NLP and Neural networks can be used to increase accuracy? Future Scope", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " Basics of Python Basics of Data Science", - "Section": "Data science", - "Speaker Info": "I'm Prashant Pandey. I've deep interest in Data Science, especially in Python. I've been working in the domain of Data Science since one year now, and have completed several projects. Presently, I'm working on Handwritten Digit and Character Recognition", - "Speaker Links": "https://github.com/Prashantpandey2398", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Prashantpandey2398", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handwritten-digit-and-character-recognition-using-python~bkV6a/", - "title": "Handwritten Digit and Character Recognition using Python" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Get to know Flask and how to create beautiful REST APIs in no time. Fall in love with Flask and learn the best practices for building APis in a hurry. Flask is a lightweight micro-framework for Python. Its simplicity and elasticity make it the best choice for building APIs in no time. In my talk, I will cover the basics concepts of Flask and Requests. I will show the tools that can automate the most common tasks in API development and will share the design patterns to avoid common pitfalls. Some of the specific tools and topics that I'll cover: Flask-Restplus, SQLAlchemy, request lifecycles, REST + CRUD API patterns, Flask architecture", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "No previous experience in Flask is needed", - "Section": "Web development", - "Speaker Info": "Sara is a seasoned software engineer and the Co-Founder of Gradient.gt, a data science and machine learning consulting company based in Guatemala, where she works crafting web applications and solutions to companies in need. When she is not coding, she spends her free time baking sweet treats and watching Rick and Morty", - "Speaker Links": "www.sara-codes.com Linkedin.com/in/sarairisgarcia Gradient G", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "montjoile", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-apis-in-no-time-using-flask~bmVGd/", - "title": "Designing APIs in no time using Flask" - }, - { - "Content URLs": "https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology I will update slides and code soo", - "Description": "Central dogma of life or of molecular biology is the core molecular process which keeps us alive! It's the machinery which converts DNA to mRNA to protein to active protein which eventually gets distributed in the body. DNA -> mRNA -> Protein Through this talk, I'll give a live demonstration of the processes by which this mechanism takes place and unravel its mysteries using Python! I'll explain how python is helping us simulating biological processes in the most elegant manner. How is DNA transcripted to mRNA? How is mRNA translated to protein? These are some of the questions I\u2019ll answer by simulating the actual processes using Python. By solving small challenges involved with this mechanism, I\u2019ll tell the audience, why Python is the best computer language for a bioinformatician and how great python libraries can make the life even easier especially BioPython. The challenges I am talking about are real bioinformatics problem, although basic, including translation, transcription and reverse complement. In the end, I\u2019ll brief some huge accomplishments of bioinformatics and computational biology and how we can contribute to this sector which has a promising future as well. Contents of the talk: Introduction : Introduction to gene and how we (computer scientists)\n recognize a gene Central Dogma of Life : a Live action of how a gene\n is converted to RNA and then to protein using Python. Why Python is best for biology? : Bioinformatics can be best studied using Python Impact of this sector : Accomplishments of Computational Biology and\n bioinformatics Conclusion : Possible ways in which we can contribute. Q & A session : Questions and answers session. Outcome: After the talk, the audience will have an understanding of how we function at a cellular level, how proteins are formed in our body and how can we simulate other biological processes using Python and will recognize the power of Python which can be harnessed in biology as well as other sciences. They will also have a basic introduction of BioPython", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Curiosity to learn :", - "Section": "Others", - "Speaker Info": "I have completed my B.Tech in Biotechnology this year from IIT Roorkee. I have interests in Web applications, Artificial Intelligence and Computational Biology. I have worked a couple of years in Computational Biology and Translational Bioinformatics Lab at my Institute and currently a Google Summer of Code student working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API ", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/simulating-central-dogma-of-life-using-python~enV7e/", - "title": "Simulating central dogma of life using Python" - }, - { - "Description": "A framework which will give a drag and drop web development option using Django as the backend", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Python and basics of Djang", - "Section": "Web development", - "Speaker Info": "Sanket Sarkar [ Microsoft Technology Associate {Introduction to Python Programming}]\nA final Year Student of B.Tech", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Sanket Sarkar (~sanket78)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/drag-and-drop-framework-for-django~elVMb/", - "title": "Drag and Drop Framework for DJANGO" - }, - { - "Content URLs": "This talk will be based on my article on Towards Data Science The hands-on examples have also been open-sourced on GitHu", - "Description": "Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. We will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D) using a hands-on approach with Python and popular open-source visualization libraries like matplotlib and seaborn. The talk shall be structured as follows: Motivation for Effective Data Visualization A quick refresher on Data Visualization Brief introduction into python open-source frameworks for visualization pandas matplotlib seaborn bokeh Univariate analysis with hands-on examples Multivariate analysis with hands-on examples Visualizing data in 2, 3, 4, 5 and 6 dimensions Visualizing a combination of numeric and categorical data Strategies for effective data visualization Conclusion", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basics of Python, data terminology (rows, columns, feature, data points, data types) helps but we will be covering briefly during the session. Hence it's not essential", - "Section": "Data science", - "Speaker Info": "Dipanjan Sarkar is a Data Scientist at Intel, on a mission to make the world more connected and productive. He primarily works on data science, analytics, business intelligence, application development, and building large-scale intelligent systems. He holds a master of technology degree in Information Technology with specializations in Data Science and Software Engineering. He is also an avid supporter of self-learning. Dipanjan has been an analytics practitioner for several years now, specializing in machine learning, natural language processing, statistical methods and deep learning. Having a passion for data science and education, he is a Data Science Mentor at Springboard, helping people up-skill on areas like Data Science and Machine Learning. He also acts as a contributor and editor for Towards Data Science, a leading online journal focusing on Artificial Intelligence and Data Science. Dipanjan has also authored several books on R, Python, Machine Learning, Social Media Analytics, Natural Language Processing & Deep Learning. More about me: LinkedIn: https://www.linkedin.com/in/dipanzan/ GitHub: https://github.com/dipanjan", - "Speaker Links": "LinkedIn: https://www.linkedin.com/in/dipanzan/ Blog Posts: https://towardsdatascience.com/@dipanzan.sarkar GitHub: https://github.com/dipanjanS Featured stories on KDnuggets: https://www.kdnuggets.com/?s=dipanjan+sarkar Recent books:- https://www.springer.com/us/book/9781484223871 https://www.springer.com/us/book/9781484232064 https://www.packtpub.com/big-data-and-business-intelligence/hands-transfer-learning-pytho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Dipanjan Sarkar (~dipanjan)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-art-of-effective-visualization-of-multi-dimensional-data-a-hands-on-approach~ep6Vb/", - "title": "The art of effective visualization of multi-dimensional data - A hands-on approach" - }, - { - "Content URLs": "Content of my talk: Computer Vision with Pytho", - "Description": "We all(probably) love facial recognition feature isn't it?. We all edit our images before posting it to social media to give a flamboyant touch and its done in too simple steps. Open the editing software, select what you want to configure(filters, Sharpness, etc.) and you're done. Quite easy, right? But what if you know how the back-end of how these softwares run? what if you know the what kind of codes make your camera detect objects? Well with OpenCV and python its simpler than you can imagine! My talk will be about OpenCV with Python. OpenCV is an acronym for Open Source Computer Vision Library . Its a library used for image processing. The code can be written in C++, Java or Python but since we all love Python, we'll use that. We will be using ' cv2 ' library for all the image processing and detection. My talk will feature: How images are stored in computer and how each pixels store image. Different types of Colour Bands and the role of Colour Bands in forming an image. Editing images with cv2 library in python. Blurring, Sharpening, Greyscaling, and other uses of image kernels. Object and Face Detection and live object Tracking using python and OpenCV.", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basic knowledge of Python and basic mathematics(Class 10th)", - "Section": "Others", - "Speaker Info": "I am an undergraduate final year student, CSE branch from REVA University. I am a passionate programmer. I am an IEEE Volunteer. I was the Chair of IEEE Computer Society Chapter REVA University. Right now i am Student Branch Coordinator at IEEE Region 10(Asia/Pacific).\nCurrently I am interning at Valtech India as a Java Developer.\nI have taught python to more than 150 students in my college by taking sessions. I have taught OpenCV to more than 80 students.\nI started loving python since 2016 when I read the book 'learn python the hard way by Zed Shaw'. My almost all the undergraduate projects are based on python", - "Speaker Links": "Read my Blog! My Github Connect with me on LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rohan Vijay (~rohan96)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/computer-vision-with-python~bo9Xe/", - "title": "Computer Vision with Python." - }, - { - "Content URLs": "TB", - "Description": "The focus is more on teaching core concepts to programmers rather than using libraries. More than one neural network will be implemented. An Easy way to learn Machine Learning An interactive way to learn ML. With ML being a leading platform in the market, the workshop introduces to one of the most important fields of Machine Learning that is Deep Neural Networks. Only basic introduction to Mathematics required. Why Python? Python for Machine Learning Machine Learning What is Machine Learning? Why learn Machine Learning? Types of Machine Learning Regression and Classification Supervised and Unsupervised Neural Networks Deep Neural Networks Feed forward Neural Networks Convolutional Neural Networks CNN Recurrent Neural Networks Layers in Neural Networks Neuron Models Perceptron Sigmoid Neuron Binary Threshold Rectifier Stochastic Binary Cost Functions (A Loss or Objective function) Gradient Descent Gradient Boosting Backpropagation Stochastic Gradient Descent Implementing the classic MNIST dataset problem A Neural Network for handwritten digit recognition Classification using individual pixels Image Classification A simple implementation using deeper networks TensorFlow Expanding the Neural Network using Google's Library for Machine Learning Might change to Caffe - nVIDIA's library for Machine Learning Deep Learning A brief introduction to Deep Learning practices Auto Encoders Other areas of Deep Learning (A qualitative study) ", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "User Prerequisites Core Python - lists, dict, string including functions and classes NumPy, SciPy - not necessary but preferred Elementary Calculus - Differentiation and Integration (Understanding qualitatively is enough) Linear Algebra System Requirements 32/64-bit Windows/Linux architecture with at least 2GB RAM Python3 compiler with NumPy, SciPy and TensorFlow library PDF reader Other Requirements but not necessarily needed Anaconda3 (or support for ipynb files, Jupyter preferred) A graphic card", - "Section": "Core python and Standard library", - "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", - "Speaker Links": "GitHub Instagram Emai", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Aniket Chowdhury (~aniket43)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-advent-of-deep-neural-networks-neural-network-implementation-without-ml-libraries-and-extending-them-with-tensorflow~av75b/", - "title": "The Advent of Deep Neural Networks. Neural Network implementation without ML libraries and extending them with Tensorflow." - }, - { - "Content URLs": "Session Content: Introduction to main units of Deep learning Feature engineering techniques for audio data DeepSpeech Architecture Live demo of DeepSpeech Project Common Voice initiative (why and its need) Community Support details Applications of speech recognition Key Takeaways: Unravel the mystery behind the AI which powers speech recognition for services such as Siri, Google Assistance etc Learn about various by which one can contribute to Project DeepSpeech & Common voice project Get introduced to major units of deep learning and state of art DL architectures powering speech to text applications Tags: AI, speech recognition, speech to text, machine learning, Python, tensorflow, deep learning, Voice search Projects links: DeepSpeech : https://github.com/mozilla/DeepSpeech https://arxiv.org/abs/1412.5567 Common voice: https://voice.mozilla.org/ https://voice.mozilla.org/en/data", - "Description": "Pitch: Our voices are no longer a mystery to speech recognition (SR) software, the technology powering these services has amazed the humanity with its ability to understand us. This talk aims to cover the intrinsic details of advanced state of art SR algorithms with live demos of Project DeepSpeech. A research says that \"50% of all searches will be voice searches by 2020\". World\u2019s technology giants have placed big bets with their investments in services providing voice search, personal digital assistant, IoT devices etc. Solving the problem of speech recognition is a herculean task, given the complexity involved with data like the human voice. The talk will cover a brief history of speech recognition algorithms, the challenges associated with building these systems and then explain how one can build advanced speech recognition system using the power of deep learning and for illustration, we will deep dive into Project DeepSpeech. Project DeepSpeech is an open source Speech-To-Text engine developed by Mozilla Research based on Baidu's Deep Speech research paper and implemented using Google's TensorFlow library. Speech recognition is not all about the technology, there's a lot more concerns, challenges around how these AI models are being part of our day to day life , it's biases etc. The bigger question revolves around centralization of these AI services, projects like Common Voice addresses these problems by enabling all to be part of this revolution, a part of the talk will focus on how people need to approach these type of research keeping in mind the community and humanitarian benefits as first priority", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic Python Feel enthusiastic about ML & AI services Interest to learn about speech recognition systems", - "Section": "Data science", - "Speaker Info": "Vigneshwer is an innovative machine learning researcher with an artistic perception of technology and business, having several years of experience in developing robust machine learning solutions for video and text analytical problem statements and have played key roles in analyzing problems, creating hypothesis matrix and delivering novel algorithms and data-driven solutions for many fortune 500 companies. An open Source aficionado, Official Mozilla TechSpeaker and the author of Rust cookbook", - "Speaker Links": "Github | Website | Facebook | Twitter | LinkedIn | Talk", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vigneshwer Dhinakaran (~dvigneshwer)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-speech-recognition-with-project-deepspeech~erNpe/", - "title": "Demystifying speech recognition with Project DeepSpeech" - }, - { - "Content URLs": "will update soo", - "Description": "Get to Know Tkinter , pyqt5 and pyqtgraph and how to create a data visualization and control interface for your geeky arduino project in no time. Tkinter is a is the standard Python interface to the Tk GUI toolkit pyqt5 is Python bindings for the Qt cross platform UI and application toolkit pyqtgraph is Scientific Graphics and GUI Library for Python I will show you how to send the commands to Arduino using Python GUI and how parse and create a real-time graphs from Arduino dat", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "You should know how to write mighty Hello World program in Python and Arduin", - "Section": "Embedded python", - "Speaker Info": "I'm just a Tinkerer. Been playing with Python , Arduino and Raspberry Pi from few year", - "Speaker Links": "Blog - My Tinkering with Arduino GitHub linkden simple dem", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Kunchala Anil (~anilkunchalaece)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-python-gui-for-arduino-project~dw88e/", - "title": "Building Python GUI for Arduino Project" - }, - { - "Content URLs": "https://github.com/vibrantabhi19/PyConIndia2018 (A Github Link to the slides and the Jupyter Notebooks) https://docs.google.com/presentation/d/1UmT3PbazC6sO_owIeiLNj5G1EdTwrdpS84JWenO-3eE/edit?usp=sharing (Introduction Slide for CNN and PyTorch) Some more slides and notebooks as and when we come up with more ideas to make the workshop interacting and interesting", - "Description": "Just like in our everyday lives, AI and robotics are increasingly a part of our healthcare ecosystem. Currently healthcare is broken; there\u2019s shortage of doctors; poor quality of care. There is a dire need to provide assistance to the whole medical industry to improve healthcare. PyTorch, which is a very popular modular deep learning framework for fast, flexible experimentation is an invaluable resource for such problems. It supports seamless conversion of Numpy arrays into GPU tensors and vice versa. The dynamic computational graph allows to change the network behavior on the fly unlike static graphs and due to Its highly modular nature helps in fast debugging. Unlike other production grade tools, Pytorch helps with lots of Research and Experimentation with novel architectures and is very useful to test ideas a bit more quickly and prototyping. With Medical Imaging being the field most impacted by AI, our goal in this workshop is to give a good head start covering the heuristics of Medical Imaging, the concepts involved in it and how to code your way out. This workshop would be divided into two halfs. First Half: Pytorch Introduction\nDuration: 1 hour 20 minutes\nThe first half would be a gentle introduction to PyTorch framework. We will introduce the audience with the basics of PyTorch. This workshop will cover topics like: What is PyTorch? (Use cases and war stories) Tensor 101 Ndarray/Tensor library Numpy Bridge, Fast CPU to GPU conversion of tensors The automatic differentiation engine or autograd Difference between Static and Dynamic computational graphs Advantages of dynamic computational graph with examples The optimization package Scope of debugging Ecosystem Linear Code flow in Pytorch (One of the core philosophy of PyTorch) Saving and loading models* Deep Learning workflows* Tutorial on Transfer Learning.* Workflows which involve writing custom data-loaders will also be introduced in brief.* A 10 minute coffee/kit-kat break. :-) Second Half: Let\u2019s dive in. Duration: 1 hour 15 minutes. Introduction to Radiology: What is radiology? What do the images look like? How is AI used here? How will AI help improve radiology practice? Liver, Tumor and Vessel Segmentation - setting the context of why it is needed. Challenges faced in solving liver segmentation. How we solved the challenges - edge maps, data imbalance and overall architecture and data used. Hands on with live Liver Segmentation using PyTorch. Challenges faced in vessel segmentation and classification. How we solved the challenges - vesselness filters, overall architecture and data used. Hands on with live Vessel Segmentation using PyTorch. Putting it all together A 15 minutes Q & A session", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Zeal to learn new things would be enough but basic knowledge of Python would be good to go but the following are always encouraged: Basic Knowledge of algebra. Python Libraries such as Numpy. Basic knowledge of working with Neural Network (not a strict requirement as we will be covering most of it). We also encourage the participants to have a look into the following linked talks/videos/literature to get a head start into the topic. The related materials from web for ideas: https://github.com/soumith/talks/blob/master/2017-NIPS/Coding-papers-in-pytorch.pdf https://github.com/soumith/talks/blob/master/2017-GATech-Atlanta/PyTorch-frameworks_overview_deepdive.pdf https://www.youtube.com/watch?v=LEkyvEZoDZg https://www.youtube.com/watch?v=VMcRWYEKmhw https://www.youtube.com/watch?v=Rv9naeLXolY&index=3&list=PLrzfRWNHZPa0gKBEXTJ0gbDu8NsR07KEH https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/01-basics/pytorch_basics/main.p", - "Section": "Data science", - "Speaker Info": "Abhishek Kumar: Deep Learning Engineer, Predible Health, Bangalore. I am presently working as Deep Learning Scientist at Predible Health, here,I work on the the research and development of Predible's core Imaging platform wherein we have build state of the art segmentation algorithms/models in Computer Vision. I have previously taken workshop at IIT-Bombay Techfest, I have spoken at Shri Mata Vaishno Devi University at their SFD celebrations and at MuPy (Manipal Institute of Technology's annual Python Conference), Kongu University and a few other colleges/Universities. I have been a constant contributor in the open source world and have been attending PyCon and other conferences every year. An athlete, a Real Madrid F.C follower and a part time stand-up comedian (good enough to make you laugh). Aditya Bagari: Final year Undergrad, Indian Institute of Technology, Madras I am a final year Undergraduate student at IIT-Madras doing my Dual-Degree in Engineering Design with specialisation in Bio Medical Sciences. I have been working on Medical Imaging and PyTorch for almost a year and I have been a constant admirer of Open Source Technologies and frameworks. Feel free to drop any suggestions or modifications that you want in this workshop. See you at PyCon", - "Speaker Links": "Abhishek Kumar: Website (A very outdated one), LinkedIn , Medium , Github . Aditya Bagari: LinkedI", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Abhishek Kumar (~vibrantabhi19)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploring-pytorch-for-ai-assistance-in-medical-imaging~bqXpa/", - "title": "Exploring PyTorch for AI assistance in Medical Imaging" - }, - { - "Content URLs": "Will be updated soo", - "Description": "Ever thought of Building a brilliant website but don't want to waste time in setting up or do the boring server setup for it or it's too hard for you to make your website secure from attackers. Well, Django is here to solve these problems for you. Django is a rich MVC-MVT Python web Framework for the website which will do all these tasks for you. After this workshop, you will be able to create dynamic high-security web applications and perform CRUD operations by interacting with the database of your choice. We will be creating a blog website where users can log in, create blogs, rate them, etc", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Laptop with Python3 installed and Pycharm (or any of your favourite IDE)", - "Section": "Web development", - "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International Universi", - "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Chhavnish Mittal (~chhavnish)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/first-steps-into-web-development-using-django-framework~dyOna/", - "title": "First Steps into Web Development using Django Framework" - }, - { - "Content URLs": "Will be updated soo", - "Description": "The ELK stack consists of Elasticsearch, Logstash, and Kibana. Although they've all been built to work exceptionally well together, each one is a separate project that is driven by the open-source vendor Elastic\u2014which itself began as an enterprise search platform vendor. It has now become a full-service analytics software company, mainly because of the success of the ELK stack. The session will cover basics of ELK stack for a kickstart", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Passion to Lear", - "Section": "Others", - "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International University", - "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chhavnish Mittal (~chhavnish)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-wih-elk-stack~axNBd/", - "title": "Getting Started wih ELK Stack" - }, - { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research\nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "The Python ecosystem is growing and may become the dominant platform for machine learning. The primary rationale for adopting Python for machine learning is because it is a general purpose programming language that we can use both for R&D and in production. In this talk I will discuss 1. Python and its rising use for machine learning, 2. SciPy and the functionality it provides with NumPy, Matplotlib and Pandas.\n3. scikit-learn for machine learning algorithms, TensorFlow and Keras for Deep learning and PyTorch for Natural Language Processing, 4. How to setup your Python ecosystem for machine learning and what versions to use. At the end I will also give case studies on using this Python ecosystem for biomedical applications", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", - "Section": "Data science", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban\nhttp://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban\nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Parthi", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mastering-machine-learning-with-python~azNya/", - "title": "Mastering Machine Learning with Python" - }, - { - "Content URLs": " Open Library Website Open Library Github Repository Open Library Client Github Repository Open Library Bots Github Repository", - "Description": "This Workshop is designed to guide developers who are interested in learning more about the basics of open source software and contributing to their first open source project. We'll look at Open Library, a mature open source project, and see how 20 open source contributors are able to make contributions which impact over a million international users. You\u2019ll learn what tools, best practices, and processes help make an open source project successful and what beginning steps you can take to enter the open source world. What is Open Library? Open Library is a non-profit online library created by Aaron Swartz and Brewster Kahle in 2006 with the mission of \u201cOne Web Page for every book ever published\u201d. Open Library is written in Python using the web.py micro-framework, and is open source on Github. Open Library uses Infobase, its own database framework based on PostgreSQL and Infogami which is its own Wiki Engine using Python. Why Open Library? Open Library has an active, supportive community, newcomer-friendly issues, and mature documentation , which makes it a good candidate for engineers who are looking to contribute to their first open source project . Some of the advantages of having Open Library as your entry to the world of Open Source Software are as follows: Open Library is very easy to install and has simple and straight-forward instructions. Issues for Beginners are labelled as first-timer-issues on the repository to help beginners get over their fear of contributing to Open Source and making it a simple process for them. Open Library has a community call every week in order to catch up the progress that each contributor is making. There is a Slack channel where anyone can be invited to and GitHub issues for communication. There is an updated Wiki which keeps getting updated as contributors contribute to the project. All coding procedures followed by Open Library are documented in a CONTRIBUTING / Getting Started guide. Some of the opportunities for new developers looking to get started to contributing to Open Library are as follows: Open Library does poorly as compared to global standards (like a modern js build system) and this is a huge opportunity for people who want to contribute to Open Library. it relies on a lot of custom code like Infogami and Infobase which are not well maintained anymore and are mostly in Python 2. So there is huge opportunity here in building a complete system while migrating to Python 3 while making sure you do retain the ease of the old code. Session Plan Creating a Github account and finding us on Github. Comment on the Slack Invite Issue to be added to the Open Library Slack Org. Understand how communication works on Open Library and getting familiar with using Github Issues and Slack for communication. Introducing yourself to the Open Library Community on Slack and initiating to become an 'Open Library Librarian'. This stage also involves talking with the Open Library community and finding Issues that match your interest. A simple and brief introduction to Git(clone, add, commit, push, pull) and Github (Fork, PRs, Issues). Setting up the project on your local dev environment. Reading Documentation as this is an important part of learning to contribute to Open Source Software. Using the Github Bug Tracker to find First Timer Issues to resolve and work on them. Making your first commit as a Open Library Librarian and submitting a Pull Request. Getting your Pull Request Merged after following community guidelines. Understanding the review process followed at Open Library and making sure to use that effectively to contribute to further Issues!", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic understanding of Python Ability to read documentation to understand the codebase Basic understanding of git and scm", - "Section": "Web development", - "Speaker Info": "Salman Shah is a Final Year Undergraduate Student at NITK Surathkal and a GSoC Student at Open Library, Internet Archive. Salman is a night owl whose primary interests include reading novels, participating in Hackathons and discussing technology. His language of choice is Python which he\u2019s used to add thousands of books to openlibrary", - "Speaker Links": " Personal Website Github Profile LinkedIn Profile", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Salman Shah (~salman96)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/open-library-one-web-page-for-every-book-ever-published~aA7ld/", - "title": "Open Library - One Web Page for every book ever Published" - }, - { - "Content URLs": "TB", - "Description": "This tutorial is meant to familiarize participants with Tensorflow, generally as a tensor library and particularly as a tool for doing day-to-day machine learning tasks. The ultimate goal of the tutorial is to be able to make participants comfortable enough with it so that they can use tensorflow as a scalable substitute for other ML libraries like sklearn. Why Learn Tensorflow? For the same reason that you should learn NumPy. Tensorflow is to Keras (and many other deep learning libraries) what NumPy is to sklearn (and many other machine learning libraries). It is the underlying data model of many deep learning applications. There are always nooks and crannies in any deep learning application that high level wrapper libraries cannot reach. The tutorial is aimed at making these accessible and debuggable with tensorflow. What will I learn? The focus of the tutorial would be on loss functions - ensuring their fundamental correctness with respect to the machine learning problem at hand, ensuring their differentiability and convergence are critical to solving a deep learning problem. There are many ready-made loss functions in tensorflow, and using these as building blocks, we will see how to make arbitrarily complex loss functions. FAQs: Q. Will I need a GPU? A. No. The beauty of tensorflow is that it can seamlessly deploy code to GPUs, without you needing a GPU to develop that code. Q. What is the format of the tutorial? A. Being a tutorial, this session is meant to be highly interactive in nature. It will be a sequence of units where concepts are first explained and then the audience will have to solve exercises in a Jupyter notebook. Q. I don't know anything about neural networks or deep learning. Should I attend this tutorial? A. Absolutely. The focus is on tensors, which are the domain of tensorflow, and not on network layers, which are domain of keras", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic knowledge of Python data structures and NumPy arrays Basic knowledge of linear algebra Elementary vector calculus", - "Section": "Data science", - "Speaker Info": "Jaidev is a data scientist based in New Delhi, India. He specializes in building data-driven products and the tooling around them for a living. His research interests are in signal processing and computational harmonic analysis. He is obsessed with applications of machine learning in personal productivity and recommendation systems. He blogs about these here ", - "Speaker Links": "Twitter GitHub Blo", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Jaidev Deshpande (~jaidev)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tensorflow-101~dB7Ye/", - "title": "Tensorflow 101" - }, - { - "Content URLs": "Weather API: Open Weather Map (OWM) Public Posts: Twitter API", - "Description": "This talk focuses on demonstrating the power of Python's Statistical and Data Science Libraries. I have been working on a project to classify average human sentiments as positive or negative. Classification is completely based on the prediction made by the ML models, which incorporates the weather of the location. I will try to prove that weather is \"one of the factor\" contributing to the moods/emotions of humans and ultimately affects the decision making ability. I have achieved the accuracy of 60%, which is good enough, with the existing and publically available data. The accuracy will certainly grow along with the data", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basic knowledge of Python Basic understanding of Statistics Pinch of common sense", - "Section": "Data science", - "Speaker Info": "I am a Python enthusiast, always a keen explorer of the power of python. I have been passionate about Python since my early college days, and then I went on developing many Web Apps, APIs based on Django and Flask, later on, my journey with Python turned towards exploring the magic of Data Science. It has been quite an interesting time spent exploring this field, and I must say that the depth cannot be determined. The more you experience, the more moments of awe occur", - "Speaker Links": " https://omkar-dsd.github.io/ https://towardsdatascience.com/a-simple-word-sense-disambiguation-application-3ca645c56357 https://medium.com/@omkar_dsd/when-killing-humans-becomes-the-right-choice-e3964419e78c https://stackoverflow.com/users/5130528/omkar-deshpande https://www.github.com/omkar-dsd", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Omkar Deshpande (~omkar08)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/analyzing-the-impact-of-weather-on-human-sentiments~bD7Ka/", - "title": "Analyzing the impact of weather on human sentiments" - }, - { - "Content URLs": "TB", - "Description": "\"Data is the new Oil!\" But, what is the benefit of this oil if you cannot refine (analyse) and sell/use (derive value) it. Big Data has pushed the frontier of analytical processing to gather more actionable insights in the past decade from having separate analytical servers to performing analytics close to the Data Lake/Cloud. A new paradigm of FOG computing has recently emerged which enables analyzing data at the Edge (close to the data capture device). This talk will focus on Edge Analytics enabled by Python & Raspberry Pi. Why attend this session? This session will provide a first hand look into the paradigm of FOG computing and Edge analytics. Model deployment is a critical part of the analytics life-cycle and this talk will provide insights and best practices to ensure seamless and robust model deployment. Also, the audience will get a flavor of python in embedded devices through the live and interactive demonstration using Raspberry Pi. Content The talk will cover the following sections: Evolution of analytics (Dedicated Machines -> Cloud -> Edge) The need of Edge analytics Analytics Life-cycle (ALC): Introduction, Importance of Model Deployment, Adapting ALC for Edge Analytics Model Exchange Formats (PFA, ONNX) for Deployment: Introduction & Need for Democratizing model development process Edge Device Introduction - Raspberry Pi Introduction to Portable Format for Analytics (PFA) Model Deployment on Edge Device (Raspberry Pi) using open source PFA engine implemented in Python Hands-on Application Use Cases - Deployment of Clustering, Regression, Decision Tree, Neural Network/ Deep Learning Models", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Python 2.7.x titus python package (pip install titus)", - "Section": "Embedded python", - "Speaker Info": "A die hard Pythonista, Ankit is a full time open source contributor and a former Google Summer of Code 2013 scholar under Python Software Foundation. Currently, he is developing the open source Portable Format for Analytics (PFA) implementation - Titus on Python 3. Ankit has 4 years of industrial experience in machine learning, quantitative modelling, data analytics and visualization. Over the years, he has developed an expertise in handling the entire data analytics pipeline comprising \u2013 ingestion, exploration, transformation, modeling and deployment. He is a polyglot programmer with an extensive knowledge of algorithms, statistics and parallel programming. He has shipped multiple releases of DB Lytix, a comprehensive library of over 800 mathematical and statistical functions used widely in data mining, machine learning and analytics applications, including \u201cbig data analytics\u201d. An IIT Kanpur alumnus, Ankit is also an active researcher with publications in international journal and conferences. He is actively working in the domain of IoT Analytics and has recently presented his work: \"Discovering Knowledge from Smart Meter Data using Competitive Learning Methods\" in the Data Science Congress 2018. \u201cIn-database Analytics in the Age of Smart Meters\u201d in the 5th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, 2017. \u201cSmart Meter Data Analytics using Orange\u201d in Scipy India 2017, Mumbai. Ankit is an active contributor to the Indian Python Community and has conducted the following workshops in PyCon India and Scipy India: Scientific Computing using Orange in SciPy India 2017, Mumbai. Making Machine Learning Fruitful and Fun using Orange in PyCon India 2017, New Delhi.", - "Speaker Links": "LinkedIn Youtube channel Githu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ankit Mahato (~ankit60)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fog-analytics-using-raspberry-pi-and-python~eE7gb/", - "title": "Fog Analytics using Raspberry Pi and Python" - }, - { - "Content URLs": "http://www.calmdownkarm.com/2018/clustering (Blog Post)\nhttps://github.com/CalmDownKarm/360classificatio", - "Description": "Quick walkthrough of how word2vec combined with more traditional clustering mechanisms can be used for topic modelling and document classificatio", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Some familiarity with clustering (Kmeans) is helpful, but not required", - "Section": "Data science", - "Speaker Info": "Recently graduated from BML Munjal University, Developer at Gramener", - "Speaker Links": "calmdownkarm.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Karmanya Aggarwal (~CalmDownKarm)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/document-clustering-with-word2vec-and-hierarchial-clusters~dG7Jd/", - "title": "Document Clustering with Word2vec and Hierarchial Clusters" - }, - { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research \nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "We survey progress in recent years toward developing a theory of deep learning. Works have started addressing issues such as: (a) the effect of architecture choices on the optimization landscape, training speed, and expressiveness (b) quantifying the true \"capacity\" of the net, as a step towards understanding why nets with hugely more parameters than training examples nevertheless do not overfit (c) understanding inherent power and limitations of deep generative models, especially (various flavors of) generative adversarial nets (GANs) (d) understanding properties of simple RNN-style language models and some of their solutions (word embeddings and sentence embeddings", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", - "Section": "Others", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban http://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban \nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Parthi", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/toward-theoretical-understanding-of-deep-learning~dJjgd/", - "title": "Toward Theoretical Understanding of Deep Learning" - }, - { - "Content URLs": "Slides will be uploaded soon", - "Description": "Python - Turing Complete and easy at the same time. Given its simplicity, one may be tempted to use it to solve a problem of any magnitude. But as the codebase scales, so does the difficulty in managing it. And as the applicability scales up, so does the difficulty in maintaining performance. In this workshop, we will walk through how these problems crop up in the first place, and how to tackle them. This workshop will NOT cover scalability from the perspective of distributing data loading and computation across multiple compute units (horizontal scalability). We will focus more on how to write code from the very start that is both efficient in performance and makes a larger codebase manageable. The topics we will go through are: 1.Performance - How should one write \"fast\" code Finding the bottleneck - Profiling Compiling Python to C - JIT vs AOT / Cython vs Numba vs Pythran vs PyPy - How they differ and choosing which one is for you Concurrency - To parallelize or not to parallelize, to sync or not to sync Choosing the right data structures Hacks and bits that can get us the extra performance 2.Design Principles - How should one write \"good\" code, because we have all written code that we have difficulty in understanding ourselves in no time Logging - Keeping track of what happened when and where Type Checking - The why and the how Unit Tests and beyond", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Cython, numba, and pythran installed. All of them are available on pip/conda Working knowledge of Python", - "Section": "Others", - "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", - "Speaker Links": "R S Nikhil Krishna Personal Website Github Linkedin StackOverflow Lokesh Kumar T Github Linkedin StackOverflow", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-code-that-you-need-not-look-back-at-fast-and-good-python-at-scale~dLlrd/", - "title": "Writing code that you need not look back at - Fast and \"good\" python at scale" - }, - { - "Content URLs": "https://gautam-ankit.github.io/HomeAR", - "Description": "In this project, we are going to create a home finder in which we are going to give an individual marker/bar code to each and every home and going to create a web-app which will tell about the home on starring the camera on the marker/bar code. This idea will help out to find some place way better than the Google maps because one can generate its own marker for his/her home and can edit the details of there home, through which one can recognize the home. For management of this data we are going to use several concept of Big data also. But this is the best way possible to implement and link augmented reality with python", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "HTML and CSS and basic Javascript,\nbasic python ,\nsome programming concepts", - "Section": "Core python and Standard library", - "Speaker Info": "As a Microsoft student partner, I gave several presentations for Hour of code. And as a Mozilla campus club caption, I gave several presentations for Virtual reality and Augmented reality using Aframe web framework", - "Speaker Links": "https://www.linkedin.com/in/ankit-gautam-9b0524108", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Ankit Gautam (~Gautam-ankit)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/home-finder-using-python-and-augmented-reality~dNnvd/", - "title": "Home finder using Python and Augmented Reality" - }, - { - "Content URLs": "https://en.wikipedia.org/wiki/Decentralized_autonomous_organization\nhttps://blockchaindevs.github.io/MeetupDA", - "Description": "Open Source Communities and their management. How things work currently A case study of different open source organizations: Advantages and disadvantages of current systems. The issues with Open Source organizations are nothing new, what are the possible solutions available? DAO and automation of majority of the tasks of a \"Open by default organizations\" What part of the organization can be automated, what can't. Important Aspects that usually breed trust among members::\n - Transparency\n - Consistency & Automation\n - Inclusion & support Our Proposal We will be posting codebase and complete websites and mobile apps that offer these solutions: Automated and transparent membership procedure. Transparent Public Elections on Blockchain for a board with automated publication of votes and results. Automate votes based on proposals Automated Procedure to apply for grants: with voting members and results being put up on Blockchain Automated meetings with MOM being recorded and put up on blockchain. Testing Proposal from the ground up: Start Small and test if these methods work locally in meetup groups \n- Automation of Tasks around meetups:\n...\nWe will keep updating here as and when we have deployed solutions on blockchain Tools used for these automation: Blockchain Dapps using : Solidity & Vyper\nPython: Kivy Framework for mobile apps and Web3.js & other such frameworks. Repos:\n They will be made online shortly, currently the experimentation is going on the following repos: https://blockchaindevs.github.io/MeetupDAO please excuse for the alpha quality of the software as they are just experiments as of now. This is a open source initiative based on the needs we feel we have seen arise in open source communities around us. Ultimate Goal Use this proposal as a catalyst and create small Organizations in local communities testing this theory. If things work in local communities, create a National Level Organization for managing the tasks around PyCon India This is just one of the hopefully multiple proposed solutions for moving on post PSSI", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "A willing ness to contribute, ability to learn. \nOpen Mind to experiment even if it leads to failure", - "Section": "Developer tools and Automation", - "Speaker Info": "http://github.com/akshayaurora Akkshay is huge open source enthusiast, he has helped bootstrap different communities around Kivy, PyDelhi, ILUGD, BlockchainDevs , HyperLedger Delhi/NCR & chaired conferences like PyDelhiConf, Pycon-India, Global Blockchain Conference. He has been involved and working on blockchain based projects from 2011 onwards, he is one of the core developers of Kivy python framework & Electrum bitcoin wallet that has been built on top of it", - "Speaker Links": "http://github.com/akshayauror", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Akshay Arora (~akshayaurora)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-open-source-communities-on-blockchain-a-transparent-way-to-manage-organizations~aKkxa/", - "title": "Automating Open Source communities on Blockchain: A transparent way to manage Organizations" - }, - { - "Content URLs": "Will be updated soon", - "Description": "In this talk, I will provide a concise understanding of Threading and Global Interpreter Lock(GIL) in Python. In the modern era of hybrid cores and processors, there is an in demand need for concurrent and parallel programming paradigms. Python, since its inception has amazing support for single threaded applications. The extensive use of Python in booming fields like Machine Learning has paved the way to constantly improve multi-threaded applications in Python. I will speak from ground level covering very crucial aspects of Threading and Locks which will provide a better roadmap for community to develop better Python applications. Program outcomes: How threading can improve performance, its pros and cons. What works best in which environment between threads and processes. Why GIL matters the most in Python How to leverage the power of open source source code to understand the crux of language. Contents to be covered: 1. Threading for noobs: Terminologies: Process, threads, multithreading, multiprocessing, types of threads, locks, mutex, CPU and I/O bound processes. Multithreading in Python: Threading module (with example) Comparative analysis of Sequential vs Multithreaded execution in Python (with example) 2. Understanding the global interpreter lock (GIL): What and why of GIL Impact of GIL on CPU and I/O Bound Processes In-depth understanding of GIL using cpython interpreter source code Reference counting Ticks via context switching 3. Infamous concepts: Cooperative vs Preemptive multitasking Parallelism vs Concurrency Thread Safety in Python 4. Removing the GIL: Famous GIL removal patch Guido on GIL, Larry Hastings Gilectomy 5. Questions Agenda: 0 - 6 minutes : section 1, Threading for noobs 6 - 15 minutes : section 2, Understanding GIL 15 - 25 minutes : section 3, Infamous concepts 25 - 28 minutes : section 4, Removing the GIL 28 - 30 minutes : section 5, Questions ", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basics of Python: Class, objects, list, libraries", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself from scratch. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-multithreading-by-deciphering-the-cpython-interpreter-source-code~aOora/", - "title": "Understanding multithreading by deciphering the cpython interpreter source code" - }, - { - "Content URLs": "So, Slides can be seen here: https://slides.com/tanayagrawal/efficient-hyperparameter-optimization#/ Full content is available here: https://github.com/tanayag/pycon_18_hyperopt You can also have a look at my article: https://blog.goodaudience.com/on-using-hyperopt-advanced-machine-learning-a2dde2ccece7 In the Repo iris.csv is the dataset that we'll work on. docker folder contains the scripts to setup Environment \"Introduction to Hyperopt.ipynb\" is iPython Notebook which contains the implementation which we'll work on during workshop and understand the concept \"link_to_slides.txt\" contains the link to our presentation", - "Description": "Hands on Experience with Advanced Hyper-parameter Optimization Techniques, using Hyperopt We'll go step by step, starting with the Hyper-parameter optimization with SkLearn's Grid Search, we'll compare it with the more effective Hyper-Parameter Optimization TPE Algorithm implemented in Hyperopt.\nWe'll also go through on how to parallelize the evaluations using MongoDB making the optimization even more effective. A Docker Image will be provided, so that participants won't have to waste time in setting up the environment. The Workflow of the Workshop would be: We will start with a slide presentation so that participants get some insight on what they are going to do. After that we'll shift on to a Juypter Notebook(pre-installed in the docker environment, so you can just focus on the implementation part), here they will implement the code, and see the best algorithms of hyperparameter optimization working. After that we'll show a working demo of a problem that we were working on and solved using Hyperopt during our Summer Intern at MateLabs. After attending this workshop you will be able to apply Hyper-parameter optimization using better algorithms which decides the hyper-parameters based on information. In short much much efficient model training", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic Python Coding and a little familiarity with Machine Learning/Data Science", - "Section": "Data science", - "Speaker Info": "Tanay Agrawal Working on Machine Learning/Deep Learning and also an Open Source Enthusiast. Currently in Final Year of his Engineering. He is working as Deep Learning Intern at Matelabs. He along with team at MateLabs is creating Meta Algorithms, so that user even with minimum or no knowledge of Machine Learning would be able to use it. Also he is a contributor at SymPy. He has previously worked on state of the art Classification and Object detection Models as well. He has previously conducted Python workshop at SFD-SMVDU and also he conduct the session of AI Circle at his College regularly. Anubhav Kesari Currently at fInal year of engineering from IIIT Guwahati. Two worked on the same problem and solved it using Hyperopt. Anubhav is the summer intern at MateLabs as well. He has worked at Cadence Design Systems in summer of 2017 as Software Development Intern. He has also been working on development of blockchain based distributed neural networks at MateLab", - "Speaker Links": "Tanay Agrawal https://github.com/tanayag https://angel.co/tanay_agrawal Anubhav Kesari https://github.com/kesarianubhav https://www.linkedin.com/in/anubhav-kesari-588a03131", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "tanay_agrawal", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-ml-learn-how-to-improve-accuracy-by-optimizing-hyper-parameters-using-hyperopt~aMmGa/", - "title": "Advanced ML: Learn how to Improve Accuracy by optimizing Hyper-Parameters using Hyperopt" - }, - { - "Content URLs": "Slides will be uploaded soon. Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv", - "Description": "There lies a huge gap between a website made as a hobby/college project and that made for professional purposes. The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! Before delving into the open source world, my code screamed that it's owned by a college kid. But things changed once I interned with Wikimedia (under the Outreachy program). I want to share this very experience with my audience that how some gotchas and design decisions can bring about this transition. In this talk, I'll touch upon some of these areas that mainly deal with backend and database. My talk will summarize my learning from using Django in an application built for Wikipedia and is capable of handling huge amount of Wikipedia's data. To give a bit of background - I built this application for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/). The app summarizes the contributions of the Wikipedia editors and presents it in a CV-like format. The biggest development challenge was dealing with millions of edits and doing all the related computations within seconds. Without any kind of optimizations, the webpage took 3 hours to load. Through my talk, I want to bring out the journey from 3 hours to 3 seconds on the table! Broad outline of my talk is as follows: Why Django : It's very important to understand why and when to use Django. Majorly I'll be touching upon the scalability aspect and how it's a full package when it comes to web development. Reducing the response time : When one is dealing with a database as huge as that of Wikipedia's, response time becomes of paramount importance. Optimizations like implementing a cache layer , using cron jobs , sessions etc will be discussed. Also, design choices will be compared - like cache layer using database vs sessions in python. Database Optimizations : In this I'll be covering how database choice and query optimizations can affect the performance when dealing with large datasets. Hope you will find this talk interesting. :)", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic knowledge of Python, Django and querying RDBMS is required", - "Section": "Web development", - "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia.\nOther than coding, I love reading, writing and trying out new things", - "Speaker Links": " Blog: https://medium.com/@meghasharma4910 Github: https://github.com/MeghaSharma21 Outreachy project: https://github.com/MeghaSharma21/WikiCV Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Megha Sharma (~megha480)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/optimizations-in-web-development-journey-from-a-college-project-to-a-professional-product~dPp4d/", - "title": "Optimizations in Web Development: Journey from a college project to a professional product" - }, - { - "Content URLs": "Tutorial Series https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-2 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-3 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-4 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-5 Github Repo (Most starred repo for a Python implementation of YOLO v3, at 589 stars at the time of speaking) https://github.com/ayooshkathuria/pytorch-yolo-v", - "Description": "The workshop will walk the audience on how to implement a state of the art object detector (YOLO: You only look once) from scratch using the PyTorch deep learning framework. The main The aim is not to merely show the audience how to implement the detector that can work on videos, but give them a deep insight about the problems that rear their heads only when one is implementing a deep architecture. Some of these issues include, Rapid Prototyping with PyTorch : Which PyTorch classes and abstractions to use to quickly code up neural network. How to implement a layer if it doesn't already ship with PyTorch. Our detector has 3 such layers! How to deal with complex architectures efficiently : What if your network has more than a 100 layers? Our detector certainly has 106 ! Do we write 106 lines of code for each layer? What if we want to run our detector over a folder containing 100000 images that we can't fit into our RAM at once. Best PyTorch practices to get around problems like these will be discussed. Speeding up Python code with Vectorisation : Python can be a slow language, but PyTorch does provide a lot of functions that are merely wrappers for super fast C code under the hood. Vectorisation and broadcasting will be covered in great detail. Using vectorised code instead of loops to do iterative tasks can give speed ups as much as 100x. Our detector can not work in real time without these optimisations. Managing GPU resources : How to write device-agnostic code, parallelize GPU/CPU ops, practices to reduce redundant GPU memory usage, and how to time GPU code. We will review the entire code base, and spend much time on justifying design decisions. A lot of non-critical code will be provided as it is to the audience, while they are expected to code along when it comes to the critical parts. These parts would be discussed in greater detail. Important PyTorch features might also be demonstrated using toy examples outside the detector code base, which the audience is also expected to code along. A docker image as well as Jupyter notebook will be provided to the audience. Google Colab may also be considered with notebooks provided. Most of the tutorials online demonstrate how to write code that is more proof-of-concept rather than being performant. When it comes to learning to code complex architectures, especially when we are transitioning from beginner to intermediate stage, most of us have to rely on the laborious process of reading open source code. The idea of this workshop is to help audience move along this journey", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Knowledge of Python Basic understanding of convolutional neural networks, image classification and preferably, but not necessarily object detection (Will spend 15 min or so giving an overview of YOLO algorithm) Basic understanding of PyTorch (the level that can be reached by taking the official 60 min tutorial)", - "Section": "Data science", - "Speaker Info": "I'm currently an research intern at a DRDO Lab where I work on video semantics, detecting violence as well as unusual activity in surveillance footage. My other interests include weakl supervised, unsupervised learning and generative modelling using GANS. I've recently graduated college, and while at college, I founded AI Circle, SMVDU, a club dedicated to helping students get started with machine learning through lectures and hands-on sessions, many of which were conducted by me. I am very passionate about sharing what I've learned, and write articles regularly at Paperspace and Medium", - "Speaker Links": "Paperspace blog: https://blog.paperspace.com/author/ayoosh/ Medium : https://medium.com/@ayoosh Github : https://github.com/ayooshkathuri", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ayoosh Kathuria (~ayoosh)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-implement-a-yolo-object-detector-from-scratch-using-pytorch-and-opencv~aQq9a/", - "title": "How to implement a YOLO object detector from scratch using PyTorch and OpenCV" - }, - { - "Content URLs": "in progres", - "Description": "Data classes have been introduced in Python 3.7 (Refer to PEP 557 -- Data Classes). This talk is to introduce data classes to the audience. Talk about why data classes and how they are different from other alternatives like named tuples, et", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Knowlede of Object Oriented Programming with Pytho", - "Section": "Core python and Standard library", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.\nI have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delhi I have done a talk \"How import works in Python\" at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar\nlinkedin profile - https://www.linkedin.com/in/sasidonaparthi\ntwitter handle - @sdonapa", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/what-you-need-to-know-about-data-classes-in-python-37~dRrEd/", - "title": "What you need to know about data classes in Python 3.7" - }, - { - "Content URLs": "Would be uploaded soo", - "Description": "My talk would be starting from the very grounds of machine learning . What is it and how is it connected with our biological brain. I will be introducing some biological concepts and infrastructure of our brain to explain to them how our natural ability of thinking and deduction work, because at last the whole field of artificial intelligence is just an attempt to mimic our brain. Isn't it?\nThis will be through a series of fun QnA . Then we will see the mathematics core which enables us to lay down the logic and basics of the brain as formulas . \n- Then we will start with the classic linear regression . Will study the basic idea behind it and also see what kind of problems we should apply it.\n- Next will be the logistic regression , a classification algorithm. Learn the difference between these two and how logistic regression could be implemented and study the beautiful mathematics behind it. \n- Then we will go for a clustering algorithm, that is, Knn . Study the simple dynamics and application of this algorithm\n- Then a glimpse over the structure and mathematics of neural network . As this talk is for the novice I would keep the mathematics to the minimum and would no go deep into \"deep\" learning.\nWe will wrap up seeing some of my projects in action so that the audience could feel the power of AI", - "Last Updated": "27 Jun, 2018", - "Section": "Data science", - "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", - "Speaker Links": "udayupreti.m", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "uday1201", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/evolution-and-basics-of-machine-learning~bWzxa/", - "title": "Evolution and basics of Machine Learning" - }, - { - "Content URLs": "http://www.thedurkweb.com/automated-anonymous-interactions-with-websites-using-python-and-tor", - "Description": "Need to get some repetitive task done on your web browser? Want to automatically fill boring forms? Or maybe you want to crawl pages that annoyingly check whether you are a browser or a robot. Or maybe you want to repeatedly bias an online poll in your favour (as long as you don't harm anyone). Circumvent all of that with Selenium, the browser automation tool. And if want you want to protect your IP while doing it then just fire up tor-selenium browser, which gives you the power of tor and browser automation. In this talk: I'll show you how to set up the browser. How to access the website through code. How to design your script to navigate through the pages and button clicks. How to effectively do your activity, like filling up text fields etc. And then a demo of it working completely.", - "Last Updated": "27 Jun, 2018", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ved Mathai (~ved47)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automate-anything-on-the-web-using-python-bindings-for-tor-selenium-and-hide-your-ip-while-doing-it~eVyXd/", - "title": "Automate anything on the Web using Python bindings for Tor-Selenium and hide your IP while doing it." - }, - { - "Description": "Need to understand the customers better way based on the attitudes and then serve better and also find the algorithm by which we can classify the future customer", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Python , Jupyter notebook and some statistical conceptual understandin", - "Section": "Data science", - "Speaker Info": "A doctor in statistics from Osmania University. I have been working in the fields of data analysis and research for the last 14 years. My expertise is in data mining and machine learning \u2013 in these fields I\u2019ve also published papers. I love to play cricket and badminton", - "Speaker Links": "https://www.linkedin.com/in/statsvenu\nhttps://www.linkedin.com/in/suresh-chekuri", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "statsvenu manneni (~statsvenu)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-customers-in-better-way-a-market-research-application-using-python~bYB2d/", - "title": "Understanding customers in better way- A Market research application using python" - }, - { - "Description": "root@pycon2018:~# python zer0-day_exploit.py [+] Checking for vulnerability.... [+] Triggering BoF.... [+] Sending staged payload... [+] Waiting for server response... <=HeLL0 fri3nd=> Do you want to know how hackers use Python for development of their hacking tools and arsenal? Have you ever thought how hackers compromise vulnerable computers around the globe with the power of automation that comes with python? If you are looking for answers to these quentions then you have come to right place... In this talk, I will demonstrate various use cases of python programming in hacking and cybersecurity. We will go through various python libraries such as Sockets, Httplib2, Scapy, Shodan etc. In the beginning, we will see the various Python implementations to perform computer networks auditing and attacks such as port scanning, ARP spoofing, DoS attack and remote code execution with buffer overflow vulnerability. Shodan is the search engine for computers and IoT devices connected to the internet around the globe and has API wrapper as a python library. With shodan, I will demonstrate how we can look up for IoT devices. We will see python script in action using shodan to find MQTT brokers to extract GPS information out of them via CVE-2017-7650 vulnerability and due to poor access control list configuration in them", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Python programming Basics of computer networking", - "Section": "Networking and Security", - "Speaker Info": "I am Chirag Jariwala ( @CJHackerz ), B.Tech (4th year) Information Technology student from SRM Institute of Science and Technology - Chennai. I am independent cybersecurity analyst and researcher and have been self-learner in this space quite for a while. I use lots of python scripting in my hacking adventures. I have done numerous workshops and training to teach people about ethical hacking and penetration testing inside my university campus. Have been active community member and given few talks at Null Chennai Chapter (an open source cyber security community which hosts meets for OWASP)", - "Speaker Links": " GitHub: https://github.com/CJHackerz Twitter: https://twitter.com/cjhackerz LinkedIn: https://www.linkedin.com/in/cjhackerz/ Null community profile: https://null.co.in/profile/8808-script-alert-chirag-jariwala-script", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Jariwala (~chirag18)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/journey-into-the-world-of-hacking-and-cyber-security-with-python-programming~e1zma/", - "title": "Journey into the world of hacking and cyber security with Python programming" - }, - { - "Description": "Django as a web framework Django is one of the most powerful web frameworks out there! (This is definitely subjective) According to stackoverflow , python has ~10% developer base. They also predict that by 2020, the developer base would be 16-19%, if it grows at the same pace, making it the leader. Usage of python for web development has been increasing significantly. When it comes to python web framework, Django is the name that rings the bell. Will discuss about a social media processing data pipeline that can be processed using the frameworks available for python. Discuss about the pitfalls to be taken care of and advantages of using these.", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Python Basics of web development Rest APIs", - "Section": "Core python and Standard library", - "Speaker Info": "I am Rahul Reddy, graduated from IIT Varanasi, Product Lead at Setuserv informatics PVT Ltd. I lead a team building data analytics pipelines that handles more than 200-300 Million records a month. Enthusiastic about building even larger, robust, secure data pipelines", - "Speaker Links": " Stackoverflow LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "rahul reddy (~rahul01)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-chained-from-personal-interactive-websites-to-complex-data-pipelines~eZD5b/", - "title": "Django Chained - From personal interactive websites to complex data pipelines" - }, - { - "Content URLs": "To be uploade", - "Description": "Sarcasm is an intensive, indirect and complex construct that is often intended to express contempt or ridicule. But in speech, it is multi-modal, involving tone, body language, and gestures along with linguistic artifacts used in speech. Sarcasm in the text , on the other hand, is more restrictive when it comes to such non-linguistic modalities. This makes recognizing textual sarcasm more challenging for both humans and machines. Sarcasm detection plays an indispensable role in applications like online review summarizers, dialog systems, recommendation systems and sentiment analyzer . This makes automatic detection of it an important problem. However, it has been quite difficult to solve such a problem with traditional NLP tools and techniques . So we will talk about the ongoing research and techniques developed to counter these problems. I have been trying to solve this problem for a while now so let's discuss it and hope that we solve it in the near future. Some of this techniques include tracking physiological gestures like eye tracking, extraction of psychological triggers or building a sarcasm dataset with the help of context features ", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "The only thing I require from the audience is their attention and interest in this fun but a very serious problem in the world of data science", - "Section": "Data science", - "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", - "Speaker Links": "udayupreti.m", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "uday1201", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sarcasm-detection-in-natural-language-processing~eXAga/", - "title": "Sarcasm Detection in Natural Language Processing" - }, - { - "Description": "About a month ago my inbox was flooded with emails beginning with We have decided to update our Terms and Conditions... . Though I am a technical person working in a financial services company and thus terms and conditions are supposed to be my cup of tea, I couldn't get myself to go through any of the actual Terms and Conditions . A python based Natural Language Processing Engine to summarize the often twisted contents of a legal agreement and defining the pros and cons for the agreement in question for the user would better equip an user to understand what exactly they are agreeing to. This is very important in today's age where we've seen our personal data being breached for the benefit of social media based companies who then sell this data to achieve gains that could be political too. In the financial and legal world such documents are of utmost importance. The process of developing a solution like this would be about defining the Gives and Takes of an agreement. Every agreement consists primarily of the things that a user is expected to receive from the other party/user and vice versa. The next step would be quantifying that particular give or take. This would give the user an estimate of what he/she would be expected to give/spend. Comparing that with the takes would help the user make a decision as to whether to agree with the terms and conditions or not. The quantifying system could consist of a number of attributes and the \"twisted ones\" or the ones affecting the user's privacy or other sensitive aspects cold be flagged appropriately so that the user can review and choose. This talk would talk about the steps, right from defining legal contexts to setting up the words, phrases and understandings for typically legal content", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Anyone who'd want to see themselves make better decisions and understand how agreeing to certain Terms and Conditions could affect their lives and their privacy", - "Section": "Data science", - "Speaker Info": "Aroma is a graduate fresh out of the National Institute of Technology, Warangal. As a techno-activist she has been a part of many projects that promote diversity and inclusion. She believes that Automation is the path to Inclusion. In 2016, a teammate of her \"Shoes for the Visually Impaired\" project presented it at the FOSSASIA. She reads, writes and enjoys walking to explore places. She presently works in a financial services firm and believes that solving problems that she has would solve problems for a large chunk of the world. An ML enthusiast she has about 20+ Coursera Certifications with the respective project work to support her learning in that field. Python is one of her favorite languages and hackathons her favorite party", - "Speaker Links": "Aroma Rodrigue", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "ARodz (~AromaR)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-nlp-to-demystify-terms-and-conditions-and-summarize-the-contents~b2Aza/", - "title": "Using NLP to demystify \"Terms and Conditions\" and summarize the contents" - }, - { - "Content URLs": "Slides Talk Specific Slides On Their Way References QN-S3VM Python Package: http://www.fabiangieseke.de/index.php/code/qns3vm Semisupervised Learn Python Package: https://github.com/tmadl/semisup-learn S3VM Seminal Work: https://papers.nips.cc/paper/1582-semi-supervised-support-vector-machines.pdf", - "Description": "Machine Intelligence algorithms, in their application to real world problems, are largely models trained in a supervised manner. Hence, they are hindered by the reality that in most practical situations unlabelled data is easier to come across and obtaining appropriately annotated and labelled data may be prohibitively expensive. Herein lies the appeal of semi-supervised learning algorithms that allow us to draw inferences with only a few labelled data samples existing among a vast amount of unlabelled data. In this talk. through the application of a variation of the tried and tested SVM, called the S3VM(Semi Supervised SVM) on standard dense and sparse data sets, we will explore the merits and demerits of semi-supervised learning. We will also take a cursory look at a few approaches used to solve the modified optimisation problem that arises when we adapt the SVM for use in a semi-supervised setting. The outline of the talk will broadly be the following: Why Semi-Supervised Learning Advantages of using Semi-Supervised algorithms rather than Supervised algorithms on limited data Approaches to Semi-Supervised Learning: Transduction vs Induction+Deduction Modifying the SVM for Semi-Supervised Learning Approaches for solving the modified SVM: Label-switching vs deterministic annealing Semi-Supervised Learning is not a silver bullet: Discussion of disadvantages", - "Last Updated": "28 Jun, 2018", - "Prerequisites": " Familiarity with Python Programming Minimal proficiency in Optimisation Methods Intermediate proficiency in Support Vector Machines", - "Section": "Data science", - "Speaker Info": "I'm Indraneil Paul, a final year Computer Science student at IIIT Hyderabad. I have been involved in machine learning, computer vision and mathematical optimisation for the best part of the past three years due to my research work. I was previously working in the Computer Vision lab on an autonomous driving project and am currently working on applying graph based machine learning models to social networks. I was also a Google Summer of Code '17 student under electric vehicle startup Green Navigation (now nav-e). I occasionally foray into experimentation with Blockchain technology with Hyperledger", - "Speaker Links": "Github: https://github.com/iNeil7", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "iNeil77", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/semi-supervised-learning-with-svms-in-python~e3pRa/", - "title": "Semi Supervised Learning with SVM's in Python" - }, - { - "Description": "Why a JavaScript talk at PyCon? JavaScript has become a crucial view for Pythonic data analysis via Jupyter Notebooks. Jupyter widgets have taken python data from read-only to a rich, interactive experience. This talk will focus on providing a delightful and consistent user experience across all platforms. Specifically, we\u2019ll talk about why we should want Jupyter to reuse our JavaScript ecosystem and how we achieve this. Finally, we\u2019ll end with a vision for enabling data to render similarly regardless of whether you view it in a Jupyter notebook, email, or a flask/nodejs powered website", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Familiarly with Jupyter Noteboo", - "Section": "Core python and Standard library", - "Speaker Info": "I am a developer for the JavaScript team at the D. E. Shaw group. One of our core principles is that users come first; we are hyper focused on improving the user experience for developers, technical users, and non-technical users of everything from intranet sites to the interactive python environment. We aim to delight", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marc Udoff (~mlucool)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-enterprise-javascript-ecosystem~b6vRb/", - "title": "An Enterprise JavaScript Ecosystem" - }, - { - "Content URLs": "Talk specific slides will be updated soon. References: https://docs.python.org/3/library/unittest.mock.html https://docs.python.org/3/library/unittest.mock-examples.htm", - "Description": "Testing is one of the cornerstones of good software engineering. It addition to help ensure that your code works as expected, it also has the advantage of iterating over your code faster. With sufficient tests, you can be pretty sure that your new code doesn't break any old ones. One of the biggest issue I find with writing tests is that there is a lot of boilerplate code that needs to be written to get even the basic unittests to work. This talk will focus on mock and patch . These are awesome utilities provided with unittest module to make your testing life much more painless but not a lot of people know about them. The flow of the talk will be as follows: Intro to testing: Why do we actually need testing? The basic problem I find with testing: Boilerplate code. (with examples) Introduction to MagicMock and patch . Applying them to real tests. Enhancing those tests: Assertions on mock. Caveats associated with their use.", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Some basic knowledge about unit testing in Python would be great", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a student at IIIT-Hyderabad on the verge of completing my M.S.\nFor the last two years, I have also been working part-time as a sysadmin for all institute servers and was involved in maintaining services like proxy, directory and the mail server. I have previously interned as a Production Engineer for Facebook and am currently a Google Summer of Code intern with CCExtractor", - "Speaker Links": "Github LinkedIn Blo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aaditya M Nair (~AadityaNair)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/supercharge-testing-by-mocking~b4qxd/", - "title": "Supercharge Testing by Mocking" - }, - { - "Description": "Less technical people are often afraid of terminal and command line utilities, but are happy to enter the same data on a website. What if Jupyter Notebook could provide cheap, human-friendly UIs for everyone? Less technical people are happy to interact with graphs and tables, but even with Jupyter Notebook, they are anxious to run cells. What would a permissioned nbviewer look like for enterprise? The goal of this talk is to get you thinking about how to use Jupyter to enable rapid-development and low-cost solutions to empower those without technical know-how in constrained environments", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Familiarly with Jupyter Noteboo", - "Section": "Others", - "Speaker Info": "I am a developer for the JavaScript team at the D. E. Shaw group. One of our core principles is that users come first; we are hyper focused on improving the user experience for developers, technical users, and non-technical users of everything from intranet sites to the interactive python environment. We aim to delight", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marc Udoff (~mlucool)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/empowering-the-less-technical~e5r8a/", - "title": "Empowering the Less Technical" - }, - { - "Content URLs": "This GitHub repo links to any content relevant to the talk", - "Description": "This talk intends to provide a fairly gentle introduction to the fundamental ideas behind quantum computing and the concepts of quantum physics that allow quantum computing to surpass the limits of classical computing. We then proceed to a quick demo of using the QISKit Python SDK provided by the IBM Q team to run experiments on a simulated (or real) quantum computer", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "This talk touches upon a topic that doesn't have any hard and fast prerequisites (apart from Python syntax, of course), but basic knowledge of the following topics will make things easier to grasp during the talk and later down the line: Some idea of what quantum physics is The concept of a quantum superposition of states Familiarity with linear algebra (not really for the talk, but will help later down the line)", - "Section": "Others", - "Speaker Info": "I'm a full-stack JS developer, Python enthusiast and Rust lover who revels in learning new technologies. I enjoy sharing my knowledge and the company of witty people", - "Speaker Links": " GitHub LinkedIn My Tech Blog on Medium", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ajmal Siddiqui (~ajmalsiddiqui)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-quantum-computing-with-the-qiskit-sdk~e9yDe/", - "title": "Introduction to Quantum Computing with the QISKit SDK" - }, - { - "Description": "Nearest Neighbour(NN) algorithm, which is a lazy and a non-parametric method used for classification is one of the most intuitive and widely used machine learning algorithms. It is most often sought by business consultants for its simple and easy to understand framework. The performance of the algorithm can be enhanced by optimally tuning its hyper-parameters, which includes the k-value and the distance metric. However, practitioners tend to focus only on optimising k and ignores the other. The very term \"nearest-neighbour\" means that we employ some notion of near, i.e. we use some distance metric to quantify similarity and thus define neighbours. This emphasises the importance of the Distance Metric in the NN algorithm. In this talk, we present some of the novel approaches used, to learn the distance metric from the training data. Also, we demonstrate how slight amendments to the approach can lead to an inception of a dimensionality reduction technique. The above mentioned approaches are bundled together as a python package and is showcased to the audience. Structure of the Talk: 1. An overview of K-NN algorithm\n2. Theory of Distance metrics\n 2.1 Mathematical definition of a metric\n 2.2 Some common distance metrics\n3. Deep dive into Metric Learning techniques\n 3.1 Why is it important?\n 3.2 The math behind metric learning \n 3.3 Application in Dimensionality Reduction\n4. Implementation using some popular dataset", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Basic programming skills in python, machine learning(familiarity with common classification and dimensionality reduction techniques) and linear algebra", - "Section": "Data science", - "Speaker Info": "Kousik is pursuing his undergraduate studies at Chennai Mathematical Institute and shows immense interest in Machine Learning and Finance. He has contributed to multiple open source projects and has interned with the research and development teams of various organisations. His primary research interests include computer vision, graph based machine learning algorithms and quantitative finance. He has also involved in different technical talks at IIT-M and is one of the members of the Chennai Python Meetup group", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kousik Krishnan (~kousik)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/comprehensive-study-of-distance-metric-learning-in-nearest-neighbor-algorithm~e7w1e/", - "title": "Comprehensive Study of Distance Metric Learning in Nearest Neighbor Algorithm" - }, - { - "Description": "SQL is a powerful tool. It is the simplest way to analyse a dataset. In recent times however unstructured data has started to get a lot of mileage. A lot of effort is spent in converting this to structured data. Some Statistics 80% of the data is unstructured As more people go online, it will lead to generation of more unstructured data. Currently the count sit at 3 billion people, so there is a lot of capacity for data overload in the coming days SQL is the world's easiest and most used programming language. The reason it is most used is because of its simplicity and power What I want to propose is a tool that will help analysts directly use SQL on text data. This will be more than just applying NLTK functions on the SQL text. It will involve the following components Data Structures ( similar to RDBMS etc) Parsing Ability to join etc Advantages The entire world of text data will be open for people with basic SQL skills to analyse. This will not just help in more productivity but help in seamless integration of business and technology Cross functional text data can be analysed easily Injection of populated knowledge graphs etc will ensure that new information gets added easily SQL will help reporting/logic storage very easy", - "Last Updated": "28 Jun, 2018", - "Prerequisites": " Python Jupyter SQL", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a data scientist at Morgan Stanley. I have been working in the analytics domain for the past 7 years\nI love applied machine learning and have been working in this capacity for the past 3 years", - "Speaker Links": "https://github.com/anantguptadbl https://www.recommendbot.in https://www.linkedin.com/in/guptaanant/ https://www.simplyanant.blogspot.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anant Gupta (~anant79)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sql-on-text~egGke/", - "title": "SQL on Text" - }, - { - "Content URLs": "Will share slides link soon.. Key Takeaways from the talk: Why we decided to build our own machine learning platfrom from scratch How to build machine learning platform using python Lessons Learned while building machine learning services How to extend this platform by distributed computation engine like Spark and deep learning platform like tensorflow", - "Description": "Abstract The purpose of this talk is to describe how helpshift has leveraged python ecosystem to build a machine learning platform without using any third party framework, and how you can build one too. In particular, You can learn how to build the following components of machine learning platform using python from this talk. How we use python celery framework to distribute model building tasks\n to celery workers How models heavier in size can be served to prediction node in real time How to monitor model building tasks on celery worker Python data science stack in Helpshift - Numpy, Scipy, Scikit-learn, etc Python libraries/framework used - Celery, S3/Azure Storage, Bottle, etc Description Helpshift provides customer service platform to around 2000+ companies across various business domains like gaming, e-commerce, IoT, banking, entertainment, travel, hospitality, productivity apps and many more. Helpshift provides a suite of ML features that include auto ticket classification, FAQ suggestions to user query and other features. As each company using our platform has a different business domain, we build separate ML models for each of our customer and for each of feature. To handle thousands of models and CRUD operations on them in production, we needed highly scalable and reliable machine learning platform for model building and serving models. Possible solution was to use Spark or Tensorflow for model building. But these frameworks did not provide facility to store thousands of models, and serve those for prediction in production. We decided to use celery framework for distributing model building tasks to celery workers and use core python data science libraries to build models. Model building using celery worker Each Celery worker in ML platform is registered to one or more model building queues. Each type of task is associated with one celery queue. In real time, the backend server submits model building task to pre-defined celery queue. One of available celery worker picks the pending task, builds the model and pushes it to blob storage like s3/azure with new model version. Model management in s3/azure We have written python wrapper around s3/azure client library to provide all required CRUD operation on models in s3. CRUD operations are simple operations like get_model, put_model, update_model with some version. Serving models to prediction Nodes Model size ranges from 5 - 25 mb. To do predictions within 30 ms, we have to either load all models in memory or store them on local disk of each prediction nodes. We decided to store all the models on local disk as loading them in memory was not a scalable approach. The challenge here is, whenever a particular model is updated, it has to be copied on each prediction node. A python service on the prediction node takes care of syncing updated model from s3 to local disk. Prediction service Prediction service is gunicorn server which fetches model from local disk and does prediction on incoming requests. Monitoring model building task running on celery worker As there are always some jobs in celery queue waiting for celery worker, we built active monitoring service which tracks the status of each submitted task. Monitoring service decodes metrics from celery worker to find failure of task and time spent by each task in waiting/running state. For any task that crosses the threshold time for wait or run state, an alert is sent", - "Last Updated": "28 Jun, 2018", - "Prerequisites": " Basic knowledge of Python ecosystem Interested in building scalable machine learning platform", - "Section": "Data science", - "Speaker Info": "Hello, I am shyam shinde , actively developing machine learning platform at helpshift . I have diverse experience in developing backend systems, designing and developing system to handle big data. Developed production systems using Java, Clojure and Python. Currently, interested in deploying machine learning services at scale. As side projects, I learn machine learning concepts and try to implement them. Apart from that, I like trekking, reading books and watching movies", - "Speaker Links": "GitHub LinkedI", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shyam Shinde (~shyam91)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-helpshift-built-machine-learning-platform-using-python-at-large-scale~e0mLa/", - "title": "How Helpshift built machine learning platform using Python at large scale" - }, - { - "Content URLs": "TB", - "Description": "Web crawling is hard. Large scale web crawling - which involves crawling millions of web pages in a month across 500 to 1000 websites, is even harder. Python comes with a number of libraries which allow you to do such crawling-at-scale but a lot of real-world issues have to be tackled to get the crawling infrastructure right Some of which are, Crawl rates - You need to strike the right balance here to make sure you don't crawl too aggressively but at the same time don't crawl too slow that the crawl finishes too late. Right Data - You need to make sure you crawl the right parts of the websites to get the right data you want. Dont get blocked! - Crawling from the same set of IP addresses will get you blocked across most modern websites. One needs some kind of rotating web proxy infrastructure to make sure that crawls can continue without getting kicked out. Capturing Errors - How to capture crawling errors so you can detect most issues and surface them up, while doing distributed crawling. Having nearly a decade of experience writing custom web-crawlers, the speakers have developed a set of custom tools to make crawling easy and painless. One of this is a tool to create a set of rotating web proxy caching nodes which use Squid and frontend by a HTTP load-balancer. The other one is a distributed crawler which uses Django as the middleware to distribute crawling across multiple crawler nodes while managing crawls at one place. In this talk, the author(s) discuss about one such tool they have created and have successfully used in multiple businesses and software companies over the last 3 years. The tool allows one to quickly and cheaply create an infrastructure of custom web proxy nodes which supports multiple VPS backends. Using this tool one can rune an industrial strength web crawling infrastructure with a set of rotating proxies of up to 50 nodes with a monthly cost of just under 300 $. The authors will talk about their experience and background creating and using the tool over the years, how it works with any web-crawler and the open source nature of the code which allows it to support different infrastructure backends and also the Squid configuration for the nodes which allows to hide the IP addresses behind the crawler. The other tool is a distrubuted web crawling monitor and management tool which uses Django to schedule and manage crawls across multiple nodes via Redis and simple HTTP APIs with the crawls performed via Scrapy derived crawlers", - "Last Updated": "29 Jun, 2018", - "Prerequisites": " Some knowledge of web crawling and or web scraping. Any knowledge of Scrapy and some experience using it is very handy Knowledge of HTTP proxy servers is a huge plus.", - "Section": "Developer tools and Automation", - "Speaker Info": "Anand B Pillai is a technology professional with 20 years of software development, design and architecture. He has worked in a number of companies over the years in fields ranging from Security, Search Engines, Large Scale Web Portals and Big Data. He is the founder of the Bangalore Python User's Group and the author of Software Architecture with Python (PacktPub, April 2017). Anand has a lot of experience in web-crawling having written the original Python web-crawler HarvestMan in 2005 and developing a number of custom crawlers for various startups solving various problems. Anand is currently VP of Engineering at the early stage Legal Tech startup, Klarity Law. Noufal Ibrahim is the CEO and Founder of Hamon Technologies at Calicut, Kerala. He was key to starting the very first PyCon India conference in 2009 and has since been involved in the conference closely throughout the years. Noufal was the keynote speaker of PyCon India 2017. Noufal has made a name not just by his Python community activities, but also by his creative Python introductory talks he has conducted in various universities and institutions in Kerala. He is also a professional trainer in Python and git. Both Noufal and Anand are Fellows of the Python Software Foundation (PSF)", - "Speaker Links": " Anand B Pillai - https://twitter.com/skeptichacker Noufal Ibrahim - https://twitter.com/noufalibrahim , http://hamon.in/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anand B Pillai (~pythonhacker)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/large-scale-web-crawling-using-python~bkl6d/", - "title": "Large scale web crawling using Python" - }, - { - "Content URLs": "Slides will be uploaded soon", - "Description": "Almost all of us have used VLC, simply because it's so good at what it does. Reads multiple file formats, transcodes videos, makes basic filtering (brightness correction,etc) effortless, and so on. VLC uses libavcodec in the backend, which is just a way for it to access FFmpeg 's api. But have you ever wondered what makes VLC (via ffmpeg) so efficient? At this talk, we will take a look at what it takes to build a video transcoder in python as efficiently as FFmpeg . It will cover Basics of computer vision - What are images and videos really, how they are stored and managed How to handle videos in python using OpenCV, an open source computer vision library Basics of concurrency and parallelism in Python How to use parallelism effectively to handle videos", - "Last Updated": "29 Jun, 2018", - "Prerequisites": " Basic understanding of OpenCV and threads is preferable Working knowledge of Python", - "Section": "Core python and Standard library", - "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", - "Speaker Links": "R S Nikhil Krishna Personal Website Github Linkedin StackOverflow Lokesh Kumar T Github Linkedin StackOverflow", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-to-beat-vlc-and-ffmpeg-at-video-operations~ejkva/", - "title": "Using Python to beat VLC and FFmpeg at video operations" - }, - { - "Description": "Users leave; but their credentials usually stick around. And this leaves a security hole to be filled. Though a lot of services integrate with GSuite but tools/third-party services/ssh credentials - places where individual or shared user accounts are managed out of band - remain a security risk. In the spirit of automation and predictability, we have been working towards a \u201c Centralized User management solution \u201d and automating everythin", - "Last Updated": "29 Jun, 2018", - "Section": "Networking and Security", - "Speaker Info": "I am working as an Information Security Engineer at Grofers. Earlier I was with Makemytrip and Expedia, and have a total of 3 years experience in the InfoSec field. I'm also a part time bugbounty hunter - acknowledged by various MNCs and some top companies of India. I am also an active blogger on Medium where I write about interesting vulnerabilities that I find on my bugbounty journeys. Some of the articles have been published in various Security magazines and newsletters like Hakin9, Bugcrowd. Managing application security, performing penetration testing, hardening network and infrastructure, and automating security tasks to reduce manual effort are some of the things I take care of on a daily basis", - "Speaker Links": "https://medium.com/@logicbomb_1 https://twitter.com/@logicbomb_", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Avinash Jain (~avinash86)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/centralized-user-management~eno7a/", - "title": "Centralized User Management" - }, - { - "Description": "A data scientist's job is usually to train a model often in the form of a jupyter notebook. However, to take this model to production takes different skills, a significant engineering effort and a lot of hidden technical debt accumulated over time. Grace, a platform agnostic deployment framework addresses this problem (thus reducing the machine learning engineering effort) by acting as an orchestration tool to deploy deep learning models in production environment leveraging tensorflow serving , docker and kubernetes. Any deep learning model to be deployed is configurable through a json spec containing input, output, model weights etc,. Other services essential to maintenance like deep-dive monitoring tools, load testing tools, structured centralized logging are provided out of the box", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "python, basics of machine learning/ deep learnin", - "Section": "Developer tools and Automation", - "Speaker Info": "Venkat Karun is a full stack generalist and polyglot with 15 years of experience building high performance, distributed systems including a decade at Google. He enjoys reading up on functional programming and lambda calculus and tinkering with ev3dev and the lego Python ecosystem in his spare time. He is currently working as Chief Architect at NicheAI pvt ltd. Venkatesh Mondi, an aerospace engineer by education worked in ISRO before finding his love for programming and machine learning. He worked as a software programmer in various platforms before co-founding NicheAI pvt ltd . He has been working on a variety of production grade computer vision solutions since it's inception. He can be found experimenting with gadgets, software, mathematics in his free time", - "Speaker Links": "Venkat Karun Venkatesh Mond", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Amith Reddy (~velutha)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/grace-a-deployment-tool-for-deep-learning-models~bqrpd/", - "title": "grace - a deployment tool for deep learning models" - }, - { - "Content URLs": "Python 3.7 Release note", - "Description": "In this talk, we will deep dive into features of Python3.7 breakpoint() Data Classes Customization of Module Attributes Typing Enhancements Timing Precision Order of Dictionaries \u201casync\u201d and \u201cawait\u201d Are Keywords \u201casyncio\u201d Face Lift Context Variables importlib.resources Developer Tricks Optimizations So, Should I Upgrade?", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Core python and its internal", - "Section": "Core python and Standard library", - "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape Tech Enthusiast - Django & Chatbot specialist Mentor/Speaker Build2learn , Chennai Geeks", - "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavani Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Bhavani Ravi (~bhavaniravi)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/whats-new-in-python37~elmMa/", - "title": "What's new in Python3.7" - }, - { - "Content URLs": "https://www.dowhatucant.com/pyconindia18", - "Description": "While introducing people to Python metaclasses I realized that sometimes the big problem of the most powerful Python features is that programmers do not perceive how they may simplify their usual tasks. Therefore, features like metaclasses are considered a fancy but rather unuseful addition to a standard OOP language, instead of a real game changer. This talk wants to show how to use metaclasses and decorators to create a powerful class that can be inherited and customized by easily adding decorated methods", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "An experience working with and developing python programs and a general understanding of the python syntax", - "Section": "Core python and Standard library", - "Speaker Info": "I am just an average guy who got into programming and fell in love with it. 3rd year undergrad at IIT Dharwad and a Google Summer of Code 2018 student with coal", - "Speaker Links": "https://github.com/ishanSrt https://gitlab.com/ishanSrt http://dowhatucant.com/gsoc_archive.htm", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "ishan srivastava (~ishan38)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/metaclasses-and-decorators-a-match-made-in-space~ervpe/", - "title": "Metaclasses and decorators: a match made in space" - }, - { - "Content URLs": "Will be updated soon", - "Description": "It seems like every tech company is slinging around buzzwords like \u201cbig data,\u201d \u201cartificial intelligence,\u201d and \u201cmachine learning\u201d. Machine learning is able to make sense of digital data at a much faster rate than any human is capable of doing and hence choosing the application of ML-Recommendation Systems, tends to be a decision of priorities. These systems are personalizing our web experience, telling us what to buy (Amazon), which movies to watch (Netflix), whom to be friends with (Facebook), which songs to listen (Spotify) etc.\nIn this talk I\u2019ll explain the amount of work going behind this, diving into the mechanism of one such way to build these recommendation systems. OUTCOME After this talk, the audience would be able to understand the actual working of these systems. It involves knowledge of different types of recommendation systems, algorithms used, evaluation of the systems generated, working of deep recommendations \u2013 at last eventually building one(model) from scratch.The talk would answer the queries about the domains of the systems created- media, e-commerce, travel & real estate , education , job-boards, etc.- 'how AI has revolutionized e-commerce.' -giving a clear insights to mechanisms responsible for the same. AGENDA Introduction to recommendation systems. Domains of recommendation systems. Categorising algorithms and their evaluations Describing the python libraries used. Building a music recommendation system using the libraries \u2013 popularity based model & personalised collaborative filtering model Performance analysis of both models & real world instances of recommendation systems. Q & A Session", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Basic knowledge of machine learning & love for pytho", - "Section": "Data science", - "Speaker Info": "Aakanksha Chouhan Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence, occasionally working on blockchain projects. I\u2019m a member of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, Blockchains and Computational Biology. I also regularly participate and give talks in paper-reading sessions and meetups like PyData Amaravati ", - "Speaker Links": "Connect with me on linkedin Twitter email : akankshachouhan98@gmail.co", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "AAKANKSHA_CHOUHAN", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-machine-learning-and-media-building-your-own-recommendation-system-from-scratch~avz5a/", - "title": "Deep Dive : machine learning and media -building your own recommendation system from scratch" - }, - { - "Content URLs": "Tensorflow for poets Fast Image classification using Bottlenecks Tensorflow Debugge", - "Description": "Accelerating Transfer Learning using Effective Caching Technique Transfer Learning is something which has become a routine today. Neural Networks have a lot of parameters (millions of them) which are trained iteratively in a data-driven fashion. With these many parameters come huge representational power (ability to model hyper dimensional complex functions). In cases where we train a custom classifier (say a CNN), we might not be having that much data so the network can easily overfit when trained from scratch. So here comes transfer learning, use the previously accumulated knowledge (in form of weights in neural nets) to learn our problem. In case of fine-tuning also we will be training final layers of the network only. (If you are not aware don't worry this will be covered). Huge networks take significant time train completely. To reduce this time comes methods of effective caching or informally called Training with Bottlenecks This method though is easy to implement, can give very good results. ResNet50 which took 45 sec for an epoch to train using normal transfer learning procedure, now takes 8 sec per epoch. Which is almost 6x speed up! * *Trained on Nvidia GeForce GTX 1050, i5-7300HQ Processor (5 category flower dataset) Learning Outcome Why is Computer Vision difficult problem? The role of Deep Learning in Computer Vision Deep Convolutional Networks for Image recognition Different Convolutional Architectures for Image recognition Difficulty in Optimizing large neural nets and hints for effective training Uses of pretrained models and basis of transfer learning What is Transfer Learning and why is it important? Different methods of Transfer Learning Accelerating training a neural network by caching the non-trainable model's output (Hands on Implementation in keras ) Analysing the speedups and potential limitations in this procedure How to debug Tensorflow Program? This presentation is not about how to debug DL model (Example DL model is not fitting well). Its about how to debug your program in programming perspective . Debugging a tensorflow program can be difficult due to many reasons out of which some are, The concept of computational graph construction Abstraction of tf.Session() many more. So we will introduce commonly used tensorflow debugging tools like (main ones are listed) Tensorboard Tensorflow Debugger tfdbg ", - "Last Updated": "29 Jun, 2018", - "Prerequisites": " Basic understanding of Deep Learning , Tensorflow and keras Working knowledge of python ", - "Section": "Data science", - "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", - "Speaker Links": "R S Nikhil Krishna Personal Website GitHub LinkedIn StackOverflow Lokesh Kumar T GitHub LinkedIn StackOverflow ", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Lokesh Kumar T (~tlokeshkumar)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/accelerating-transfer-learning-using-effective-caching-and-how-to-debug-tensorflow-programs~dwA8a/", - "title": "Accelerating Transfer learning using Effective Caching and How to Debug TensorFlow programs" - }, - { - "Content URLs": "http://openaccess.thecvf.com/content_ICCV_2017/papers/Zhang_StackGAN_Text_to_ICCV_2017_paper.pdf https://pytorch.org/ Slides to be uploaded soon", - "Description": " The workshop is intended to introduce, explore and get a hands on experience on one of the most interesting application of GENERATIVE ADVERSARIAL NETWORKS which is - given the description of an image, the GAN model generates an image according to that description. The workshop is to be divided in two parts: \n1. Giving a hands on of using word embeddings to encapsulate the textual information and basics of how to train a vanilla GAN.\n2. Combining the word embedding and training a 2 stage stacked GAN to generate relevant Image ( We will be providing with pre-trained models as training takes a lot of time ) The workshop would then aim to go over the plausible applications that it could have.\nThe first part of the workshop will be as follows: We would be teaching basics aspects of NLP i.e word embeddings with hands on experience of python libraries NLTK etc. We would be then moving on to the next part where we will teach the basics of how to train a vanilla GAN on their laptops using Pytorch followed by a simple application. We will be providing the audience with Jupyter notebooks with skeleton code and the remaining code will be written on the spot.\nAim of the teaching the training procedure is to get the audience a hang of what parameters to keep in mind while training a Neural Network. The second part of the workshop will be as follows We will be training the Gan using the word embeddings to get a rough Image representation followed by another GAN ( stacked one after other ) to get a full resolution image ( details given in Paper ) We will be providing the trained model of GAN as it requires a lot of time to train the GAN. We will be providing the Jupyter Notebooks giving the architecture and will be writing some parts of the Stacked GAN\u2019s on the spot. We will be discussing the possible applications of GAN\u2019s in both research and industry.", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Basics of NLP ( word embedding ), Basics of Neural Network, Basics of Python numpy and Pytorch", - "Section": "Others", - "Speaker Info": "I ( Sairam ) am currently a research associate at Center for Visual Information Technology, IIIT Hyderabad. I graduated from Electronics Engineering from IIT BHU last year. My experience with Computer Vision is of 4 years, with varied internships at CWNU, South Korea working on face recognition, NTU Singapore working on Maritime vessel detection to Crowd modelling. I\u2019m currently working on Cancer detection from slide images of cancerous tissues.I have been the lead of many workshops and tutorials conducted at my college, for acquainting freshmen with the basics of Vision and ML. Zeeshan is currently a research fellow at Center for Visual Information Technology, IIIT Hyderabad. He has graduated in Electrical Engineering from VJTI, Mumbai. He has an experience of 2 years in developing trading systems at Citi. Currently he is working on gradient estimation for stochastic neural networks", - "Speaker Links": "My LinkedIn profile can be viewed at: https://www.linkedin.com/in/sairamtabibu/ Zeeshan's Profile: https://www.linkedin.com/in/zeeshan-ashraf-508587137", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Sairam tabibu (~sairam)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/synthesising-images-from-text-using-generative-adversarial-networks~epqVa/", - "title": "Synthesising Images from text using Generative Adversarial Networks" - }, - { - "Content URLs": "Contents related to the talk will be added later", - "Description": "During my M.Tech. programme at IIT Guwahati, I observed that researchers in both industry and academia work with testbeds , both real and virtual, for making advancements in Computer Science , whether it is in algorithms, networking protocols or data science by running exhaustive experiments. I realised that Python, being a very versatile language , can be used to do everything related to experimental research and analysis , without requiring the usage of any other scripting language. Based on my experiences, I am presenting a talk to explain how to build automated testbed experiments, data collection and analysis with Python and a few libraries, avoiding big and bulky frameworks as much as possible . My talk is structured as follows: Building a testbed for computing and networking experiments Using Python and paramiko to provison entities (PCs, smartphones, Raspberry Pis, routers, switches, etc.) in the testbed Running tests on the entities with subprocess and paramiko Collecting log files and other trace data from testbed entities Parsing log files and trace information to collect statistics with basic text processing and regex and storing them in appropriate Python data structures like lists, tuples and dictionaries for easy access Analysing collected statistics with Python math and generating reports Visualizing graphs from statistics with python-gnuplot or matplotlib I hope that after attending my talk, you will be able to automate your testbed experiments to the extent of spending less time on experimentation and data collection and more time on actual research and publishing papers", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "There are minimal prerequisities for my talk. You need to have knowledge of the following: Basic algorithms and data structures Computer networks, especially IP addressing Python basics Also you need to have: The willingness to learn and experiment", - "Section": "Developer tools and Automation", - "Speaker Info": "Hello everyone! I am Sunit Kumar Nandi , a Trainee Teacher at National Institute of Technology, Arunachal Pradesh. I have completed my M.Tech. at IIT Guwahati this year and am also enrolling for Ph.D. I am deeply interested in computer networking, telecommunications, operating systems and distributed systems design . I use Python for most of my daily work involving a great deal of experimentation. Apart from that I contribute to SuperX OS , a Linux distribution with KDE, based out of Assam, India. I love BSD and Linux based systems and have been involved with them since my childhood. As a result, I have had 14 years of experience with managing Linux servers, networking equipment and designing automated systems in the simplest way possible. In my free time, I spend my efforts running Techno FAQ , an e-magazine for science, technology, education and business", - "Speaker Links": "You can follow me on: Facebook Twitter My open source contributions: SuperX OS Packages I maintain for Arch Linux: utserver quassel-core-static Other projects I run: Techno FAQ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sunit Kumar Nandi (~sunitknandi)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-testbed-experiments-data-collection-and-visualization-with-python~bo0Xd/", - "title": "Automating testbed experiments, data collection and visualization with Python" - }, - { - "Content URLs": "Will provide the links soon", - "Description": "Apache Spark is an open-source Distributed Computational Framework. It sits on top of Cluster Manager and Distributed Storage. Spark program runs in driver and utilizes Cluster manager to run tasks. Apache Spark has become the most preferred option in the field of Machine Learning due to its faster processing utilizing in-memory computations with Resilient Distributed Dataset (RDD). With the Python being the most preferred language for Machine Learning and Deep Learning tasks, PySpark has become most important weapon in the arsenal of Data Scientists/Data Engineers. PySpark is Python API to the Scala Core of Spark allowing Python programmers access to run Distributed jobs in Spark. This session will introduce you Spark architecture and show how to use PySpark to run Machine Learning tasks on Spark", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Knowledge of Machine Learning Knowledge of Pytho", - "Section": "Data science", - "Speaker Info": "Shashi Jeevan is an author, trainer, architect with over two decades of experience in the software industry working in various domains including Finance, Digital Signage, Rich Media Management, etc. He loves to master new technologies and share his learnings. He regularly presents and organizes free technical sessions through the Hyderabad Software Architects meetup group which he founded in 2015", - "Speaker Links": "https://www.linkedin.com/in/shashijeevan/ https://shashijeevan.com https://github.com/shashijeeva", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Shashijeevan M.P. (~shashijeevan)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-pyspark~egGGe/", - "title": "Introduction to PySpark" - }, - { - "Content URLs": "Slides Deck: https://slides.com/ineil77/deck/fullscreen References Imbalanced Learn Python Library: http://contrib.scikit-learn.org/imbalanced-learn/stable/index.htm", - "Description": "Classification algorithms are known to under perform when faced with data that is heavily skewed towards one class as most of them are designed to work under assumptions of uniform class distribution. Another such caveat is the assumption of uniform cost of misclassification of all samples. For instance in a transaction fraud detection setting, the fraudulent transactions are vastly outnumbered by the genuine ones. Also the cost of wrongly classifying a fraudulent transaction as a genuine one far outstrips the inconvenience caused by flagging a benign transaction as a malicious one. This talk aims to cover the various approaches used to cope with this commonly faced problem: Oversampling Methods Undersampling Methods Synthetic Data Generation Cost Sensitive Learning Key takeaways from this talk: How imbalanced data sets undermine classifier performance How to eliminate class imbalance The advantages and disadvantages of over/under sampling and synthetic data generation Robust evaluation metrics insensitive to class imbalance", - "Last Updated": "30 Jun, 2018", - "Prerequisites": " Basic Python Understanding of basic performance evaluation metrics", - "Section": "Data science", - "Speaker Info": "I'm Indraneil Paul, a final year Computer Science student at IIIT Hyderabad. I have been involved in machine learning, computer vision and mathematical optimisation for the best part of the past three years due to my research work. I was previously working in the Computer Vision lab on an autonomous driving project and am currently working on applying graph based machine learning models to social networks. I was also a Google Summer of Code '17 student under electric vehicle startup Green Navigation (now nav-e)", - "Speaker Links": "Github: https://github.com/iNeil7", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "iNeil77", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-comprehensive-overview-of-dealing-with-imbalanced-datasets-in-python~ejkPa/", - "title": "A Comprehensive Overview of dealing with Imbalanced Datasets in Python" - }, - { - "Content URLs": "CHAOS", - "Description": "Software development projects, in particular the open source ones, heavily rely on the use of tools such as Git, GItHub and mailing lists to support, coordinate and promote their development activities. \nDespite their paramount value, they contribute to fragment the project data, thus hindering the work of both practitioners and researchers to collect, clean, link and analyse this data to derive insightful analytics about the software project. In this context, the Community Health Analytics and Open Source Software (CHAOSS) project, under the umbrella of the Linux Foundation is currently working towards analysing open source communities and how they function. This talk presents GrimoireLab, a Python-based open source platform, part of CHAOSS. GrimoireLab allows us to seamlessly analyse open source projects, measuring their activities, processes and communities.\nWe will discover the tools composing GrimoireLab and learn how to use them. At the end of the talk we will know how to: Collect data in an automatic and incremental way from almost any tool related with contributing to open source development (e.g., source code management, issue tracking systems, forums), Enrich the collected data with additional information like contributors affiliation and geographical data as well as manage and unify identities (e.g., emails, username) belonging to the same contributor. Visualize your project data through interactive dashboards and reports. I will also touch upon my experience as a Google Summer of Code-18 student under CHAOSS and how you can participate in the community and contribute to the project", - "Last Updated": "30 Jun, 2018", - "Prerequisites": " Willingness to learn about new tools Interest in Open Source Development [A must] A good understanding of how APIs work Knowledge about how the command line works Basics about how Elasticsearch works is appreciated but not necessary", - "Section": "Data science", - "Speaker Info": "Hey!! I am Pranjal Aswani. I recently finished my engineering from TCET, Mumbai . I am an Open Source enthusiast and a Python Dev. As you might have guessed from my Proposal, I am working with CHAOSS under GSoC-18. I have a high interest in Data Analysis and this is going to be my first PyCon talk! (if selected :P) If you are a potential employer or just want to talk, please feel free to visit my website for more information! (link below", - "Speaker Links": " aswanipranjal.github.io blog GitHub LinkedIn Twitter", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pranjal Aswani (~pranjal2)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-is-your-open-source-project-doing~bklNd/", - "title": "How is your Open Source project doing?" - }, - { - "Content URLs": "Info about selenium: http://selenium-python.readthedocs.io/getting-started.html Project repo: https://github.com/pareksha/WhatsApp-Automatio", - "Description": "I was fed up with the daily 'Good Morning' messages I had to send to my crazy not so important friends as well as waking up till midnight just to send 'Happy Birthday' messages. I decided to automate all this stuff and I found 'Selenium' to be just fit for the purpose. Selenium is simply a web browser automation tool but what you can do with it is totally up to your imagination. This talk will be about the numerous crazy ideas you can implement using Selenium including automating WhatsApp messaging like wishing birthdays at midnight and sending bulk messages on one click. The talk will also include how quickly and easily these things can be implemented using Selenium", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Knowledge regarding basic python syntax (or of any other programming language)", - "Section": "Developer tools and Automation", - "Speaker Info": "Currently, I am a Google Summer of Code intern with coala . I love coding and python is my favorite programming language. Regarding college, I am a CSE 2nd year undergrad at UIET, Panjab University", - "Speaker Links": "GitHub: https://github.com/pareksha GitLab: https://gitlab.com/pareksha GSoC blog: https://pareksha.wordpress.com/ LinkedIn: https://linkedin.com/in/pareksha", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pareksha Manchanda (~pareksha)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-messaging-using-selenium~bmn9d/", - "title": "Automating messaging using Selenium" - }, - { - "Content URLs": "Will be updated soon", - "Description": "If things work out as you\u2019ve envisioned, there will be a time in your webapp\u2019s lifecycle when it\u2019s serving a large number of users. By the time things get to this point, it\u2019s ideal if you\u2019ve architected your webapp to both scale gracefully to meet this load, and also be resilient to arbitrary failures of underlying compute resources. This talk is about how you can use Docker containers and Kubernetes to help your Django webapp achieve these architectural goals. While it meanders a bit through theory and philosophy, it does work up to a concrete example to help solidify concepts", - "Last Updated": "30 Jun, 2018", - "Prerequisites": " Basics of Linux Familiarity with Docker and docker files Kubernetes(optional)", - "Section": "Core python and Standard library", - "Speaker Info": "Hello I am Jaipreet Singh. I am a Sofware developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", - "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Jaipreet Singh (~Jaipreet95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/maintaining-scalability-of-django-powered-web-app-by-using-containers-and-kubernetes~bqr0d/", - "title": "Maintaining scalability of Django powered web App by using containers and Kubernetes" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Objective To explain the various design patterns that Django programmers use and prevent reinventing the wheel in each of your projects. Takeaways of this talk would be to know the answers to: What are the current best practices in Django and what are not?\nWhich are most common and useful design patterns?\nHow to identify and implement these patterns? Description Design Patterns are patterns we see and code in almost every Django projects. They are scenarios for which we wished had a canonical and elegant solution. Based on the seminal work on design patterns in the Gang of Four book and Martin Fowler's book, the talk takes you through several well known design patterns to improve your Django code. It might also cover several new patterns in web application development that you can apply to other frameworks", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Basic knowledge of OOPS and Python\nShould have completed atleast one Django Projec", - "Section": "Core python and Standard library", - "Speaker Info": "Hello I am Jaipreet Singh. I am a developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", - "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Jaipreet Singh (~Jaipreet95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/design-patterns-in-python-and-django~epqpa/", - "title": "Design Patterns in python and Django" - }, - { - "Content URLs": "http://pyflyby.or", - "Description": "Python is a wonderful programming language because of its lack of boilerplate. However, one remaining area of boilerplate is import statements. When writing a python program, it's tedious to go back and forth to the top of the file to add and remove import statements. When using Python interactively, it's tedious to type import statements. I have created a tool called Pyflyby to automate imports. Pyflyby has two killer features. (1) With one button, Pyflyby automatically modifies your Python code to add necessary imports and remove unnecessary imports. You can integrate into your editor or use the command-line tool. (2) Pyflyby enhances IPython/Jupyter to automatically import symbols on-demand. I started Pyflyby in 2011 as a side project. It has become wildly popular within my firm; most developers at my firm swear by it. I recently open sourced Pyflyby to make it available to the community. In this talk, I will present how to use Pyflyby, how it works, and how it has changed Python development at my firm", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "Non", - "Section": "Developer tools and Automation", - "Speaker Info": "I have been a developer in the asset management division of the D. E. Shaw group since 2009. I also manage the Python infrastructure group at the firm", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Karl Chen (~quarl)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pyflyby-automatic-imports-for-python~erv4e/", - "title": "Pyflyby: Automatic imports for Python" - }, - { - "Content URLs": "Will be updated soon", - "Description": "In this talk the enthusiasts will get to see the integration of Django, DRF, Django Channels and Angular to create a modern Real-time web App Goal:\nTo clear the clouds around creating Modern WebApps Using Djang", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Python\nDjango\nDRF\nAngula", - "Section": "Web development", - "Speaker Info": "Hello I am Jaipreet Singh. I am a developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", - "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Jaipreet Singh (~Jaipreet95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-modern-real-time-apps-with-django-drf-django-channels-and-angular~bo0Bd/", - "title": "Building Modern Real-time Apps with Django, DRF, Django Channels and Angular" - }, - { - "Content URLs": "Github: https://github.com/arijitsaha/FloodRis", - "Description": "Catastrophic floods had a deep impact on the early human psyche resulting in a potpourri of great flood stories ingrained in the mythology of early human civilisations spread across the globe. Despite all the human progress floods can still cause massive property damages, economic losses and casualty. Several major cities and towns in India reported a series of devastating urban floods in recent times, and the resulting human and financial loss makes study of models that can identify the flood risk of an area extremely relevant. This talk focuses on geo-spatial analytics and describes multiple techniques that can be used to assess the flood inundation risk of a geographical area. The techniques use freely available data captured by different satellites. The talk will demonstrate how we can use python libraries and Digital Elevation Models (DEM) to analyse a terrain with respect to it's elevation. The talk also also focus on how to build a first order flood fill model to identify flood inundation risks of a geographical area due to overflow of water from a nearby water body, and due to heavy rains. Some key take-aways from this talk are An introduction to various types of Remote Sensing data with extensive focus on Digital Elevation Models (DEM) Various types of public data sources available for Geospatial Analytics Working with translator library for raster and vector geospatial data like GDAL How to use other geospatial libraries like PyDEM for topographic analysis Descriptive Analytics using Python packages like numpy, pandas, scikit-learn, seaborn, matplotlib etc.", - "Last Updated": "01 Jul, 2018", - "Prerequisites": " Basic / Intermediate knowledge of Python Interest in Geospatial Analytics using Python or curiosity in application of analytics for catastrophic risk management", - "Section": "Data science", - "Speaker Info": "Arijit Saha Arijit Saha is a data professional with over sixteen years of industry work experience in architecting, designing & developing large-scale data products, platforms & solutions for both big & medium size enterprises. Currently he is busy engineering Enterprise AI data platform & products for some of the most well-known global enterprises. He is an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Big Data Analytics, Geospatial Analytics and application of Artificial Intelligence in Enterprises. LinkedIn: https://www.linkedin.com/in/arijitsaha/ Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), Geospatial Analytics, and Reinforcement Learning. LinkedIn: https://www.linkedin.com/in/atulsinghphd", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "arijit.saha", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-flood-risk-in-this-modern-age-an-introduction-to-geospatial-analytics-with-python~avz0a/", - "title": "Managing flood risk in this modern age - An Introduction to Geospatial Analytics with Python" - }, - { - "Description": "As we move towards microservices and distributed architectures it is important to ensure your tooling acts as an effective communication between different teams. This talk is not only about building better applications but improving business delivery through better visibility into your application through the elastic stack. The Basic structure of the talk shall be: Understanding logging and exceptions. What to log and what not to log? Building pipelines to ship logs for your distributed application. Understanding ElastAlert alerting rules. Real-world examples and mechanism of how you can tie in ElastAlert with your IT operations.", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "Some understanding of building business applications for any stack should help", - "Section": "Developer tools and Automation", - "Speaker Info": "Amit Sethi, is a Software Developer at E2E networks. A cloud computing company out of Delhi. His day job involves writing code for distributed applications running using API's and Infrastructures. Some of which he owns and some which he does not. He is passionate about understanding how to deliver a better customer experience of application he writes while ensuring sanity for himself and fellow colleagues", - "Speaker Links": "twitter linkedi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Amit Singh Sethi (~dusual)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/better-visibility-into-your-distributed-application-through-elastalert~axB3d/", - "title": "Better visibility into your distributed application through ElastAlert" - }, - { - "Content URLs": "I will share presentation & relevant code soon to github", - "Description": "How I was able to scale training workloads which gave results in 3 days to experiments in 3 hrs! \nOfcourse it came with a lot of pain, but distributing the model across multiple nodes using a centralised control framework was totally worh it. A simple RESTFul framework for conducting Tensorflow training and evaluation \u2013 \nThis talk will help you: get the best results for any Tensorflow task using a distributed deployment scale your expirments to the next level run on multiple nodes to utilize faster and parallel training/inference systems What the talk will cover: Small intro to DeepLearning with Tensorflow - What it is? Why is it diffirent from other python libraries? Conducting an image segmentation task in Tensorflow How do you make it run on REAL data? ( Train + explore ) x N How to setup the an experiment for the best results in the least time", - "Last Updated": "01 Jul, 2018", - "Prerequisites": " Understanding of python object oriented programming Knowledge of RESTFul APIs Basic understanding of machine learning", - "Section": "Data science", - "Speaker Info": "Kshitij Agrawal I am a strong believer of using technology to solve real problems. With a deep specialization in computer vision, I have developed and deployed a wide array of computer vision applications on hardware as well as cloud. A deep interest in reliable large scale computer vision led me to work at solving challenges around autonomous driving at Intel India. Post my MS from IIIT-Hyd, I was working at Tonbo Imaging, a leader in thermal imaging devices for the military", - "Speaker Links": " LinkedIn Udacity Webinar on Computer Vision", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "kagrwl", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-deep-learning-managing-tensorflow-models-using-simple-resttful-frameworks~dwA1a/", - "title": "The Zen of Deep Learning \u2013 Managing Tensorflow Models using simple RESTtful frameworks" - }, - { - "Content URLs": "Will update shortly", - "Description": "The talk aims to provide an understanding of popular tools at disposal for writing efficient tests using pytest. This intermediate to advanced talk will do a walk through of all components involved in writing production-ready test cases using fixtures, auto-fixtures, factories, faker, mocker etc in a django application. Once the tests look good, they will be integrated with Jenkins (Blue Ocean) where a coverage report of tests will be displayed. Continuous Integration of code on VCS (GitHub) with Jenkins will provide test-runs on every code push to remote repository. This will arm the audience with a robust test suite which is ready to be deployed", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Familiarity with python web-framework (any)", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Aditi Bhatnagar, a senior software developer at a start-up in Bangalore. I have industry experience of 6 years and find myself constantly in need of writing well-tested code. Robust integration tests have often protected me from accidental errors seeping in production", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Aditi Bhatnagar (~aditi95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/testing-with-pytest-and-continuous-integration-with-jenkins~enoWa/", - "title": "Testing with pytest and continuous integration with Jenkins" - }, - { - "Content URLs": "To be updated soo", - "Description": "I wrote a few lines of code to build a web application using Flask back in University. Everyone found it so good, it was like a forest fire. I could never have estimated that a few lines of code can help thousands of people with stuff they do every day. In my case, I designed and developed a website 'Papercop' which did the simple job of downloading all the relevant question papers from the university's portal and all the student had to do was enter their roll number. No Ads. No signups. No logins. One input. One output. And everyone out there loved it. Thousands of students used the site before every examination I'd like to take the audience through the ups and downs of seeing how a simple idea they keep thinking of, can be brought to life using Python while talking about best practices and growth hacks", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "Non", - "Section": "Web development", - "Speaker Info": "I am an IIT Kharagpur graduate(2017) who spent over 4 years coding in Python. Worked with all styles of python from website development using Django and Flask to scientific computing using numpy and scikit-learn to web-scraping using Selenium. It's been a wonderful journey all along and I'm now looking forward to bring as many people on board as I can to experience what I've experienced. I am also the founder of Papercop, an examination preparation portal for the students of IIT Kharagpur which has about 70k+ hits. I am a very passionate speedcuber( Can solve the rubiks cube in about 10s odd). Won plenty of medals in speedcubing competitions across the country. I now work as an analyst with American Express. Speaker at Pycon India '17 and invited to Pycon Italy'1", - "Speaker Links": "Links to previous talks: Pycon India'17 Twitter Linkedi", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anuj Menta (~anujmenta)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/can-a-few-lines-of-python-help-thousands-of-people~azEZe/", - "title": "Can a few lines of Python help thousands of people?" - }, - { - "Description": "All web developers who use python have come across django. It is both hated and loved to varying degrees. But what about day 500. What happens when you have a team of 15 people developing and 5 teams talking to the django application. What kind of baggage does django bring for day 500th. What kind of things it solves for the day 500. Some of the points we shall talk about? What kind questions does the day 500 bring? Admin. Your friend and your foe. Managing your database changes Configuration Management Django in a muti-skill, multi-team environment. Django in a distributed environment. Building visibility in your django app.", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "An understanding of django and web development basics should be helpfu", - "Section": "Web development", - "Speaker Info": "Amit Sethi, is a Software Developer at E2E networks. He has had his own love-hate relationship with django. Apart from that he has worked with frameworks like pyramid, tornado and flask with python. And also used rails and beego with ruby and golang. He is an opinionated developer with love for elegant API'", - "Speaker Links": "twitter linkedi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Amit Singh Sethi (~dusual)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-on-day-500~dyDEb/", - "title": "Django on day 500" - }, - { - "Content URLs": "To be updated soon", - "Description": "We have always been taught that the earlier you book a flight, the cheaper it is. What if I said it isn't? You see it's not a straight line and it has a minimum at some point(someday before the flight). We are going to see how historical Airfare data can help us derive the best day to book a flight so that you 'actually' get the cheapest fares. The talk would talk about the entire process, from getting the data, to training a basic Neural network on the data. With advancements in deep learning in these few years, it is very easy to train a simple statistical model to predict the prices. Also, my thesis at IIT Kharagpur was titled 'Forecasting of Airfare prices using Neural networks' and the talk is based on that along with a few improvements I made on top of that", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "A brief understanding of neural networks or any machine learning model in general could help you make the most out of your talk", - "Section": "Data science", - "Speaker Info": "I am an IIT Kharagpur graduate(2017) who spent over 4 years coding in Python. Worked with all styles of python from website development using Django and Flask to scientific computing using numpy and scikit-learn to web-scraping using Selenium. It's been a wonderful journey all along and I'm now looking forward to bring as many people on board as I can to experience what I've experienced. I am also the founder of Papercop, an examination preparation portal for the students of IIT Kharagpur which has about 70k+ hits. I am a very passionate speedcuber( Can solve the rubiks cube in about 10s odd). Won plenty of medals in speedcubing competitions across the country. I now work as an analyst with American Express. Speaker at Pycon India '17 and invited to Pycon Italy'1", - "Speaker Links": "Links to previous talks: Pycon India'17 Twitter Linkedi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anuj Menta (~anujmenta)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/forecasting-and-observing-airfare-trends-using-python-and-neural-networks~aA23b/", - "title": "Forecasting and observing Airfare trends using Python and Neural Networks" - }, - { - "Content URLs": "https://github.com/audreyr/cookiecutte", - "Description": "When starting with a new python project/django web app, starting with initial project structure may not be that easy. Thinking about best practices that you have seen some other popular opensource projects and doing it over and over is very tiring.. what if we can just create a project with very little effort and share your set of tools that used in project to other team members? This talk is mainly about cookiecutter, it is a cli utility that creates projects from templates. We will see how to use existing cookiecutter template and finally create a template that works well for you and your team and share that template", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "Knowledge regarding basic python and may be jinja templating", - "Section": "Developer tools and Automation", - "Speaker Info": "Working as developer at Pramati technologies..Working with python from past 3 years, loves programming and automation", - "Speaker Links": "github - https://github.com/code-R\nlinkedin - https://www.linkedin.com/in/vamsi-krishna-29690614", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/scaffolding-made-easy-with-cookies-cookiecutter~dB2kd/", - "title": "Scaffolding made easy with cookies (Cookiecutter)" - }, - { - "Content URLs": "https://www.slideshare.net/veerskyfire/cyber-disorde", - "Description": "How social media is affecting our real life, what would be the prevention we can take to protect our digital identity and will share many real life case studies of cyber-crime with whom people will relate easily to better understand the scenario of cyber disorder and how to prevent such data leakage", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisites", - "Section": "Others", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog\nhttps://www.viralparmarhacker.com Linkdin\nhttps://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter \nhttps://twitter.com/viralparmarhack Github \nhttps://github.com/Veerskyfire", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cyber-disorder~bD2ye/", - "title": "Cyber Disorder" - }, - { - "Content URLs": "For Reference: https://github.com/Veerskyfire/auth0-pytho", - "Description": "This is introductory talk about the Authentication, where I will discuss about the role that Auth0 authentication plays in modern software development where it is a lot more than just the login screen. You will be able to learn about the different concept of authentication with python and In this talk the audience will learned about the different concepts that make up modern identity important for us to be secure, it will also enable people from the different peers technical as well as non-technical enthusiast to take opportunities to rethink of Authentication process of applications", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Networking and Security", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog\nhttps://www.viralparmarhacker.com LinkedIn\nhttps://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter \nhttps://twitter.com/viralparmarhack GitHub \nhttps://github.com/Veerskyfire/ Facebook \nhttps://www.facebook.com/viralparmarhacke", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/authentication-with-auth0~eE2Ya/", - "title": "Authentication with Auth0" - }, - { - "Content URLs": "https://www.slideshare.net/veerskyfire", - "Description": "Topic is about how AI and ML are building dystopia for us. The big companies like Google, Facebook, Amazon who are in business of capturing-selling data & our attention to advertisers, gathering our data, harvesting it and use against us to manipulate us & control us. How Social media Ads influence us using its persuasion architecture. Will explain how AI prediction is a threat to our freedom with Case study of smart health care", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Others", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog https://www.viralparmarhacker.com LinkedIn https://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter https://twitter.com/viralparmarhack GitHub https://github.com/Veerskyfire/ Facebook https://www.facebook.com/viralparmarhacke", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/we-are-building-dystopia-using-ai-ml~dJ2Jd/", - "title": "We are building dystopia using AI & ML" - }, - { - "Content URLs": "https://www.slideshare.net/veerskyfire/who-is-spying-on-yo", - "Description": "Topics is about how our privacy is compromised every day, how it happens due to mass surveillance by governments, big tech company, data brokers & 3rd party apps etc., what are our rights to privacy & why it matters, what are the precaution we can take to secure it, secure communication channels like TOR and also will discuss about Broadband Policy, Net Neutrality & Cyber Warfare", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Others", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog https://www.viralparmarhacker.com LinkedIn https://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter https://twitter.com/viralparmarhack GitHub https://github.com/Veerskyfire/ Facebook https://www.facebook.com/viralparmarhacke", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/who-is-spying-on-us~dG2Lb/", - "title": "Who is Spying on us ?" - }, - { - "Description": "Introduction to creating RESTful APIs in Python using django framework. This workshop is for everyone who develops web application backends or mobile app backends. Content which will be covered in workshop are as follows: HTTP methods Django Models Request & Response Status Codes Serializers Nested Serializers DRF classy views Hyperlinked APIs Permissions Authentication Authorization Viewsets and Routers In this workshop, we will be building Medium Clone from scratch by creating RESTful APIs", - "Last Updated": "02 Jul, 2018", - "Prerequisites": " Familiarity to *nix operating system. Basic python 3 & OOP concepts. Knowledge about HTTP and web development is plus.", - "Section": "Web development", - "Speaker Info": "Piyush Maurya: Piyush is currently working at Infosys, Mysuru & active volunteer @bangpypers . He has 2.5 years of experience in Python/Django, which includes building college event portal to large scale enterprise. He lives in Mysuru and can be found at every BangPypers Meetup. Nowadays, he is experimenting with Flutter SDK and uses django-rest-framework to build APIs for mobile apps. Karan Shah: Karan is currently working at Infosys, Mysuru. Right now he is exploring Flutter SDK and trying to develop a cross platform app", - "Speaker Links": "Github: https://github.com/piyushmaurya23 Twitter: https://twitter.com/piyushmaurya23 Linkedin: https://www.linkedin.com/in/piyushmaurya23", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Piyush Maurya (~piyushmaurya23)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/restful-apis-in-python-django-rest-framework-101~aM2Ob/", - "title": "RESTful APIs in Python: Django Rest Framework 101" - }, - { - "Content URLs": "https://pytest.org", - "Description": "Nowadays everyone follows agile and care about code quality and testing their code, which gives them the confidence to maintain their application. Do people take shortcuts while writing unit tests? what are the common things to look out for while writing unit tests and good patterns to follow? This talk would be focused on those set of people who already know about unit testing in Python but they often feel the need of knowing the unit test best practices or they question themselves whether they are doing it the right way or not. Writing unit tests for your code is fairly simple but if you don't write them in the correct way or not following some of the best practices then it becomes a nightmare in the long run. Some of the things that will be covered during the talk are, why your unit test suite should be faster, effective usage of mock/stub. During my talk, I'd not only be emphasizing on writing good quality unit tests and would also hope to motivate the audience to follow these practices by showing them some practical use cases. For this, I'll be illustrating real code examples of such scenarios, best practices, and principles during the talk. How do tests help maintain good documentation? Why people suggest following TDD and how tests help to improve the design of your code and maintain for the long run", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "People should be familiar with writing unit tests using any test framework", - "Section": "Developer tools and Automation", - "Speaker Info": "Working as developer at Pramati technologies..Working with python from past 3 years, loves programming and automation", - "Speaker Links": "github - https://github.com/code-R \nlinkedin - https://www.linkedin.com/in/vamsi-krishna-29690614", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unit-testing-best-practices-some-common-pitfalls~dL2Xa/", - "title": "Unit Testing best practices & some common pitfalls" - }, - { - "Content URLs": "N.A", - "Description": "When I started using Python for scientific computing, it was simply a tool that helped me get the results I needed. It was a simple tool with a large and helpful community. Most of my code was simply an working amalgam of solutions found on Stack Overflow. I didn't take the time to learn about the fundamentals of the language, the tools that the language provided and the best practices. Only after I started working professionally did I take the time out to learn Python at a more basic level. As professional software developers, I think our job is to not just write code that works but to write code that uses the best practices. It's our duty to keep ourselves up to date about the advancements in the language and understand the language and the ecosystem at a more fundamental level. Towards this end, I will talk about a few language fundamentals such as attribute access on classes, decorators and closures in Python. I will talk about best practices such as using list comprehensions instead of explicit for loops. I will introduce a number of packages in the standard library that help write better Python code such as argparse and Path. Finally, I will introduces resources that helped me better understand the language and the ecosystem such as online documentation, books and talks by experts", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No prerequisites are expected from the audience. This talk will be accessible to developers with all levels of experience", - "Section": "Core python and Standard library", - "Speaker Info": "I'm a Scientific Software Developer. I've been using Python professionally for just over two years. I was using Python for almost 3 years before that for scientific computing. I have a B.S. & M.S. in Physics from IIT Madras.\nI've given a number of talks in the Pune and Chennai Python meetups. I've also conducted workshops at SciPy India, PyCon India and a few other locations", - "Speaker Links": "More information about me and my work can be found at - http://rahulporuri.github.io/\nI occasionally blog at https://rahulporuri.blogspot.com/\nI'm @rahulporuri on twitter and you can reach out to me personally at rahul.poruri@gmail.com ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "rahul .poruri (~rahul66)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/growing-as-a-python-developer~aK2Me/", - "title": "Growing as a Python Developer" - }, - { - "Content URLs": "if possible download Firefox: https://www.mozilla.org/en-US/firefox/new/ on your computer and/or phone", - "Description": "We as programmers often do not give a lot of thought/importance to our online privacy while using the web. This session/talk will be useful for programmers to guard their online privacy. Consider a programmer using google search engine to search for errors or using stack overflow to find answers to fix a broken python dependency. All of it is stored and profiled against the online identity of the programmer. This data can then be used to sell ads which as we all feel are annoying.\nThis session/talk will help everyone (who uses the web) learn the best practices of anti-tracking, ads blocking, anti-profiling clean browsing environments. We as programmers might be using the same browser for professional and personal work/browsing causing mix-match of data and annoying ads popping up during work sessions. \nThis session/talk will help such programmers keep it all separate via firefox profiles, just like clean python virtual environments :) What will happen during the session? Introduction to Firefox and Icebreaker - 3 mins Customize Firefox, Profiles, and Preferences - 10 mins How you can change Firefox configs to have a more customized and private experience - 10 mins How to block trackers on the web - 10 mins Best Privacy extensions - 5 mins Use of privacy respecting search engines - 5 mins QA - 7 mins This session/talk is for anyone and everyone who uses the web", - "Last Updated": "03 Jul, 2018", - "Prerequisites": " A couple of screens/monitors or a projector at the session will help participants hack, make, learn and share with other participants. Sticky notes Sharpies Optional firefox installed on computers or phones of participants. Open mind", - "Section": "Others", - "Speaker Info": "Ankit Gadgil is an open source and open web advocate who believes the web should be equally accessible to all for equal opportunity. He strongly supports data privacy. Ankit works for Red Hat as a senior software engineer and enjoys working with python, Js, algorithms, and architecture.\nHe usually contributes to open source projects like Mozilla, MediaWiki, Wordpress. He has also served as a member of the Mozilla Reps Council", - "Speaker Links": "Info: https://reps.mozilla.org/u/ankitgadgil/ Twitter: @anknit", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ankit Gadgil (~anknite)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-firefox-like-a-boss-privacy-settings~aORYe/", - "title": "Using Firefox like a Boss - Privacy Settings" - }, - { - "Content URLs": "Content will be updated soon", - "Description": "Note:- This talk will be co-presented by Me and Saurabh Ghanekar. Talk Summary:- For a long time we have faced many problems in transferring a file from one place to another without the use of a central server. But with the use of peer to peer, BitTorrent protocol, it is relatively easy for us to share our data. But there is a problem in here. It is not fully decentralized. There are still centralized servers that host these files. Moreover we at our college find it quite difficult to share our study material over LAN as nobody hosts their study materials (duh!!!). So we decided to create a decentralized file sharing application that enables us to share our file to all our friends even if we didn\u2019t hosted it on a server. In this talk we will be explaining the basics of decentralization. We will expand on what and how this could be used to make a file sharing application. We will also shed some light on how to make a fairly secure file sharing application based on the topics we will be covering at the beginning of our talk. Once we are through with the theory and our code, we would be presenting our proof of concept i.e. a small demo of the application. Outcome of the Talk:- After this talk you would expect to learn the basics of decentralized network, how to make a secure decentralized application and successfully learn how to make a decentralized file sharing system. Agenda:- Brief Introduction of Decentralization. [6 min] Basics of File Transfer over a Network. [4 min] What a fairly secure File Sharing Network mean? [5 min] Making and Implementation of making a Decentralized File Sharing Network. [10 min] Making and Implementation of making a Decentralized File Sharing Network. [10 min] A small Live Demo. [3 min] Q and A. [2 min]", - "Last Updated": "03 Jul, 2018", - "Prerequisites": "Love for Pytho", - "Section": "Networking and Security", - "Speaker Info": "This talk is co-presented by Me and Saurabh Ghanekar. Shubham Rao Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData . Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", - "Speaker Links": "Shubham Rao Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitHub E-mail me at : cshubhamrao [at] gmail [dot] com Saurabh Ghanekar Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Shubham Rao (~shubham66)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-cool-way-to-share-files-in-this-21st-century~dNRDd/", - "title": "A Cool Way to Share Files in this 21st Century" - }, - { - "Content URLs": "Coming soon", - "Description": "Abstract Tox is a generic virtualenv management and test command line tool you can use for: checking your package installs correctly with different Python versions and interpreters running your tests in each of the environments, configuring your test tool of choice acting as a frontend to Continuous Integration servers, greatly reducing boilerplate and merging CI and shell-based testing. Description In this talk we will see what is tox and how we can use it to test our application using different python versions or different Django versions etc., we will see how tox help us in reducing the boilerplate code when integrating with jenkins/travis Outline Introduction to tox (3 min) Diving into tox (how tox works) (5 min) Writing a basic tox configuration - tox.ini (3 min) See how OpenStack leverages tox with Jenkins (4 mins) Some use cases with tox ex: bandit, pep8 (3 mins) Demo (5 mins)", - "Last Updated": "03 Jul, 2018", - "Prerequisites": "Basic understanding or virtual environments and unit testing using python", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tox-python-testing-wrapper~dP81d/", - "title": "Tox - Python testing wrapper" - }, - { - "Content URLs": "https://tutorial.djangogirls.org/en", - "Description": "Django Girls is a non-profit organization and a community that empowers and helps women to organize free, one-day programming workshops by providing tools, resources and support.\nYou'll work through a tutorial in small groups with a coach, so you'll be able to learn at your own pace. Every coach will guide their group of attendee and teach them Django. There will be general 2-3 meta coaches to help these coaches. \nDuring Django workshop you will create your website in Django ", - "Last Updated": "03 Jul, 2018", - "Prerequisites": "Basic knowledge of Python will be sufficient", - "Section": "Web development", - "Speaker Info": "As per workshop structure, there is no one speaker. There will be group of coaches, metal coaches, volunteers and organizers. I am final year student of Bachelor of Engineering in Computer. I have organized Django Girls workshop before at our city and it was amazing experience to see 45+ women get inspired and learned. I love contributing to open-source and got my first internship Zulip-Winter-of-Code at Zulip. Also got selected for GSoC-2018-with-Zulip and interned at IIT-Bombay", - "Speaker Links": "Portfolio GitHub Linkedin Django Girls Bhavnaga", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Dave Yashashvi (~dave)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-girls-start-your-journey-with-programming~aQR0b/", - "title": "Django Girls - start your journey with programming" - }, - { - "Description": " With the rise of MEAN(MongoDB Express AngularJS NodeJS) stack framework with Python for secure server-side scripting. A simple introduction to using Python Capabilities for Server Management. Using NumPy and SciPy libraries in Javascript.", - "Last Updated": "04 Jul, 2018", - "Prerequisites": "Core Python. Javascript", - "Section": "Core python and Standard library", - "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", - "Speaker Links": "GitHub Instagram Emai", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aniket Chowdhury (~aniket43)", - "created_on": "04 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/integrating-python-with-nodejs~eV9vd/", - "title": "Integrating Python with NodeJS" - }, - { - "Content URLs": "To be updated soon !", - "Description": "90% of data in the internet today is either image or video.The exponential rise of visual data has continuously urged researchers to develop robust and efficient Object detection algorithms,but CNN or R-CNN or YOLO or SSD which algorithm can give best results.In this talk I will try to cover salient features in some of the most influential works in this problem statement.The talk begins with intro to CNNs and goes into detailed discussion of state-of-the-art deep learning algorithms used for object detection. Structure of the talk - The talk is structured into 3 sections :\nIn the first 20 minutes we will have a talk on the architectures, then 10 minutes will be dedicated for some hands-on demo to build a CNN using Keras/Pytorch and the rest of the time will be for QnA. Contents - The talk will begin with a discussion on Convolution Neural Networks and various terms associated like Convolution,pooling,activation used etc and there after discussing about the various state-of-the-art algorithms like R-CNN,Fast R-CNN,Faster R-CNN,R-FCN,YOLO and SSD.One of my analysis criteria will be on their speed at inference allowing real-time analysis. Take aways : What is a CNN,what are convolution,pooling etc. What are R-CNN,Fast R-CNN,Faster R-CNN,R-FCN,YOLO and SSD How to implement a CNN using keras/Pytorch.", - "Last Updated": "03 Jul, 2018", - "Prerequisites": " Basic python or any other language programming. Basic knowledge of Machine Learning and Neural Networks. Most importantly an interest to learn a new concept.", - "Section": "Data science", - "Speaker Info": "The speaker is a 4th year undergraduate student from the department of Computer Science and Engineering at IIIT Bhubaneswar. He is a Data science, Machine Learning and Deep learning enthusiast.He has an experience of over 2 years in this field and has worked on Machine Learning and Deep Learning and it's application to Computer Vision(CV) and Natural Language Processing(NLP). He has worked on few self projects and been a part of 2 research Internships, One at IIIT Bangalore and another at IIT Kharagpur . He has experience of working with various libraries like sci-kit ,Tensorflow ,Keras ,Torch and Pytorch", - "Speaker Links": "Get in touch with me through LinkedIn Also reach me on Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "saiamrit", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-detection-demistified-state-of-art-deepnets~dR7Oe/", - "title": "Object Detection Demistified-State of art DeepNets" - }, - { - "Description": "Short description. Unit testing and continuous integration are core part of any software development team, in this talk you will understand how py.test and pytest-bdd (behaviour driven testing) helps us accelerate this process. Things you'll learn pytest basics, gherkin basics for pytest-bdd pytest Intermediate concepts - fixtures, parametrizing test cases pytest-bdd intermediate concepts - step definition, reusing pytest fixtures Jenkins integration for pytest", - "Last Updated": "05 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm the head of technology at TenderCuts and Envee. We are an omni-channel meat delivery startup. At our company we make heavy use of python from our ERP to our mobile app", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "varunxyz", - "created_on": "05 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/super-charging-python-testing-with-pytest-and-pytest-bdd-jenkins-integration~eXR5b/", - "title": "Super charging python testing with pytest and pytest-bdd + Jenkins Integration" - }, - { - "Content URLs": "http://prezi.com/89s2vr6bmar0/?utm_campaign=share&utm_medium=cop", - "Description": "I will be discussing how the use of Python in Africa has grown significantly since 2010 and how, as a result new innovation centers like the High Performance Center in Zimbabwe are beginning to build an industry using it", - "Last Updated": "04 Jul, 2018", - "Prerequisites": "no perquisites require", - "Section": "Others", - "Speaker Info": "Marlene Mhangami is the first African to have been voted onto the board of directors of the Python Software Foundation, the group organization behind the popular computer programming language Python. She is the Chair of PyCon Africa and heads up the Google's Women Techmakers Harare. \nMarlene is also the co-founder of ZimboPy an organization getting Zimbabwean girls excited about code. The organization has been working with girls around Harare to teach them Python programming and is excited about their progress. They also frequently host mentorship weeks and learning programs with local Universities including HIT, the UZ and CUT. Finally, Marlene is also the co-founder of the Purple Lipstick Trust a Zimbabwean non-profit organization that empowers young women to achieve their goals. The organization creates social media content and events that help girls make the best decisions about their lives.\nShe is excited about seeing technology and science used for social good. Marlene is interested in advocating for, and seeing software developer communities grow to create the best environments for innovation to happen! Minority representation in tech spaces is also something she is passionate about and hopes to be part of increasing", - "Speaker Links": "www.linkedin.com/in/marlene-mhangami-90a740130\ntwitter: @marlene_zw or @zimbop", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marlene Mhangami (~marlene)", - "created_on": "04 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-growth-of-the-python-community-in-africa-and-how-zimbabwe-is-building-one-of-the-biggest-artificial-intelligence-labs-in-the-world~bWRQa/", - "title": "The Growth of the Python Community in Africa and How Zimbabwe is Building One of the Biggest Artificial Intelligence Labs in the World" - }, - { - "Description": "Django has swiftly made its way to the top of the web application stack and it is becoming extremely popular among the developers whether freshers or veterans due to its robust framework and inbuilt security features. However, a lot of the developers take this security for granted while developing a web application or an API and therefore often end up with some loopholes that can be exploited by the attackers directly impacting the consumer\u2019s data and the website's reputation. This workshop is intended to talk about those common and uncommon flaws giving special focus to the Owasp Top 10 standards of web application security, use cases where developers might fail to implement them and secure coding practices wrt the same. We will be presenting a live demo on intentionally made vulnerable Django applications with real-life use cases. We will understand how hackers may exploit them, common mistakes developers might make which can lead to a specific vulnerability and how to patch them/build them securely along with secure coding best practices. The demo application will be open source for the audience to try live during the workshop and after it too", - "Last Updated": "05 Jul, 2018", - "Prerequisites": " Beginner level Django and Python knowledge Interest in understanding common attack methodologies and developing secure web applications.", - "Section": "Web development", - "Speaker Info": "Soumya Singh Soumya Singh is a programmer at heart and she has 2+ years of experience in professional Django development and over 3 years experience with Android application development. She is currently working at BugsBounty.com - A crowd-sourced security platform for ethical hackers and organisations where she heads a team to build various security-related products. Besides this, she is LCCSA certified Ethical Hacker and takes cyber security rather seriously", - "Speaker Links": "LinkedIn Profil", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Soumya Singh (~soumya96)", - "created_on": "05 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/owasp-top-10-web-security-loopholes-vs-django-which-is-allegedly-secure-no-matter-who-is-coding-with-it~eZRwe/", - "title": "OWASP Top 10 Web Security Loopholes v/s Django - Which is \u201callegedly\u201d secure no matter who is coding with it." - }, - { - "Description": "A face animation software which will be very useful in the media and entertainment industry. Here, by just showing your face you can create an avatar", - "Last Updated": "05 Jul, 2018", - "Prerequisites": "Should know basics of Pytho", - "Section": "Core python and Standard library", - "Speaker Info": "A final year BCA student who is very enthusiastic about artificial intelligenc", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Swarnali Singha (~swarnali)", - "created_on": "05 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/face-avatar-using-artificial-intelligence~bYRMd/", - "title": "Face Avatar using Artificial Intelligence" - }, - { - "Content URLs": "Details of this talk can be found on my website. This talk was previously given at EuroPython 2017 slides on speakerdeck video of this talk being given at EuroPython 201", - "Description": "Command execution time can become important in a number of applications. Commands executed in command-line completion need to execute in less then 100ms or users will perceive a delay. In Shell scripting one might want to execute commands repeatedly in a for loop and fast execution times makes this more feasible. Python is a very powerful language but has a much slower startup time compared to other interpreted languages like Perl, Lua and Bash. It can take up to 10 times longer to startup then some of these other languages. MicroPython was written as a lean implementation of Python 3 with a small subset of the standard library mainly intended to run on microcontrollers. But it happily runs on Unix systems with excellent startup performance, making it an ideal candidate for implementing certain time sensitive commands. This talk will: Explain when achieving fast execution times matters and when it doesn\u2019t. Present two different approaches to measuring command execution time, one simple and the other more detailed and accurate. Compare execution times of a simple set of scripts that add two numbers in an number of different interpreted languages (micropython, python3, awk, perl, lua, bash). Present an example use case of MicroPython on Unix. Bash completion for pip install that completes the names of available packages live from a remote pypi mirror. Demonstrate the auto completion script with pip on a local pypi mirror. ", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "Basic understanding of running python scripts on the command line", - "Section": "Embedded python", - "Speaker Info": "I'm a passionate Python developer living on the sunny island of Bahrain. I've been a speaker at Python conferences before and ran the Bahrain Linux User Group for five years. During that period I was a regular speaker at the groups monthly meetups. I\u2019ve taught courses in python programing and computer networking to both students and working professionals", - "Speaker Links": "I've given talks at two python conferences before: EuroPython 2017: Executing scripts in a few milliseconds with MicroPython PyLondinium 2018: Snow globe intruder alert syste", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Marwan Al-Sabbagh (~marwan)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/executing-scripts-in-a-few-milliseconds-with-micropython~e1DVd/", - "title": "Executing scripts in a few milliseconds with MicroPython" - }, - { - "Content URLs": "Details of this talk can be found on my website. This talk was previously given at PyLondinium 2018 slides on speakerdec", - "Description": "Learn how to build a snow globe that sounds an alarm and flashes a red alert when intruders are about. Me and my six year old daughter designed and built this project to have fun with friends and learn a bit about computers along the way. Adafruit\u2019s Circuit Playground Express is a fantastic $25 computer packed with sensors, buttons, LEDs and a little speaker. Add this DIY Snow Globe Kit and some Conductive Thread and we have the makings of an ingenious Snow globe intruder alert system. All written in python using a simple text editor without the need for any special software, drivers or soldering. The globe has a rainbow mode that randomly fades different colors in and out and an alarm mode to detect intruders. Modes can be switched by giving the globe a tap which it detects with it\u2019s motion sensors. Once in alarm mode the globe will flash green until an intruder steps on the conductive thread which will sound the alarm and flash the globe red. The Circuit Playground was used to teach my six year old daughter the differences between computer inputs and outputs and how to issue commands to computers using the Python REPL. She learned about the different frequencies of sound waves by calling the beep function with different frequencies. This opened up the topic of the hearing range of humans compared to other animals like dogs. She then learned to set the color of each of the ten NeoPixel LEDs into a rainbow pattern by calling the light function multiple times with each color and position. We explored how any color can be displayed as a combination of red, green and blue by using a digital microscope to see these three LEDs change with different colors. This talk will cover: Tour of the Circuit Playground Express Assembling the snow globe The rainbow and alarm code REPL sound and light with a six year old Troubleshooting tips", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "Basic exposure to python", - "Section": "Embedded python", - "Speaker Info": "I'm a passionate Python developer living on the sunny island of Bahrain. I've been a speaker at Python conferences before and ran the Bahrain Linux User Group for five years. During that period I was a regular speaker at the groups monthly meetups. I\u2019ve taught courses in python programing and computer networking to both students and working professionals", - "Speaker Links": "I've given talks at two python conferences before: EuroPython 2017: Executing scripts in a few milliseconds with MicroPython PyLondinium 2018: Snow globe intruder alert syste", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marwan Al-Sabbagh (~marwan)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/snow-globe-intruder-alert-system~b2E1a/", - "title": "Snow globe intruder alert system" - }, - { - "Description": "The hardest part of building a text classifier is finding labelled data to train the model. The next hardest part is making sure that data is fair and representative. In this talk we will discuss some approaches to rapidly generating corpora suitable for supervised training from public data and with open-source tools. This talk will include some practical tips as well as some less-obvious pitfalls, and is suitable for both novices and more experienced Natural Language Processing Practitioners. At the end of the talk you will be able to give a convincing answer to the eternal question: How do I build a text classifier for a product that doesn't exist yet? Co-presented with Alex O'Conno", - "Last Updated": "06 Jul, 2018", - "Section": "Data science", - "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. He is currently employed as a Machine Learning Engineer with Pivotus where he works on problems in the Natural Language Processing space. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", - "Speaker Links": " My talk at PyCon APAC 2018 An attendee's review of my talk", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Alizishaan Khatri (~alizishaan)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/something-for-nothing-boostrapping-text-classification~e3GOe/", - "title": "Something for Nothing: Boostrapping Text Classification" - }, - { - "Description": "At Sumo logic which is entirely cloud-based, one component of it resides out of the cloud and rests in the hands of users, in their own infrastructure. This component is sumo's installed collector. This is an installable package for which various forms of binaries get generated in form of rpm, deb, tar, sh, exe and docker images. These packages, along with a plethora of functionalities of the installed collector, need a test bed which not only gives the user freedom to select which tests to run but also which kind of OS the packages might be installed at. We have created a testbed which is multi-platform and runs on the back of AWS cloud infra. The automation testbed has been designed such that we get to write code in a platform agnostic manner, hence the same set of tests can be run in Windows, Debian or RHEL systems. The testbed helps us with managing various versions of installed collectors and help us with verifying our upgrades and various flows across them. We use Ansible for our box setups, of various Linux and windows types, and pytest to write various test scenarios, these tests verify various functionalities of collector along with the installer themselves. Using pytest we can leverage huge armada of python libraries available such as ansible libraries, fabric, sumo's own search, metrics libraries. This kind of test-bed has uniquely brought down our 2 weeks of tests cycles to now less than 3 days and gives us immense confidence in delivering projects at a much rapid pace", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "A beginner's knowledge of ansible and pytest is all people will need to know of", - "Section": "Developer tools and Automation", - "Speaker Info": "Vivek Gupta , Lead QE - platform, Sumologic Vivek has been working with python through most of his career with experience of 7 years in companies like Adobe and Quad Analytix previous to Sumologic. Responsible for Sumologic's entire platform testing, his team works on a wide scope of challenges related to their installers, hosted collectors and their core services. Gourav Garg , QE - platform, Sumologic Gourav has an experience of 1 year and was hired straight out of college. He is responsible for the collection team QE activities along with quite a few QE Jenkins activities at Sumo. He takes care of the entire range of installed collectors as well as hosted collectors", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "vivek gupta (~vivek73)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/multiplatform-automation-test-bed-using-ansible-and-pytest~b4JVe/", - "title": "Multiplatform automation test bed using ansible and pytest" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of Github Repository", - "Description": "Named Entity Recognition is the task of extracting named entities like Person, Place etc from the text. It is an important step in extracting information from unstructured text data.\n I will explore various approaches for entity extraction using both existing libraries and also implementing state of the art approaches from scratch Agenda for the Talk: Introducing Named Entity Recognition Standard Named Entity using NLTK and Spacy Training Custom Entity Tagger using Spacy or Rasa Standard Algorithms for NER Conditional Random Field (CRF) Deep Learning for NER using LSTM in Keras Structured Deep Learning for NER using LSTM-CRF End-to-End NER via Bi-directional LSTM-CNN-CRF", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "A Basic Knowledge of Python, Machine Learning and Natural Language Processing", - "Section": "Data science", - "Speaker Info": "Subramanya T A is Senior Data Scientist at Sentienz. He heads the Data Science team at Sentienz", - "Speaker Links": "LinkedIn Profile: \n https://www.linkedin.com/in/subramanya-t-a-7306a729/ Sentienz Website:\n http://www.sentienz.com", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "T. A. Subramanya Paddillaya (~t._a._subramanya)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/named-entity-recognition-in-python~e5gKb/", - "title": "Named Entity Recognition in Python" - }, - { - "Description": "How many times have you banged your head on the wall while using Javascript to build a page showcasing your shiny new Python project? Wouldn't it be great if your blog readers could run and play with the code right away? Fancy running Jupyter-like notebooks entirely in the browser without any server? This talk will get you a headstart into running Python directly in the browser. Agenda Introduction (2 mins) About me Why the Browser is an important stack to target? Three major approaches (20 mins) We will be peeking at the official demo and docs for these projects and dig deeper on how they work. Brief details below : Transpilation - Python code is converted to Javascript before the page is loaded. Examples include PyScript and Transcrypt Python implementation in Javascript - Python code conversion to JS takes place in the browser itself Examples include Brython , Skulpt and Batavia Brython converts Python code into JS in the browser with access to the DOM elements and events The way Batavia works is marvelous! It takes the bytecode for the Python program generated and interprets the Python bytecode as a running program in the browser realtime using a Javascript implementation of the Python VM. Web Assembly - Converting full implementations of Python to run on the web Examples include PyPyJS and Pyodide PyPyJS as the name suggests is the entire PyPy implementation compiled to Javascript. It is PyPy compiled for the web via emscripten, with a custom JIT backend that emits asm.js code at runtime. Pyodide takes this to a different level. It takes the entire Python scientific stack and compiles it to run on the browser using Web Assembly. That means every data library you love - numpy, pandas, matplotlib will run directly on the browser - no installation needed! Conclusion (5 mins) Learnings about Python internals This area is still in its infancy - what to look forward to?", - "Last Updated": "07 Jul, 2018", - "Prerequisites": "General overview of how Python works under the hood - What happens when you run a Python file using CPython, what Python bytecode is etc", - "Section": "Core python and Standard library", - "Speaker Info": "Currently working as a Freelance Python Developer based in Kochi. Originally did Bachelors in Mechanical Engineering from CUSAT.\nI have completed consulting projects in ML and AI with multiple startups and companies. My work on CNNs was the winning solution for IBM\u2019s Cognitive Cup challenge in 2016 and gave a talk on the same at the Super Computing conference SC16 at Salt Lake City, Utah : Slides Previously I was a Technology Innovation Fellow with Kerala Startup Mission where I started a non-profit student community TinkerHub, that has a focus on creating community spaces across colleges for learning the latest technologies. I've been dabbling around with browser technologies since my college days since 2011 being a Mozilla volunteer which got me interested in finding ways to run Python in the browser", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/praveensridhar/ Previous talks : Anthill Inside talk on Explainability in AI SpeakerDeck", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Praveen Sridhar (~psbots)", - "created_on": "07 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-in-the-browser-run-run-run~b6jVb/", - "title": "Python in the Browser - Run! Run! Run!" - }, - { - "Content URLs": "Find me on Quora My WordPress blog My LinkedI", - "Description": "Computers can tell us whether we\u2019re happy, sad, angry or any of the several emotions we feel. Computers can understand what we\u2019re saying and answer back. How does all this magic happen?\nThis concept of teaching a program to analyze speech and understand it is called speech recognition. I\u2019ll talk about speech recognition and its various nuances, and how it is handled using Python. I\u2019ll also talk about various branches of speech recognition such as speech emotion recognition and text generation based on speech data, and speech recognition implementations on hardware as well. Here is a basic summary of what all I will cover: Speech recognition: what is it, why is it required - concepts like spectral analysis, MFCCs (Mel Frequency Cepstral Coefficients), Fourier transforms, signal processing etc. How Python can make speech recognition easier Branches and new areas of speech recognition: speech emotion recognition, sentiment analysis etc., work done in these fields in the past few decades How speech recognition models are built: acoustic and language models etc. Resources like blogs, libraries, toolkits etc. for studying and getting started with speech recognition models in Python Basic workflow and tips on how to create your first speech recognition model using Python A brief on various repositories of speech databases, how they can be accessed and prepared for input to speech models Speech recognition models implemented on FPGA (hardware), some seminal (and thoroughly comprehensive) research papers to read on the latest work in the field Other media such as video data and face emotion recognition, resources for studying them up further Applications and future scope, closing remarks I will cover the basics of how speech is read, processed and quantified, concepts like the Fourier Transform and spectral analysis, the various Python libraries and resources that exist for the same, and how one can build their own speech recognition system easily. Perhaps an Alexa 2.0", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "Basic knowledge of Python and data science should suffice", - "Section": "Data science", - "Speaker Info": "I am a third year undergrad at Delhi Technological University. I am passionately fond of data science and machine learning, and have worked on several projects and authored research papers on the same. My research area particularly centers around ensemble learning and methods, and I've started taking an interest in speech recognition systems in recent months. I have worked with professors across several universities, and am always up for discussing Python, machine learning and data science with anyone", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anjalib123", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speech-recognition-using-python-how-a-computer-can-tell-if-youre-angry~e7kye/", - "title": "Speech recognition using Python: how a computer can tell if you're angry" - }, - { - "Description": "Is there a better time to be a developer! Thanks to Cloud Computing, deploying applications is much more comfortable than it used to be. Serverless computing is an abstraction layer in the cloud. It does not mean that there are no servers, but instead, underlying infrastructure (VM, storage, containers, etc.), as well as the operating system, is abstracted away from the developer. Applications are run in compute containers that are event triggered. Developers have to create functions and depend on the infrastructure to allocate the proper resources to execute the task. Manage the load by creating copies of the functions and scale to meet the demand. OpenFaaS (Functions as a Service) is a framework for building serverless functions with Docker Swarm or Kubernetes which has fantastic support for metrics. We can package/deploy any simple API / service as a function. At a high level in this session: We will discuss and implement a live python function via template and deploy this python functions to Docker Swarm & Kubernetes. We will design and host a page which is broken into many functions. We will touch up the architecture of OpenFaaS and how python community can contribute to OpenFaaS Store We will discuss how to use K8's and it's Operator to push python function using OpenFaa", - "Last Updated": "08 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "https://www.linkedin.com/in/vivsridh https://twitter.com/vivek_sridhar https://github.com/vivsridh4 https://hasgeek.tv/rootconf/2018-day-2/1509-distributed-tracing-with-jaeger-at-scale https://hasgeek.tv/rootconf/cloud-sever-management-delhi/1435-auto-remediation-at-scale-using-watchers-vivek-sridha", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vivek Sridhar (~vivek861)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-push-deploy-serverless-python-function-with-openfaas-framework-on-kubernetes~e0Byb/", - "title": "Build, Push & Deploy serverless Python function with OpenFaaS Framework on Kubernetes" - }, - { - "Content URLs": "Functional Programming Blog: Functional Programming 101 Took inspiration from Mary Rose Cook and her blog which moved me to write \nFunctional Cod", - "Description": "Introduction This is an intermediate level talk, that\u2019ll help the audience appreciate the Functional Programming Paradigm and how it can be helpful in the day to day scripts that we write.\nIt\u2019ll also touch upon how the concept of functional programming can help elevate the thought process. What can folks expect? To learn what the functional programming paradigm is. To develop the thought process of thinking \u201cfunctionally.\u201d How python can be used to write functional code How day to day work can be made quick and easy The focus of the talk What is functional programming? - 10 mins This segment comprises of exploring what first class objects are and how we\u2019ve been conditioned to think that just variables can be taken as first class objects.\nThen we move on to explore how even functions can be considered first class objects, and what prime features need be followed to be able to say that functions are first class objects. What are first class objects? - 5 mins This segment explains what first class objects actually are and gives a really brief introduction on what makes variables or functions be treated as first class objects. \nThis also include a live coding section, explaining how functions can be: Assigned to a variable Passed as a parameter Returned from another function How does Python fit in? - 10 mins This section showcases the different utilities python inherently provides to support functional programming. It explains how map, filter and reduce, fit in and used in our daily habit of writing code. This also will be accompanied by live code examples and scenarios that we face regularly. We dive a little into partials and look at the tip of the iceberg called decorators. The Whys and Wherefores of Functional Programming - 5 mins This is a segment about various real life experiences; situations where functional programming can be the right tool and where this should be a total no, no. \nLike they say \u201cRight horses for the right courses\u201d, this segment will cover where not to use functional programming and when this debate shouldn\u2019t be brought up. This segment will also cover what is the best place to bring in functional programming and its benefits", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "You should have A basic Knowledge of Python Written about 1000 lines in Python A curiosity to learn more and get better ", - "Section": "Others", - "Speaker Info": "Farhaan is a Software Developer at Clootrack , a Bangalore base startup. He also contributes to FOSS projects and is lucky enough to have few documentation patch in Core Python. He used to heavily contribute to Pagure and still trying to make time to do the same. He actively maintains a blog and indulges in online discussion on twitter. He mentors students to contribute to Open Source Projects, he is also actively involved with Dgplug and is always up on IRC to have a quick discussion", - "Speaker Links": "Website: farhaan.me Functional Programming Blog: Functional Programming 101 Personal Blog Twitter: fhackdroi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Farhaan Bukhsh (~farhaanbukhsh)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-functional-programming-what-when-and-how~bkPNd/", - "title": "Python: Functional Programming - What, When and How?" - }, - { - "Content URLs": "Contents will be updated here: https://github.com/dipakkr/pycon-2018 You can also find the presentation here after the session", - "Description": "Computer vision enables the machine to see and analyze objects like humans do. Despite the significant recent advancement in computer vision, implementing it efficiently at a scale presents a serious challenge. Computer Vision deal with techniques like Object Recognition, Object Detection, Face Recognition, segmentation and many more. \nThe best example of this would be a Self-driving car. In this session, we will discuss, how to get started with computer vision using OpenCV. OpenCV is a computer vision library which provides an implementation of the various algorithm on a single call. However, It takes a lot of time and a good understanding of Convolutional Neural Network to build a good computer vision technique. Let\u2019s Start !!!!!! We will also see few demos DEMO - Image Filtering Object Detection Image Recognition", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Beginner or Intermediate in Python Basic numpy operation Love for Computer Vision and Python", - "Section": "Data science", - "Speaker Info": "a Researcher , Backend Developer , and Machine Learning Enthusiast . I am currently working as Deep Learning Research Intern at MNIT Jaipur . You can find out more about him at : https://github.com/dipakkr https://www.linkedin.com/in/dipakkr/ https://medium.com/@dipakk", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Deepak Kumar (~dipakkr)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-with-computer-vision-using-opencv~ejPPb/", - "title": "Getting Started with Computer Vision using OpenCV" - }, - { - "Content URLs": "1.Understanding Convolutional Neural Networks - CS231n Stanford-http://cs231n.stanford.edu/\n2.Any Deep Learning Library preferably Tensorflo", - "Description": "This talk will cover understanding limitations of Convolutional NN in detecting images. \nAfter understanding this limitation, I will introduce the concept of capsules.\nThis talk is highly inspired from the paper from Geoff hinton- Dynamic routing betwen Capsules-https://arxiv.org/pdf/1710.09829.pdf\nI will try to explain the process of training a multi layer capsule system on MNIST and comparing it with a convolutional net at recognizing highly overlapping images.\nI will use Tensorflow or Keras to show my demo Jupyter notebook.\nI will also discuss the limitations of capsules", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "1.Linear Algebra\n2.Probability and Statistics\n3.Any Deep Learning library (Tensorflow/pytorch/Keras)\n4.Deep Learning layers- Fully connected and Convolutional layer", - "Section": "Data science", - "Speaker Info": "Hi, I am Swapan Jain. After graduating in Computer Science from Delhi Technological University, I self studied AI by reading books,papers and taking courses online. I am a prospective graduate student from fall 2019", - "Speaker Links": "I currently do not have open source contributions, but I will begin the blog from August.\nmy twitter handle is @swapanj162. I will update about my blog or any project on my twitter", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "SWAPAN JAIN (~swapan)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/capsule-networks-overcoming-limitations-of-convolutional-neural-networks~egPGa/", - "title": "Capsule Networks - overcoming limitations of Convolutional Neural Networks" - }, - { - "Content URLs": " Project source code: https://github.com/sunainapai/makesite Additional material such as slides will be shared after the session in a GitHub repository", - "Description": "The session is about a static site generator named makesite.py that is written in less than 125 lines of code. It is a single Python module that contains everything necessary to develop a static site or blog from scratch. There is no need to read any documentation to understand how it works. There is no need to learn how to write configuration files to produce some desired effect. With makesite.py : The code is the documentation. The code is the configuration. The talk would focus on: A brief code walkthrough of the project that shows how a simple static site generator can be built from scratch without a lot of effort. How this project can be used for your static websites or blogs. Agenda First 5 minutes: Introduction and background: whoami ? What do I do? Prior experience in Python. Problem to be solved: a static site generator written in shell script to be rewritten in a sane language. A new project idea: Write some Python functions to render my static site generator. Scope of the project. Next 15 minutes: Code walkthrough (<= 125 lines of code). A particularly nice pull request from another developer. How to use the project for your own static websites or blogs. Last 5 minutes: Announcing the project on Hacker News and reaction from Hacker News community. Lessons learnt from the experience. Role of the community as a motivator for small projects. What next?", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Basic knowledge of Python", - "Section": "Web development", - "Speaker Info": "Sunaina Pai is a software developer from Bangalore. She works on big data technologies during the day. In the evening, she dabbles in Python and Lisp to explore the beauty in programming", - "Speaker Links": " LinkedIn - https://www.linkedin.com/in/sunainapai/ GitHub - https://github.com/sunainapai/ Blog - https://sunainapai.in/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sunaina Pai (~sunainapai)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/makesitepy-a-simple-lightweight-and-magic-free-static-siteblog-generator-for-python-developers~elPge/", - "title": "makesite.py - A simple, lightweight, and magic-free static site/blog generator for Python developers" - }, - { - "Description": "Can we make any machine talk or give speech, naturally like any human ? Can my digital personal assistant like Siri, Alexa etc mimic my voice or give response in my own voice ? Generating human like natural voice has been a topic of research for a long time and a quite challenging task. But recent development in field of Speech Synthesis using advance deep learning technologies has made it achievable. Speech Synthesis has been integral part of any voice driven application. Although we have been able to generate good quality voice using standard method but in reality the generated voice is still too robotic ,emotionless and far away from the actual human voice. In the recent AI development in this field has made it possible to generate expressive human level voice. There are many recent papers like wavenet ,Tacatron and deep voice which do well upon precisely generating actual human voice and even mimic any person voice. In this talk , I will cover literature of voice synthesis and how we can generate human level voice without doing phd in speech processing. Key Components of talk : 1. Understand the basic literature of speech synthesis 2. Components of speech synthesis engine. 3. How to create own voice dataset. 4. Building basic text to speech engine using Tacotron2. 5. Application of real time speech synthesis", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Basic knowledge of python and jupyter notebook. Familiarity with machine learning components. Basic knowledge of linear algebra, probability distribution and calculus. Knowledge of speech processing is bonus .", - "Section": "Data science", - "Speaker Info": "Myself Rishikesh ! I am working at Humonics Global Pvt. Ltd as Data Scientist. Apart from my job I am actively contributing to open source projects and speaker of many data science communities like PyData Delhi, Delhi Kaggle Group etc. \nMy area of expertise are Speech processing, Data science, Deep learning and statistical modeling ", - "Speaker Links": "Linkedin Githu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rishikesh kumar (~rishikesh)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speech-synthesis-engine-for-generating-human-like-natural-voice~e9mBe/", - "title": "Speech Synthesis engine for generating human like natural voice" - }, - { - "Description": "A/B testing is widely used to compare 2 alternatives of doing something in order to find out the best alternative. Typical A/B testing involves statistical hypothesis testing which is not intuitive. On the other hand, Bayesian methods are much more intuitive and are based on less assumptions. This talk aims to give a brief on how to do an A/B test with Bayesian methods using Python", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Basic understanding of Python Basic understanding of probability", - "Section": "Data science", - "Speaker Info": "Vaibhav Pawar is the head of analytics at Loylty Rewardz. He has 10+ years of experience in using data science to solve business problems across industries like banking, retail, airlines, insurance etc. in the areas of marketing, product, digital and consumer loyalty analytics. He has deep understanding of machine learning techniques and has hands-on experience in automating and deploying ML solutions at scale. He graduated from IIT Bombay in 2008. His master's thesis was in the field of Bayesian networks", - "Speaker Links": "https://www.linkedin.com/in/vaibhav-pawar-588391a", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vaibhav Pawar (~vaibhav41)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bayesian-ab-testing-using-python~bmP9a/", - "title": "Bayesian A/B testing using Python" - }, - { - "Content URLs": "Participants should know about the classification of text using ML and little knowledge about name entity recognization", - "Description": "So, there will be a simple reminder chatbot made by using a machine learning algorithms. There will name entity recognization and classification algorithms combined to have a chatbot work", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "tensorflow\nkera", - "Section": "Data science", - "Speaker Info": "I am AI enthusiasts. Love to make an end to end AI products", - "Speaker Links": "I am a chatbot developer. https://github.com/sam-a", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sambit Sekhar (~sambit74)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/making-of-chatbot-without-using-any-platform~enPWb/", - "title": "Making of chatbot without using any Platform" - }, - { - "Content URLs": "Pyqtlet: A library that integrates Leaflet into PyQt Source Code on Github Code for example applications using Pyqtle", - "Description": "Qt is a popular GUI framework used across industries for many different purposes. PyQt is the python wrapper around Qt , and thus it has access to all of the same features. Interestingly, Qt implements the code of Chromium Web Engine, which gives you all the power of a browser, and thus the functionality of any JavaScript library. For the purpose of this talk, we will discuss how to integrate LeafletJS ( a JS library for maps ) into PyQt , thus allowing apps written in native python to have beautiful interactive maps. Then we will go into further details of how to add these maps into simple apps. Finally, we will talk about how to integrate other JavaScript libraries into Python, and all the benefits this can bring", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " A familiarity with Front End Development concepts Beginner level JavaScript Experience with any GUI framework", - "Section": "Others", - "Speaker Info": "I am a developer at a Banagalore based start-up called Skylark Drones. As one of the few developers in the team, I get to don many hats across domains. I create POC web applications, work on internal tools dealing with GIS, automate processes involving large volumes of data flow and write code that runs on the drone itself. And that's just a typical week. I have been working in Python for over 2 years, and love it. The Zen of Python is essentially my life philosophy and I enjoy the simplicity and expressiveness that the language grants. My interests include: Biryani, Ultimate Frisbee and Hating on JavaScript", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Samarth Hattangady (~samhattangady)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/integrating-js-libraries-into-pyqt~boPBd/", - "title": "Integrating JS libraries into PyQt" - }, - { - "Description": "Blockchain is one of the most revolutionary technologies of our times, which is still maturing and with immense potentials yet to be realised. In essence, it is a distributed public database of records which opens rooms for cryptocurrencies and smart contracts to be built on top of it. While the internet is abuzz with blockchain, the concept is difficult to comprehend in its entirety. It lies at an intersection Game Theory, Cryptography, Network and Data Transmission, Economic and Monetary Value, and Trust Systems. It becomes difficult to wrap one's head around each of these domains and get a 360 view of the subject. The workshop tries to help the audience build a comprehensive understanding of the subject, with Python being the programming language. The attendees will leave with a complete picture of the moving pieces of the jigsaw puzzle that blockchain is, and by the end of it will be able to build their own blockchain, cryptocurrency and a smart contract POC on ethereum. The workshop is divided into three parts : Context Building - 45 mins Blockchain fundamentals and principles - 90 mins Coding a smart contract in Vyper (pythonic solidity) - 30 mins 1. Context Building : Basic of Game Theory - Introduction and the Iterated prisoner's dilemma (IPD), creating matches and tournaments using Axelrod python library Cipher encryption and decryption in python Demonstration of network fundamentals and internet data handling Evolution of money and trust systems and why bitcoin is not a mainstream currency When blockchain should be avoided Why decentralisation matters 2. Blockchain with Python: Understanding mining, incentives, payment records, and ownership Programming a basic prototype of a blockchain Adding a proof of work to our prototype Putting our prototype on a database Doing transactions on unique addresses Adding decentralisation to our prototype by distributing it over a network 3. Coding a smart contract with Vyper Understanding what a smart contract is Programming one with Vyper on Ethereum", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Intermediate understanding of Pytho", - "Section": "Others", - "Speaker Info": "Saket is founder-techie at Sosio . Sosio caters to the large-scale data needs of enterprises in payments, supply-chain, Ad-Tech, and non-profits. He has been programming in Python for over 10 years and has been semi-active in tech-conferences attending and delivering talks across the globe. In his personal capacity, he has introduced Python to more than 500 individuals and conducted training sessions at corporate houses like Oracle. In his previous life, he spent a good chunk of his time optimising computational mechanics algorithms. He is implementing blockchain with one of his supply-chain partners and would like to share his learning experience in the workshop", - "Speaker Links": "LinkedIn Twitter Github SpeakerDeck Medium Instagram", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Saket Bhushan (~saket)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-and-smart-contracts-from-first-principle-in-python~epPpe/", - "title": "Blockchain and Smart Contracts from First Principle in Python" - }, - { - "Description": "Do you or your team write lots of services? Do you worry about the less glamorous bits about maintaining your service? Is your company growing aggressively and adding code in lots of different programming languages? Are you tired of writing HTTP clients for all your services in every programming language? Do you build your APIs with Python and then write HTTP client code in Java for your mobile apps? Do you want to deprecate your old API but are worried all your clients won't be able to keep up? - Then this is the talk for you. Did you know that you're not the only one who has these problems? Companies big and small struggle with these but most of them seem to have settled on how to approach them. In this talk we'll look at how we can structure our data for compatibility with our present and future clients using Protocol Buffers. We'll also learn how to communicate this data effectively to our clients using GRPC, with almost no effort spent on serialisation/deserialisation. We will also see how we can write services that can be consumed by non-Python clients and how we can consume services written in languages other than Python but without having to learn a new language or a clunky framework. The goal is to build a service that is easy to write, easy to consume and scales very efficiently as the problem grows. In short, we'll learn to do more with less. This will be a demo-driven talk with few slides. We will look at and write real Python code that gets things done", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Basic understanding of REST over JSON would be helpful, but is not necessary. We will cover the basics at the beginning of the talk. Basic understanding of Python classes would also be helpful, but is also not necessary. No other pre-requisites", - "Section": "Web development", - "Speaker Info": "Hi, I've spent almost all my adult life building distributed systems and understanding how they work. I've worked on interesting problems almost exclusively in a polyglot environment and this often reflects in the code I write or my approach to dealing with problems. I've debugged strongly consistent* key-value stores, run container orchestration systems at scale and broken my foot once from falling down a stairwell. I work with Grofers trying to make developers more productive and infrastructure more reliable. I look forward to seeing you at PyCon Indi", - "Speaker Links": " https://kasisnu.com https://www.linkedin.com/in/kasisnu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kasisnu Singh (~kasisnu21)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/protocol-buffers-and-grpc-building-friendly-services~bq90b/", - "title": "Protocol buffers and GRPC - Building friendly services" - }, - { - "Description": "Python 3.5 RC introduced type hints in the standard library, since then a lot of projects use Python hints in the code. The large open Python source projects like Zulip use it. For past one year, at work, I have been using Python type hints in the data pipelines and neural networks. The talk is based on the experience. In this talk, I'll cover the following topics. Code before and after using type hints. Advantages of using type hints Pain points of using type hints Developers view of using type hints Second thoughts of using type hints", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " You should possess familiarity with Python, and grasp of the type system.", - "Section": "Core python and Standard library", - "Speaker Info": "I'm kracekumar, working as software engineer for past seven years. My experience has been around building web applications, data pipelines, and automating servers. Currently, I work as a Software Engineer at minds.ai", - "Speaker Links": " GitHub", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kracekumar Ramaraju (~kracekumar)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/experience-with-python-type-hints~dwl1e/", - "title": "Experience with Python type hints" - }, - { - "Description": "Submitting a proposal for to deliver a talk on \u2018EEG based Cognitive Brain Mapping using Python\u2019 under the broad area of signal processing. An intensive and in-depth theoretical and practical aspects in EEG signal processing for different research applications will be discussed. The development of a brain computer interface using EEG for control applications shall be explained with relevant research results. The demonstration to control the interfaced hardware using acquired brain signals via EEG shall be provided. The talk is intended for beginners in EEG signal processing but intermediate users will find it informative as well. Cognitive neuroscience is being widely explored these days to develop more interactive brain computer interfaces (BCI) particularly for device control applications. Neural driven BCIs are gaining importance while providing assistance especially to paralytic/ physically locked-in patients in order to restore a useful life. An attempt shall be made to explain that how a cognitive activity of human subjects and associated neural activation captured via electroencephalography (EEG) vcan be translated into action. A framework to develop an automated control application environment using Python shall be discussed in detail . The analysis of a multichannel EEG dataset acquired from human subjects shall be explained and discussed in Python environment to extract the relevant features to develop possible control applications via hardware interfacing through Arduino. The proposed methodology can be utilized to offer patients with severe motor neuron disorders an alternative means of communication and control over their environment via applications for neurorehabilitation of motor and cognitive functions", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Biomedical signal processing\nBasic Pytho", - "Section": "Others", - "Speaker Info": "Rashima Mahajan (PhD ECE)\nAssociate Professor\nFaculty of Engg and Technology\nManav Rachna International Institute of Research and Studies, Faridaba", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "rashima", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/eeg-based-cognitive-brain-mapping-using-python~er64e/", - "title": "EEG Based Cognitive Brain Mapping using Python" - }, - { - "Content URLs": "https://speakerdeck.com/siliconsenthil/how-we-built-heroku-like-paas-over-aws-with-just-pytho", - "Description": "We wanted an easier way of creating and deploying microservices implemented in different tech stacks. We wanted it as simple as PaaS platforms like Heroku. On the other hand, we did not want to miss the high level of customizability with IaaS like AWS. So, we blended the benefits of these two. i.e. utmost convenience with high-level of customizability. Instead of taking the route of Puppet, Chef, Ansible etc. , we built a CLI tool in Python that enables our developers to create & deploy service with a single command. We call this cloudlift :). It's been more than a year since we started using it and it's been fantastic. You will learn about our journey of building and using cloudlift", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Python Basics of AWS ecosystem", - "Section": "Developer tools and Automation", - "Speaker Info": "Converting human aspirations into reality via software has been my fascination and my job. \nHave been a programmer for more than a decade and leading teams for a while now. \nWorked at ThoughtWorks for 8 years. Currently, I lead the engineering team at Simpl. Have lead projects that are diverse in terms of tech stack and scale. Worked for enterprises and startups.\nInterested in talking about on design, technologies, the philosophical angle of tech etc.\nBelieve software building is a unique combination of science, art, and collaboration", - "Speaker Links": "http://siliconsenthil.i", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Senthil Velu Sundaram (~senthil13)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-we-built-heroku-like-paas-over-aws-with-just-python~avk0b/", - "title": "How we built Heroku-like PaaS over AWS with just Python" - }, - { - "Description": "Most of us use micro-services for all the goodness that they bring in. But there are some pain points too, to be addressed while using multiple micro-services. One of the them is testing. With all the micro-services as moving parts, how does one ensure that the whole app is coherent and well tested ? Is it enough if all the unit tests pass in each micro-service code base ? What else do we need to be confident in order to ship the code like a boss ? Outline of the talk Challenges in testing micro-services Consumer driven contract (CDC) tests - what are they, how they work ? How Pact works and what are the available tools in Python ? How are CDC tests simpler than integration tests ? Best practices in maintaining the pact file Demo: how to write CDC tests with Pact for a simple micro service", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Awareness of micro-service environments or APIs would be helpful", - "Section": "Developer tools and Automation", - "Speaker Info": "Devi is an independent software consultant and trainer with an experience of more than 12 years in the industry. She has been working with PowerToFly as a lead developer/architect. She has given a couple of talks at PyCon India, RootConf before, which were well received. She has done M.Tech in Computational Science from IISc, before which she tried out teaching mathematics. She spends her free time enjoying with her 2 daughters and painting with water colors", - "Speaker Links": " https://www.linkedin.com/in/asldevi/ https://powertofly.com/talents/devia https://speakerdeck.com/asldevi/rest-apis-at-pycon-india-2015", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "asldevi (~asldevi)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/testing-micro-services-made-easy~axm3b/", - "title": "Testing micro-services made easy" - }, - { - "Description": "Description \u201cTradition is not to preserve the ashes, but to pass on the flame\u201d. Running Python coding workshops in areas with unreliable internet access and with outdated hardware among the participants present a challenge for capacity building and knowledge sharing. Jupyterhub run in a local area network can bridge this gap and therefore make your workshops more resilient. Contents The talk will demonstrate how to set up and run a workshop successfully in an environment without internet access and the absence of uptodate hardware on real-life projects using Python, PySpark and Jupyterhub. Contentwise the session focuses on data science and the preprocessing of mobile phone metadata in order to extract features. The talk will include time for Q&A. Take aways What are the challenges running a coding workshop in adverse\n environments? How to set up a Jupyterhub in a local area network?", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Interest in spreading your own knowledge to people beyond the usual suspects", - "Section": "Data science", - "Speaker Info": "We are a young university spinoff project of the department of statistics of the Freie Universit\u00e4t Berlin, Germany called \u2018knuper\u2019. We work with governments around the world by augmenting official statistics with mobile phone metadata and other big data sources", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "knuper", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/coding-for-everyone-setting-up-coding-workshops-in-challenging-environments~azoZb/", - "title": "Coding for everyone - Setting up coding workshops in challenging environments" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of Github Repository", - "Description": "Deep Learning has revolutionized areas like Speech recognition. Recently, deep learning approaches have obtained very high performance across many different NLP tasks.\nIn this workshop, we will see the application of deep learning to common NLP Tasks and implementation in python using Keras Library. Agenda for the Talk: An Introduction to Deep learning - MLP, CNN and RNN and its implementation in Keras Discussion of Common NLP Tasks Language Modelling with RNN Word Embeddings - Word2Vec and Glove Sentence Embeddings - WMD and Doc2Vec Embed, Encode, Attend, Predict - Deep Learning formula for state of the art NLP Models Text Classification with 1D-CNN and LSTM Sentiment Analysis with Recursive Neural Network and Tree-LSTM Building Question Answering with Bi-Directional Attentional Flow Model Entity Extraction using Bi-LSTM and CN", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "A Basic Knowledge of Python, Machine Learning, Deep Learning and Natural Language Processing", - "Section": "Data science", - "Speaker Info": "Subramanya T A is Senior Data Scientist at Sentienz. He heads the Data Science team at Sentienz", - "Speaker Links": "LinkedIn Profile:\n https://www.linkedin.com/in/subramanya-t-a-7306a729/ Sentienz Website - http://www.sentienz.com", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "T. A. Subramanya Paddillaya (~t._a._subramanya)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/applying-deep-learning-for-nlp-using-python-workshop~dynEe/", - "title": "Applying Deep Learning for NLP using Python - Workshop" - }, - { - "Description": " Introduction to ensembling techniques About XGBoost Parameters and their tuning Application using python Latest updates", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Basic knowledge of python and machine learnin", - "Section": "Data science", - "Speaker Info": "Ina Jain is currently working as a Data Scientist in Pramati technologies and has 6+ years of industry experience", - "Speaker Links": "https://www.linkedin.com/in/inajain27", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "ina jain (~ina)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/xgboost-tree-based-ensembling-technique-using-python~dBykb/", - "title": "XGBoost - Tree based ensembling technique using Python" - }, - { - "Content URLs": " https://medium.com/@anandology/designing-restful-apis-671e091a2561 https://github.com/anandology/restful-apis/", - "Description": "APIs are all around. Everyone talks about RESTful APIs, but what does \u201cRESTful\u201d really mean? This hands-on workshop takes you through everything that you need to know to design great RESTful APIs. During the workshop, the participants will understand the key concepts behind RESTful APIs, critically examine some of the popular APIs, design an API from scratch and see how APIs evolve. We'll also take couple of popular APIs, rip them apart and design a better version of them. Participants will be divided into smaller groups to allow discussions and most of the time is spent thinking about the design. Please note that this is about designing APIs, and not about the tools. Participants will spend lot of time thinking about and designing API endpoints and request/response format, but will not write any code. OUTLINE Introduction to HTTP Internet vs. World-Wide-Web Key Concepts of Web URL, HyperText, HTTP Representational State Transfer (REST) What is REST? Thinking in Resources HTTP Methods Status Codes Resource Representation Examples of RESTful APIs Good and bad examples of RESTful APIs Designing an API version 0 - Naive CRUD API for blog posts. version 1 - blog api made RESTful version 2 - add support for tags version 3 - add support for comments version 4 - add suport for authors Authentication and Secutity Introduction to authentication patterns Study of Basic Auth, OAuth, access keys and JWT Adding authentication to the blog API Excercises Best Practices Pratical tips and tricks Versioning APIs Documenting APIs ", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "The workshop is targeted at web developers interested to build APIs. The participants are expected to have good understanding of how web works", - "Section": "Web development", - "Speaker Info": "Anand has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, rorodata , which he recently co-founded. He regularly conducts advanced programming courses through Pipal Academy . He is co-author of web.py , a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive", - "Speaker Links": " https://anandology.com/ https://pipal.in/trainers/anand https://github.com/anandology", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Anand Chitipothu (~anandology)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-restful-apis~aAx3e/", - "title": "Designing RESTful APIs" - }, - { - "Content URLs": "Slides Ur", - "Description": "Ever wanted to play your favourite song on guitar quickly even when you don\u2019t know how to play guitar? Our Python based MIDI to guitar tabs Transcriber can help you do that: \u2022 Find your song in MIDI format (with .mid as file extension) \u2022 Let our Python Transcriber do its magic \u2022 Enjoy the tablatures Transcribing MIDI files directly to tablature creation ready JSON A lot of people take to learning the guitar every year. But most of them give up mid-way because of one or more of the following reasons: Guitar is a difficult instrument to learn People want to learn guitar by playing songs but are unable to do so right from the beginning Results are often not visible immediately depending on a person's existing knowledge of music and willingness to learn guitar Enter Python Though it seems to be quite easy to manually create and make the app read guitar tablatures for songs, the following challenges need to be addressed: Readiness of the output to support playback of a song along with tablatures - this essentially means storing the timing for each note/chord (when many notes are played together) in order to play the song exactly as it is The whole process would be incredibly time consuming In order to overcome these challenges, a simple yet efficient solution was derived - to convert a MIDI file directly into guitar tablatures. Python was chosen for implementation of the solution for the following reasons: Python has a very efficient and time saving file I/O mechanism and the current use case operates completely on MIDI files and the Transcriber outputs a JSON file, which in turn is served to the client. More libraries to read MIDI files and present them in an understandable manner than any other language and their ease of use. These libraries, when used in conjunction with each other offer all the features that Java's javax.sound.midi package offers. Availability of renowned libraries such as numpy and scipy for the algorithm to determine most optimal finger positions A plethora of options for using a server side framework to host the Transcriber as a service Since Python is an interpreted language, it is really useful for quick experimentation with tools like IPython unlike languages like Java in which complete programs need to be compiled beforehand. This saved us a lot of time. ...Where Credit is Due The solution could not be achieved without the use of the fantastic libraries used below for reading MIDI files: Mido by olemb Python Midi by vishnubob music21 by Prof. Michael Scott Cuthbert (MIT) The authors have our gratitude. How the Transcriber Works The high level working of the Transcriber is as follows: MIDI files are read and all the guitar parts in the song (commonly referred to as guitar tracks ) are extracted in the form of notes and chords An algorithm calculates the best possible finger placement on the guitar fretboard for these notes and chords A time driven JSON is generated for use by any platform that can parse JSON to do one or more of the following: Play the song Display guitar tabs in sync along with song playback Only display guitar tabs Why Use the Transcriber? Some work has already been done in this area and there are existing open source solutions like TuxGuitar and a few others. But the Transcriber here produces up to 70% better results than any of these solutions. By better , the following is meant: Transcriber generates more easily playable tablatures The tablatures also mimic up to 60% of most of the original tablatures", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Core python Ability to integrate and use third party libraries", - "Section": "Core python and Standard library", - "Speaker Info": " RIshabh Shah Rishabh has around 4 years of python programming experience, he has developed an array of applications of which one was this Transcriber. Inputs from real world guitar players have been quite useful while developing the Transcriber. He developed this transcriber with one of his colleagues Srinivas Kalyani\n 2. Srinivas Kalyani Srinivas has around 3 years of technical experience with nearly 1.5 years of experience in Python. He has worked primarily on Django and entered the world of Core Python while writing the Transcriber", - "Speaker Links": "A list of few of our blogs can be found as follows: Rishabh: A Guide On Building REST API\u2019s Using Python Frameworks Slash Down Your Hosting Costs By 95% On Google App Engine Finding Your Google App Engine Hosting Costs Too High? Here\u2019s How To Fix It Srinivas: Need A Web Scraper? Here\u2019s How To Build One Using SCRAPY AND XPATH", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rishabh Shah (~rishabh104)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learn-guitar-via-python-programming-midi-parsing~bDAyd/", - "title": "Learn Guitar Via Python Programming (MIDI Parsing)" - }, - { - "Content URLs": "You can view my blogs 1. Women and Data Science 2. Quantization and need for TPUs 3. Application of signal processing in machine learning You can view my various slides her", - "Description": "Imagine a play in a small theatre, where you are a producer sitting with the audience. Let us suppose the actors are weights and there are rows and rows of TPUs/GPUs behind. The director has assured you that they have rehearsed the play about 10 times, now all you do is pray that the performance goes well\nImagine you have 100 different tasks to be performed backstage, but the theatre given to you is really tiny. How will you manage? The answer is by optimizing the tasks. Divide tasks between individuals in such a way that you require less time and space. But how do you manage that with a neural network? How does quantization affect neural computations? When you are dealing with a large amount of data, one has to keep in mind the ever-changing values that one might obtain. Especially, signal data with large SNR (Signal to Noise Ratio) in them, which causes different sets of data to be produced. The best way to deal with such signal data is to apply truncation or rounding off such values, typically making it a many-to-few mapping. This mapping happens from 32-bit(at training) to 8-bit(at inference). On the other hand, traditional Internet of Things (IoT) infrastructures has two main parts \u2013 the edge and the cloud. The edge is the part of the system that is closest to the source of data. It includes sensors, sensing infrastructures, machines, and the object being sensed. The edge actively works to sense, store, and send that data to the cloud. So how does quantization help with edge computing? Does it have the potential of changing how we run models on the cloud? TALK AGENDA Introduction: 5 mins A Beginner's Guide to Quantization: 5 mins Understanding Quantization in TPUs: 10 mins Demo: Implementation of Quantization in Edge computing: 10 mins", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Knowledge on Tensor Processing Unit . Knowledge of IoT and Edge Computing Knowledge of Deep Learning", - "Section": "Embedded python", - "Speaker Info": "I am a fresher from SRM Institute of Science and Technology. I understand that engineering is not everyone's cup of tea and that everyone has a different perception of it. During my second year of study, I realized that for me education was something that was present beyond books and into practical applications. So I collaborated with a few other mates in college and started this place called the Next Tech Lab which was involved in cutting-edge innovation and novel research ideas. As a few of my achievements that the lab made me achieve included winning the Smart India Hackathon 2017 as the first prize under Ministry of Steel for using machine learning to detect power theft in India. Recently I was invited to the WiPDA conference in Xi'an China for presenting my work in GaN modeling of devices using machine learning, a collaboration with the University of Cambridge. I have around 3 IEEE Xplore Paper s (https://ieeexplore.ieee.org/document/8293259/)and 1 Elsevier papers for my contribution to electrical and machine learning fields As a lab, we have done so much more to protect gender diversity even among the strength of 200 members keeping a ratio of 50:50. We were portrayed for accomplishments by the News 18 in a short video. Over the past 6 months, I have had the opportunity to work and intern at Saama Technologies where I research on Machine Learning in order to accelerate clinical trials. A part of this work has exposed me to how models are necessary to be optimized across all devices big or small", - "Speaker Links": "My various talks in meetups in chennai 1) A Glance into Image Recognition of Cursive Text using OCR . 2) A Beginner's Guide to Machine Learning-Women Who Code Chenna", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "archana iyer (~archana52)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quantiziting-of-neural-networks-for-edge-computing~eEBYa/", - "title": "Quantiziting of Neural Networks for Edge Computing" - }, - { - "Content URLs": "To be added soon", - "Description": "Human psychology has remained and continues to remain one of the most challenging areas of research as it aims to understand individual\u2019s behavior and mind, including conscious and unconscious phenomena, as well as feeling and thought. The extent of impact social media has caused on the human mind is huge and perhaps, hard to imagine. Thanks to python and it's brilliant capabilities to process natural language, we can now understand how social media is affecting our lives from a psychological perspective and if it is capable of changing our behaviors, our expressions, our sleeping patterns, or even emotions. From social posts, we can draw interesting conclusions about both men and women if we can comprehend what are the topics they are most interested in, what time of the day are they most and least active etc. Core idea: Collect a dataset from Twitter (or any other social network) of the world's top 400 most influential women for the year 2013 and for the year 2018 Train an NLP model and use this model to classify the collected data under various categories like education, religion, etc. and identify if the post is a concern, compliment, complaint etc. Perform a year-wise trend analysis to identify the topics they are most interested in and parameters like the most/least active time of the day, the most active/least active day of the week the average time spent on twitter per week/month etc. Carry out behavioral analysis by evaluating how the ways of expression, activity levels etc. have changed on social media over the last five years and what might have been the possible reasons for the same Structure: 5-10 mins \u2013 Introduction and discussion ( algorithms and concepts being used ) 10-20 mins \u2013 Code walkthrough followed by discussions on the results obtained (Please refer the core idea section for more details) Remaining time \u2013 Q/A or general discussion Contents: An introduction to natural language processing - text normalization, n-grams, PoS tagging An introduction to deep learning - neural networks and neural language models (framework - keras) A brief discussion on the implementation of a sentiment classifier - Naive Bayes classifier/RNN classifier If time permits, test out a few tweets to understand the working of the classifier Conclusion - how can the results help identify opinions, attitudes, emotional states & future scope (of the project) Note: The entire talk will be a powerpoint based presentation along with illustrative code snippet", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "Python - Beginner/Intermediate Machine Learning - Beginner NLP/Deep learning techniques - Beginner Keras/Tensorflow - Beginner Basic familiarity with the following libraries/tools: 1. numpy 2. pandas 3. matplotlib 4. jupyter noteboo", - "Section": "Data science", - "Speaker Info": "The speaker of this talk is Reyha Verma . She is currently working as a data scientist at Sprinklr, Gurgaon. Since her organization is the world's best social media management platform, she spends most of her office and her personal time juggling between new, efficient deep learning models and tons of social media data. She is an open-source enthusiast who has also previously been a mentor with Zulip, an open-source python based chat application for FOSS Outreachy program 2016 and has undertaken research projects at National Sun Yat-Sen University, Taiwan and Bhabha Atomic Research Center (BARC), Mumbai while pursuing her undergraduation at the National Institute of Technology, Srinagar", - "Speaker Links": "LinkedIn - https://www.linkedin.com/in/reyhav Github - https://github.com/reyha Twitter - https://twitter.com/reyhav", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "reyha (~reyha)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decode-human-behavior-through-code-a-counter-intuitive-approach~b8lgb/", - "title": "Decode human behavior through code: A counter-intuitive approach" - }, - { - "Content URLs": "Rough draft of slide", - "Description": " tl;dr : As data becomes increasingly extensive, it becomes important to move your models away from the cloud to where your data is being generated to reduce latency, increase security and save internet bandwidth. This talk will be about how you can run trained TensorFlow models on Edge devices and how you can use Edge Computing accelerators like the Neural Compute Stick to make your models run even faster. Long Version There are a lot of very compelling reasons for shifting computations away from the edge and into the cloud, with the most important being latency issues. Here, latency refers to the time it might take to send data to a server and then receive the response. The few seconds of delay caused by this might not be a problem for your smart home applications, but when in an industry, those few precious seconds, or even microseconds can cause a machine to breakdown or even take lives. Furthermore, many industrial processes might be happening in places where running an internet line may not be possible: a mine, for example. And even if having an internet connection is possible, most companies are hesitant to send data over an internet connection and risk exposing their data to hackers prompting them to keep their data in-house. Finally, if you have a lot of sensors, you will probably be streaming data in the order of gigabytes every hour. It does not make sense for companies to pay for the bandwidth to send that much data when most of it will be discarded anyways. Thus it is important to shift all that computation to where the data is being generated. This talk will be about how to move your existing TensorFlow models to Edge devices like Raspberry Pi's. The talk will also introduce other Edge Computing hardware like the Neural Compute Stick to make your models run even faster on Raspberry Pi. Why Attend this talk This talk will give the audience an understanding of Edge devices and Edge Computing. You will also learn the best practices to deploying models on the Edge. The live demo's will also give the audience an idea about how to run TensorFlow models on embedded devices. Topics covered: Edge Computing and Raspberry Pi - 5 Minutes TensorFlow Models - 5 minutes Demo on how to run models on the Edge - 10 minutes Demo with Benchmarking tests - 5 minutes Q/A - 5 minutes", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Python 3.5 TensorFlow 1.7", - "Section": "Embedded python", - "Speaker Info": "I have been working in the field of ML for the last year. I am currently working as a Deep Learning Research Engineering Intern at Saama Technologies, where I am using TensorFlow to reduce the time taken for clinical trials and help get patients medicines quickly. My primary work was with the University of Cambridge. There I used TensorFlow to create a model that can optimize the design of Gallium Nitride circuits. This work was published in one of the world's largest conferences on Power Electronics - WiPDA . In my second year of UG studies, I realized that engineers should have more practical knowledge. I started a student-run cross-disciplinary research lab called Next Tech Lab . As a part of the lab, I won the Smart India Hackathon for creating an app that could be used to detect electricity power theft . I have also published many research papers in IEEE and Elsevier . I am also an active member of the Indian Deep Learning Community . I also write articles such as this one: convolutional filter types and Data Correlation and Machine Learning . I believe in spreading knowledge and teaching others about Machine Learning", - "Speaker Links": " Links to slides for my talks - here Links to talks and github- here Website - csoham Medium articles - here LinkedIn Saama blog", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Soham Chatterjee (~soham48)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/running-tensorflow-models-on-a-35-device~dGELa/", - "title": "Running Tensorflow models on a $35 Device" - }, - { - "Description": "Static code checking should be easy, but in practice, it\u2019s easy to be overwhelmed by the volume of tools available, and disappointed with the returns on time spent integrating. The world of static code analysis has evolved a great a deal and appears to be underutilised for Python. Here are some of the things we are going to cover: Linting - automate your code reviews Measuring test coverage - legacy code is that which is not tested Security checks - what can you get for free? Static type checking with a dose of gradual typing Dead code analysis - reduce the noise Setting up an effective CI pipeline - aiming for less process and more results Setting up productive developer environments - leverage code completion and type hints", - "Last Updated": "09 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-static-code-checking-asymptotically-approaching-perfection~dLRXa/", - "title": "Python static code checking: Asymptotically approaching perfection" - }, - { - "Description": "If you\u2019ve been using python for any length of time, you know it as this versatile tool that can be used to build almost anything, and in a very friendly way. But Python use in the large codebase arena is very different from Python for a small service. What if you knew that that shift was due? What if you knew that the next project you started was definitely going to be collaborated on by a hundred developers? Let\u2019s look at these differences and prepare ourselves and our codebases for that shift. We\u2019ll learn how: Maintaining large codebases isn\u2019t free, and how the Python ecosystem\n supports you in your efforts. Testing a large application isn\u2019t easy, and how to use the latest and\n greatest testing methods to make sure your code does what you expect\n it to. Immutable data structures aren\u2019t just easier for humans to process,\n but also for machines to validate. Python has learnt from its neighbouring languages, and now has a type\n system that is here to help.", - "Last Updated": "09 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/reliable-code-what-the-giants-have-taught-us~dJRJd/", - "title": "Reliable code: What the Giants have taught us" - }, - { - "Description": "Do you use isinstance() frequently and know there is a better way, but you just don\u2019t know how? Have you been bitten from using mutable arguments to functions? Python has an interesting data model as a dynamic language. This model shapes the programs you write and a good understanding of this goes a long way in writing effective code.\nThis talk covers the various approaches you could take to handle the behaviour of your objects from duck-typing to the new dataclasses introduced in Python 3.7 .\nWe will also take a deep dive into the Python data model itself and see how we can leverage it to give intuitive APIs to our libraries. All the benefits of having a thought out data model apply. Your code can be cleaner and easier to test. \"Bad programmers worry about the code. Good programmers worry about\n data structures and their relationships.\" - Linus Torvalds \"Show me your flowcharts and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won\u2019t usually need your flowcharts; they\u2019ll be obvious.\" - Fred Brooks", - "Last Updated": "09 Jul, 2018", - "Section": "Core python and Standard library", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-type-system-building-an-effective-mental-model~aKRMe/", - "title": "Python Type System: Building an effective mental model" - }, - { - "Content URLs": "Slides: https://slides.com/yashmehrotra/distributed-tracing/ Github Repository to be added soo", - "Description": "This talk would be about our journey to successfully trace every request in our Python-based microservice Architecture. An outline of the talk: Why distributed tracing ? How distributed tracing works at a glance ? Distributed tracing using Python Insights you can gather from distributed tracing Performance Observability Easily debugging microservice failures", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Basic knowledge about python based web applications An idea about microservice architecture Unhappiness with existing inter-service debugging tools ", - "Section": "Others", - "Speaker Info": "This talk will be given by Yash Mehrotra. He is currently working at Grofers where he is a part of the Search Team. He has also interned at HackerEarth, AdWyze and is a former Mozilla Winter of Security Participant. He recently acquired a keen interested in distributed systems and loves to beat people at FIFA in his free time", - "Speaker Links": "Website: https://yashmehrotra.com/ Github: https://github.com/yashmehrotr", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Yash Mehrotra (~yash2)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/distributed-tracing-for-your-python-based-microservice-architecture~aM6Ob/", - "title": "Distributed Tracing for your Python-based microservice architecture" - }, - { - "Description": "In recent times, we have seen a startling rise in data aggregation and reliance on machine learning models. This has grave consequences when our data is not protected and when model behaviour is deliberately modified. Differential Privacy is a privacy aware sampling technique that ensures that no one individuals property can be extracted from the model. Adversarial examples look similar to real images but are engineered in such a way that they result in nonsensical predictions from ml models. Recent research has shown that the issue of adversarial attacks on machine learning models could be solved by using differential privacy. This talk aims to introduce differential privacy, adversarial examples and introduce the audience to the vibrant python research community around these topics", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "An understanding of how neural networks wor", - "Section": "Data science", - "Speaker Info": "I'm Sadhana Srinivasan, I did my master's in Mathematics from BITS Pilani. I've been coding in python and working in machine learning for the past 3 years, having taught deep learning and machine learning courses at BITS. I interned at EY working on chatbots for analytics. I'm currently a research engineer at Saama Technologies working on AI based solutions for the healthcare industry", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sadhana Srinivasan (~rotuna)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/differential-privacy-and-adversarial-examples~dNyDb/", - "title": "Differential Privacy and Adversarial Examples" - }, - { - "Content URLs": " https://speakerdeck.com/anandology/deploying-ml-apps-in-minutes https://github.com/rorodata/firefly https://github.com/rorodata/rorolite https://github.com/amitkaps/full-stack-data-science", - "Description": "Often, the most convenient way to deploy a machine model is an API. It allows accessing it from various programming environments and also decouples the development and deployment of the models from its use. However, building an good API is hard. It involves many nitty-gritties and many of them need to repeated everytime an API is built. Also, it is very important to have a client library so that the API can be easily accessed. If you every plan to use it from Javascript directly, then you need to worry about cross-origin-resource-sharing etc. All things add up and building APIs for machine very tedious. In this talk demonstrates how deploying machine learning models an APIs can be made fun by using right programming abstractions. The talk presents the couple of open-source libraries firefly and rorolite created to solve this very problem and also shares the experience of building cloud-based PaaS platform that addresses these issues", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "The participants should have understanding of machine learning models and APIs", - "Section": "Data science", - "Speaker Info": "Anand has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, rorodata , which he recently co-founded. He regularly conducts advanced programming courses through Pipal Academy . He is co-author of web.py, a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive", - "Speaker Links": " https://anandology.com Firefly documentation Rorolite documentation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anand Chitipothu (~anandology)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-as-a-service-how-to-deploy-ml-models-as-apis-without-going-nuts~aOzYe/", - "title": "Machine Learning as a Service: How to deploy ML Models as APIs without going nuts" - }, - { - "Content URLs": "Example of one of our outputs:", - "Description": "Have you ever wondered how snapchat filters work? In this talk we will give you a thorough explanation and demo of the famous face swap filter using OpenCV, dlib and NumPy. Talk Summary: We will do a line-by-line walkthrough of our code to extract facial landmarks of both images using methods like convex hull and delaunay triangulation. We then swap faces of the two input face images and blend them using the seamlessclone method. We will also go through various computer vision concepts required to understand the underlying mathematics. Outcome: After this talk you would be able to learn how to do the above mentioned tasks and some insights into a few OpenCV methods and we will also go over a little bit of numpy basics. Agenda: Introduction and live demo [5 min] Explanation of facial landmark detection methods [5 min] Overview of functions used in our code [5 min] Line by line walkthrough of the code [10 min] Questions from the audience [5 min", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Love for Python, Familiarity with Python3 synta", - "Section": "Others", - "Speaker Info": "Sarvesh Shroff: I am currently a sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. I have won a national level robotics championship held at IIT-R. Miran Junaidi: I am MTH Junaidi, sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. Also gave a lightning talk at PyCon Taiwan 201", - "Speaker Links": "Sarvesh Shroff: GitHub LinkedIn Miran Junaidi: GitHub LinkedI", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sarvesh Shroff (~sarvesh77)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-your-own-snapchat-filter-using-opencv~dPA1e/", - "title": "Creating your own Snapchat filter using OpenCV" - }, - { - "Description": "Monitoring and alerting are essential components of any system. As the number of services grow, monitoring all of them all the time becomes a mammoth task in itself. Hence, there's always a need for having an intelligent system to monitor other systems\u2019 behaviour and notify the appropriate stakeholders when an anomaly occurs.\nHere are some of the things I am going to cover: The need for effective anomaly detection in systems monitoring. System metrics that matter to you - CPU, memory, disk, etc Using StatsD and CollectD for data collection. Building a useful data pipeline Using PySpark for real time data processing Using NumPy and SciPy for business intelligence Implementing anomaly detection algorithms.", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Participants should have some basic knowledge of systems monitoring. Having used tools like New Relic, Grafana would be an added advantage. Basic knowledge of streaming data and Kafka would also be useful", - "Section": "Data science", - "Speaker Info": "I am an Engineer at Grofers. Worn multiple hats throughout my career starting from Full-stack Engineering, to Backend, to Data, and now to Release Engineering. Co-founded crowdsource logistic platform DbyT. Worked as a Programmer Analyst at Virginia based RTS Labs and as a Salesforce Consultant for Richmond based MCIM. Worked with clients from Healthcare, Mission Critical, Datacenter management, Payments industries", - "Speaker Links": "https://medium.com/@sharmaNK/ https://www.linkedin.com/in/nand-kishore-sharma-49902219/ https://github.com/sharmaN", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "nandkishore sharma (~nandkishore)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-system-monitoring-using-pyspark~aQB0b/", - "title": "Real time system monitoring using PySpark" - }, - { - "Content URLs": "I will upload the Slides after the talk", - "Description": "In this talk I want to cover the following topics around Test Automation : Generating python REST API Client with swagger codegen. Automating the python REST API Client generation using swagger spec. Writing automated API Tests/Functional tests (which consume the API\n Client libraries) using pytest as a test runner. Dynamically installing the REST API client and executing the tests\n in the CI pipeline - Jenkins. Invoking the Tests and including them in product\n qualification via the CI Pipeline - Jenkins. ", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Familiarity to REST APIs. Familiar with Test Runner pytest - https://docs.pytest.org/en/latest/ Basics of CI - Jenkins - https://jenkins.io/", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a software test automation engineer and a python lover", - "Speaker Links": "https://linkedin.com/in/hemamalini-rengarajan-55248a", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "HemamaliniRengarajan", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-rest-api-client-generation-and-test-execution-in-ci-pipeline~dRDOa/", - "title": "Automated REST API Client generation and Test execution in CI pipeline" - }, - { - "Description": "SecureDrop is an open-source whistleblower submission system that media organizations can use to securely accept documents from and communicate with anonymous sources. It was originally created by the late Aaron Swartz and is currently managed by Freedom of the Press Foundation. In the modern age of Internet, keeping privacy in the online world has become a bigger battle ground. It became an even bigger challenge for the journalists, lawyers, and anyone else who is dealing with sensitive material. Whistleblowing and leaking have dominated news coverage in recent years. SecureDrop (a Python application) project provides a reasonably safe way for the journalists to receive tips/sensitive materials from anyone, and still safeguarding the sources and keeping the materials secured. SecureDrop also won The Award for Projects of Social Benefit from Free Software Foundation in 2016. This talk will be divided into three sections, why, how and what is in future. Introduction How is SecureDrop working in newsrooms? The top view of the technical stack (Flask application + rest of the stack) Tips for web developers thinking about privacy What are the biggest challenges and threats? What is in future? (SecureDrop workstation project: explaining the new PoC workstation using Python on QubesOS). As a project SecureDrop has many different parts running in different systems. This talk will provide an overview of the technical backgroud of the project, and will try to help the curious minds to go a step ahead to contribute or use the similar ideas in the other applications", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Non", - "Section": "Others", - "Speaker Info": "Kushal Das is a regular speaker in various conferences. He is a CPython core developer and director at The Python Software Foundation.\nHe is currently working on SecureDrop project full time as a staff member of the Freedom of the Press Foundation ", - "Speaker Links": " https://kushaldas.in https://github.com/kushaldas", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kushal Das (~kushal)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/securedrop-the-open-source-whistleblower-submission-system~eVKva/", - "title": "SecureDrop, the Open Source whistleblower submission system" - }, - { - "Content URLs": "The slides accompanying the talk, along with all the examples may be found at RJ722/reducing-dead-code . Other useful links: RJ722/example-vulture displays an example on how we can integrate vulture with CI tests. vulture coala.io ", - "Description": "Maintaining a high level of code quality is important for any serious project. One aspect of this is ensuring that all code is actually used. There are many reasons for dead code ending up in a project. The most common is refactoring, but another is misspellings, which are only detected at runtime for dynamic languages. Finding and removing dead code allows to keep the code base clean and reduces bugs. This talk is focussed on how we can use Vulture to find dead code. It helps you find unused code in Python programs and it is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python's dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused. Nonetheless, Vulture can be a very helpful tool for higher code quality. One part of this talk is to discuss how to automate testing for dead code with Vulture. There are quite a few options available: Adding vulture to your continuous integration testing. A script using the Vulture API for custom tests. Identifying false positives and creating whitelists VultureBear : Integration with coala - a static code analysis tool. This talk is a revised version of a similar talk given at PyCon India 2017 (by the same speaker)", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " python and pip installed Optional requirements: coala coala-bears", - "Section": "Developer tools and Automation", - "Speaker Info": "Rahul Jha He is currently pursuing B.Tech. (ECE) from Zakir Husain College of Engg. & Technology, Aligarh Muslim University. He develops free and open source software. His key contributions in the Vulture community include the vulture API, and the whitelisting scripts . Apart from computers, he likes playing with Robot Cars and editing Wikipedia pages", - "Speaker Links": "You may find more about Rahul here: https://rj722.github.io https://github.com/RJ722 https://twitter.com/rahul722j You may contact him through: e-mail: rahul722j@gmail.com IRC: #vulture on freenode (nick: RJ722)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rahul Jha (~RJ722)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/scavenge-dead-python-bits-with-vulture~bWXQd/", - "title": "Scavenge Dead Python bits with Vulture" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/19inq4BNUi3U74uIBz-nN7gSVOvtC9S4s-FBW0Im1gUg/edit?usp=sharin", - "Description": "Master data is at the heart of an efficient and effective modern business.Master data management (MDM) is the effort made by an organization to create one single master reference source for all critical business data, leading to fewer errors and less redundancy in business processes. The real challenge is the real world data is messy and it's difficult to make a decision out of this data. There are lot of records which can be duplicates or have the same entity references which leads to ambiguity and resource consumption. Entity resolution (ER) is the task of disambiguating records that correspond to real world entities across and within datasets. Problems associated with entity resolution are equally big\u200a\u2014\u200aas the volume and velocity of data grow, inference across networks and semantic relationships between entities becomes increasingly difficult. Data quality issues, schema variations, and idiosyncratic data collection traditions can all complicate these problems even further. When combined, such challenges amount to a substantial barrier to organizations\u2019 ability to fully understand their data, let alone make effective use of predictive analytics to optimize targeting, thresholding, and resource management. Dedupe it's a modern day python library for entity resolution, which works on machine learning algorithms to perform Deduplication and Record Linkage", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic Knowledge of Python and Basics of Machine Learning Classifiers like LR,KNN, DT etc.", - "Section": "Data science", - "Speaker Info": "Vinay is working as a Data Scientist and he loves creating the Data Driven Applications and really love working with the messy data and cleaning it to implement Machine Learning Models to the new age applications. In his leisure time he blogs on Kanoki.org and writes articles on Data Science central.\nHe is an Electrical Engineer from an academic perspective and earned certificate in Data Mining from Indian Statistical Institute and currently pursuing his masters in Statistics. He has delivered talks in the past in PYCON - New Delhi and other conferences Internationally. Beside Data, he is a passionate cyclist and rides 100KM average in a week", - "Speaker Links": "personal Blog: https://kanoki.org/ Pycon-2016: https://www.youtube.com/watch?v=ADjRj6qPF7o&t=29s Selenium Conference 2016: https://www.youtube.com/watch?v=mS3dzczv1ZQ&t=9", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "vinaybabu", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-mdm-entity-resolution-using-dedupe~eZNwe/", - "title": "Demystifying MDM & Entity Resolution using Dedupe" - }, - { - "Content URLs": "Will update soo", - "Description": " playing makes learning fun. And how do you make learning mathematics fun? Obviously playing with mathematical abstractions. Early days people used to play with mathematical objects using pen and paper. But imagine playing with repetitive things using pen and paper. That will make it boring soon, won't it? in this talk I will show you how python can be used to make simple to advanced iterative mathematics fun. Yes you are reading it right. From shuffling of a deck, sequences of numbers, calculus these are few steps of our journey through iterative mathematics using python. I will be using basic python data structures , list comprehensions, and some functional programming aspects to demonstrate this. \n\u200c take aways from this talk - if you are a maths enthusiast , you will understand how to write python code to solve your problem. If you are a programmer you will understand how do you make use of simple python functionality to do recreations in mathematics.", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "School level mathematics and zeal for recreational mathematic", - "Section": "Core python and Standard library", - "Speaker Info": "Vikrant has over 12 years of experience in crafting software solutions. He conducts python trainings through pipal academy. He has worked on diverse areas like Computational Fluid Dynamics, mathematical algorithms for bioinformatics, network-based license servers etc. He has worked at Strand Life Sciences and DRDO. He has a Masters in Computational Science from Indian Institute of Science", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "vikrantpatil", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/adventures-in-iterations~bYNMd/", - "title": "Adventures in iterations" - }, - { - "Description": "You\u2019ve heard a lot about concurrency. Asyncio has been in the standard library for a while, and concurrency is picking up mindshare. Why does the world suddenly care so much about concurrency? How did people write concurrent code before asyncio? Do we still need multithreading, multiprocessing, Gevent, Tornado, etc now that asyncio is here? You\u2019ve also heard about the GIL. Supposedly, it doesn\u2019t let you write parallel programs - so why does Python have it? We\u2019ll also discuss the kinds of problems that can be solved faster with concurrency and the kinds of problems that definitely can\u2019t. Let's answer all these questions and more in this light, demo-driven talk", - "Last Updated": "10 Jul, 2018", - "Section": "Core python and Standard library", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-python-concurrency-story~eX25b/", - "title": "The Python concurrency story" - }, - { - "Description": "We propose to build a deep neural network model that can learn to mimic the handwriting of an individual. Given an input text, the model will learn to synthesize the same but in the form of handwritten text", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Curiosity and willingness to learn something new. :)", - "Section": "Data science", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Deepayan (~Deepayan137)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/teaching-machines-to-write~e1PVd/", - "title": "Teaching machines to write." - }, - { - "Content URLs": "https://github.com/bhoom10 https://www.linkedin.com/in/bhoomika-agarwal", - "Description": "Do you spend too much time manually testing your user interfaces? Automation is the answer. Python and Selenium offer a simple but powerful framework to script any testing. In this talk, I will show you how to use the combination of Selenium WebDriver and Python code to automate web UI tests. Follow along and learn how to locate elements, navigate pages, test user interactions with forms and drag-and-drop elements, and use waits to control test timing and execution. The lessons are practical and can be immediately applied to your development workflow. \nTopics include: What is automated testing? Python-Selenium bindings Parsing the DOM structure Locating elements in the DOM Navigating and interacting with pages Explicit and implicit waits", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Python basics HTML basics", - "Section": "Developer tools and Automation", - "Speaker Info": "Bhoomika Agarwal is a developer associate at SAP Labs India. She works in the field of cloud development, machine learning and open source technologies at SAP Labs. Prior to this, she has worked in Sprinklr and completed her graduation in Computer Science from PES Institute of Technology, Bangalore. She has done research in Big Data, Quantum Computing, Linear Algebra and Brain Computer Interface. She has published research papers and given presentations at numerous conferences about these topics. She has published tutorial courses online on Unacamedy and Lynda to disseminate the knowledge she has acquired over the years with experience", - "Speaker Links": "https://www.lynda.com/Python-tutorials/Python-Automation-Testing/651196-2.html https://unacademy.com/user/bhoomika1", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "bhoom10", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/web-ui-automation-using-selenium~ern4e/", - "title": "Web UI automation using Selenium" - }, - { - "Description": "What is Language Model ? Language Model is basically a way to determines how likely a certain sentence is in the language. \"You are reading my LM write up now \" is more likely to be said than \u201cNow you are my LM reading write up\u201d , even though both sentences contain only correct English words; and the sentence \"I had ice-cream with a\" is more likely to end with \"spoon\" than with \"banana\" . LM helps impart this understanding of a language to machines. What\u2019s the need? \"Computers are incredibly fast, accurate and stupid; humans are incredibly slow, inaccurate and brilliant; together they are powerful beyond imagination.\" (Albert Einstein) Computers don\u2019t understand our language! All they are programmed to understand are very specific instructions. Languages we speak are much more complex than that; you can say one thing in multiple ways, for example \"where do I go for party tonight?\" and \"could you give me name of the best restaurant near me?\" -- this is called language variability. As if this was less burden to translate to computers, sometimes you say something that can have several meanings, like \"Look at the dog with one eye\" -- this is called language ambiguity. A human being usually understands the correct meaning in the context of the conversation. A computer... doesn't really. There are many amazing work already done in the field with Siri autocompleting what you forget to type or Google responding to your \u201cokay Google\u201d calls. This said, there still exists immense room for research in the field of making these models more and more intelligent, be it in disambiguation, intent understanding etc. The basis of all starts from a language model. Types Language model is broadly of two types: Statistical LM: A language model is formalized as a probability distribution over a sequence of strings (words), and traditional methods usually involve making an n-th order Markov assumption and estimating n-gram probabilities via counting and subsequent smoothing (Chen and Goodman 1998). The count-based models are simple to train, but probabilities of rare n-grams can be poorly estimated due to data sparsity (despite smoothing techniques) Neural LM: The use of neural networks in the development of language models has become very popular, to the point that it may now be the preferred approach. The use of neural networks in language modeling is often called Neural Network based Language Models, or NNLM for short.\nNeural network approaches are achieving better results than classical methods both on standalone language models and when models are incorporated into larger models on challenging tasks like speech recognition and machine translation. What does it take to build a language model? A corpus large enough to contain multiple variations possible and a good model :D Sample Use cases Autocorrect Automatic summarization Automated reply to emails Spell Corrector (Grammarly)", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic idea of NLP Concept of tokenization, lemmatization etc. Just a skim through read of n-gram modeling(if possible, else what use will I be of :P) Basic python coding Scikit learn, NLTK libraries of Python", - "Section": "Data science", - "Speaker Info": "Data Scientist with ~4 years of experience. For more info, please pay a visit to my LinkedIn", - "Speaker Links": "https://www.linkedin.com/in/divyachoudhary28", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Divya Choudhary (~divya798)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~bqm0b/", - "title": "Language Model (Text Analysis) using Python from scratch" - }, - { - "Description": "Many people are moving towards machine learning and artificial intelligence in python without even knowing the basics of the language.\nI would like to focus on the point of knowing the core basics of the language including its syntax and basic commands. After knowing the basics can only a person learn other details of the language. I would after explaining the basics like to focus on some standard libraries like numpy, pandas and matplolib and how they help in data visualisation", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Non", - "Section": "Core python and Standard library", - "Speaker Info": "I am Prabhleen Kaur Bindra, currently pursuing a bachelor's degree in computer science and engineering, from government college of engineering, Aurangabad. I moved towards python from the last 2 months as I developed my interest towards artificial intelligence especially machine learning. I am a novice to the python environment and do not know much details of it though. I would like to share my experience of python", - "Speaker Links": "https://www.linkedin.com/in/prabhleen-b-538ba210", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "prabhleen bindra (~prabhleen)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-baiscs-and-some-standard-libraries~eplpe/", - "title": "Python baiscs and some standard libraries" - }, - { - "Content URLs": "https://github.com/Blaze404/Digit_Recognitio", - "Description": "As neural networks, or in general, machine learning, form the crux of almost all the new technologies , its good to know the internal machinery of these algorithms. We will, in this workshop, train a neural network and study its ins and outs, and finally classify hand written digits with any image of choice . First we will get our hands onto numpy and using that matrix calculus . Next will be learning about gradient descent with multiple multidimensional visualizations using matplotlib( not necessary to be acquainted with). Here we will understand why it is best way to find a needle in a very very big haystack, by performing live comparisons with other methods. And that will be all you'll need to kill in this session. The Neural Net : This will start with structure of neural networks and why it is that way . Then forward propagation , and getting our heads over what is multiplied/dotted with with what. \nThen we'll study about different activation functions and cost functions , and where to use which. And finally, back-propagation , conquering the last enemy and minimizing the cost function for Keanu Reeves like precision. In addition to it, we'll differentiate between stochastic, batch and mini-batch gradient descent , and compare their results. At the end of session, we'll test our neural network on digit images of our choice , and further train the network if necessary", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Introductory knowledge of python Basic calculus Basic Matrix operation", - "Section": "Data science", - "Speaker Info": "I'm Mustafa Qazi, a third year Engineering student in Computer Science, from Govt. College of engineering, Aurangabad. I have four to five months of experience in Python and two months now in machine learning. I have a few projects in machine learning and this being one of them. I know somewhat about big-data jargons like map-reduce, Pig and Spark .Ya, I'm not an Ian Goodfellow in machine learning, but I'll be happy share what I have learned uptill now, and learn further with what experience I'll get from this", - "Speaker Links": "Github LinkedI", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Mustafa Qazi (~mustafa65)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/training-and-optimizing-an-artificial-neural-network-for-classification-from-scratch-with-just-numpy~avr0a/", - "title": "Training and optimizing an Artificial Neural Network for classification from scratch with just numpy." - }, - { - "Content URLs": "Presentatio", - "Description": "Today DASH streams are being used industry wide in Live media (Twitch, Facebook Live, Youtube Live) and would be soon incorporated in static media delivery. We would try to go through most of the use cases we as a consumer or developer would need to utilize these or serve our very own livestream. MPEG DASH (Dynamic Adaptive Streaming over HTTP) is an ISO standard employing adaptive bitrate streaming technique which works by breaking the content into a sequence of small HTTP-based file segments. Each segment contains a short interval of playback time of content, served in several bitrates/codecs, where all of this information is enclosed in a XML media presentation description (MPD). Unlike conventional streaming protocols, this works with standard HTTP servers over TCP, and can fully utilize the benefits of HTTP/2 if both client and server supports it. Naturally, most CDN's and servers can serve the dynamic stream as segmented static media files, with one dynamic entry point which delivers the MPD serving the current time. Due to lack of open libraries handling DASH media, we would be building a DASH utility toolkit. It would be carrying out activities of segmenting (generation), re-merging (consumption), and clipping out a specific period of clip, where the on-media tasks are carried out by ffmpeg. Special care will be taken for \"dynamic\" streams which are live streams. We will go through some production code behind https://esl.atx.sx which is specialized facebook streamer, and some challenges that came up serving its 1 million users", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Conventional streaming media basics asyncio Media descriptors - codecs, timestamps", - "Section": "Networking and Security", - "Speaker Info": "Arnav is currently working as a Developer at hedgehog lab , Hyderabad. He has presented technical talks at previous PyCons. He maintains several pet projects, his most recent https://esl.atx.sx serving the esports community. Having spent a decade behind the computer screen, he often gives valuable insight into Web Architecture, Network Infrastructure & Security and Hardware. When he is unable to find the most elegant and practical way to approach a solution, he is often found reading and outputting chunks of python code. He also takes out time and enjoys mentoring peers on good coding practices. Rest of the time he is deeply devoted leading his DotA team", - "Speaker Links": "arnav.at PyCon India 2017 Talk linkedin.com/in/arnav", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "_arnAV", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handling-dash-streams-generation-consumption-clipping~dwv1b/", - "title": "Handling DASH streams - Generation, Consumption & Clipping" - }, - { - "Content URLs": "https://towardsdatascience.com/python-basics-for-data-science-6a6c987f2755 https://towardsdatascience.com/customizing-plots-with-python-matplotlib-bcf02691931f https://towardsdatascience.com/5-quick-and-easy-data-visualizations-in-python-with-code-a2284bae952", - "Description": "Data is a commodity, but without ways to process it, its value is questionable. Data science is a multidisciplinary field whose goal is to extract value from data in all its forms. Machine Learning is a field which is raised out of Artificial Intelligence(AI). It is about extracting knowledge from data and is an integral part of many commercial applications and research projects today, in areas ranging from medical diagnosis and treatment to finding your friends on social networks. My talk will show what data visualisation is, and how it is an essential component for data science. Data visualisation is the key to actionable insights, It allows us to take our complex findings and present them in a way that is informative and engaging to all stakeholders. Also, data visualisation helps us make sense of large amounts of data in quick, easy way in a universal manner. In the end, the consumer of the product of all artificial intelligence or machine learning endeavors will be people. We should ensure results are delivered as actionable, impactful insights to act upon in business and in life. By the time the conference is over, you will have a brief overview of data visualisation and started thinking of how to use data visualisation for your organisation or projects", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic knowledge of python. Knowledge of basic graphical representations like bar graphs, scatter plots etc.", - "Section": "Data science", - "Speaker Info": "Myself Saurabh Sunil Deshmukh, currently pursuing my B.E. (Computer Science and Engineering ) from Government college of Engineering Aurangabad, Maharashtra. I started with python three months before considering its scope and popularity in data science and machine learning. I have also studied Big Data analytics using Apache Spark and Apache Hadoop. I would love to share my (just started) journey into data science also eager to hear from everyone else", - "Speaker Links": "https://github.com/Saurabh2798/Python https://github.com/Saurabh2798/introduction_to_ml_with_pytho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saurabh Deshmukh (~saurabh15)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-machine-learning-and-importance-of-data-visualisation~egN3d/", - "title": "Introduction to machine learning and importance of data visualisation" - }, - { - "Description": "In this era of automation, AI and machine learning have conquered the hearts of Techno enthusiasts.\nAs for this very purpose,\nI would like to focus on training Machine Learning model from scratch . Dividing the session as into 3 groups of which part 2 will be extensively loaded with information. 1: A BIT LOOK-OVER (very precise): Synopsis of Pandas ,numpy,matplotlib,scikit-learn. 2: UNDERSTANDING (crux and to depths) : Understanding Machine Learning ,concepts of training a model ,Theory along with Mathematics ,roles of the above libraries to reach our motive. 3: APPLICATION ( Attention in part 1 and 2 would be enough): Training a model using Linear Regression as well as a model with Logistic Regression", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic Python,basics of mathematics", - "Section": "Data science", - "Speaker Info": "I am Devyani Sudhir Kulkarni ,\nThird year student and \npursuing B.E. from Government College of Engineering Aurangabad ,Maharashtra.\nAs user of Python I am new to Python community and so acquainted to few features of it .\nData science and field of Analysis has always been of my interests, so I managed to gain bit knowledge learning hadoop ,hive ,spark ,pig and currently using python", - "Speaker Links": "https://www.linkedin.com/in/devyani-kulkarni-a63717135", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Devyani_Kulkarni", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/training-machine-learning-model-using-regression~bkNEa/", - "title": "Training Machine Learning model using Regression." - }, - { - "Description": "The Tor network is a group of volunteer-operated servers that allows people to improve their privacy and security on the Internet. Tor's users employ this network by connecting through a series of virtual tunnels rather than making a direct connection, thus allowing both organizations and individuals to share information over public networks without compromising their privacy. Along the same line, Tor is an effective censorship circumvention tool, allowing its users to reach otherwise blocked destinations or content. Tor can also be used as a building block for software developers to create new communication tools with built-in privacy features. It has become even more important as we kept hearing all the different stories about government surveillance and how the big companies are tracking everyone on Internet. In this talk, I will showcase a few ways any Python developer\ncan make use of the Tor Project inside of their code or infrastructure and provide solutions which thinks about the users' privacy from the beginning. Talk outline Introduction to the Tor Project Simple Python example to do HTTP calls using Tor network Using Stem to control the Tor process for your project Deploying any Python (or any otherone) web application and creating Onion service for the same Points to remember Nyx to monitor More upsteam usecases (onionshare, ooni). The audience will get a chance to learn about the various ways they can connect and use the Tor network using Python", - "Last Updated": "10 Jul, 2018", - "Section": "Networking and Security", - "Speaker Info": "Kushal Das is privacy advocate who is also part of the Tor community team and a CPython Core developer. He is working as SecureDrop developer in the Freedom of the Press Foundation ", - "Speaker Links": " https://kushaldas.in Tor community team", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kushal Das (~kushal)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-tor-network-for-python-developers~ejNle/", - "title": "THe Tor Network for Python developers" - }, - { - "Content URLs": "Will update this repository in a few days to include sample notebooks : https://github.com/mohdkashif93/PyCon-Graph-Analysis In the meantime you can checkout these repositories for reference Networkx example notebooks Quickstart using graph-tools", - "Description": "In this short tutorial we will be exploring graph networks from the ones mentioned below and work on analysing it various properties and features which will help us to analyse the various patterns that may exist in a network. We will exploring : Community detection in a network Identifying nodes of influence Graph properties like betweeness, centrality, transitivity, clustering coefficients, etc. and what information do they provide about the graph Path finding in a network ( If time permits, we will try to take an image of a maze and find the shortest path out of the maze, by using CV and networkx) Graph Databases in Python Analyzing graphs based on the no. of cliques, k-cliuqes, etc. Visualizing graphs in 2D and 3D space using Python We will be covering the following libraries in this tutorial Networkx graph-tools Neo4J (Graph Database usingPython) Visualization examples using graph-tools, networkx and plot.ly We will be using the following graph data for our analysis: Game of thrones network Marvel Universe Social Graph StackOverflow tag Data Facebook Ego Networks Bonus : If time permits we will take up a random image of a maze and try finding the path out of it, something similar to this (we will be using scikit-image for skeletonizing and networkx for path finding)", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic knowledge for Python will suffic", - "Section": "Data science", - "Speaker Info": "Hi, I am a Python Developer at Qualcomm, who is super enthusiastic about comics and video games. Sometimes when I get bored I head over to Stackoverflow and solve other people's problems, which is my version of being the friendly neighbourhood spiderman (or Nagraj, since Python translates loosely to Naag or snake in Hindi, so you know... sorry that was a lame reference) :", - "Speaker Links": "Stackoverflow : https://stackoverflow.com/users/story/8160718 Github : https://github.com/mohdkashif93 LinkedIn : https://www.linkedin.com/in/mohdkashif93", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Mohammed Kashif (~mohdkashif93)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/network-analysis-using-python~bmgre/", - "title": "Network analysis using Python" - }, - { - "Content URLs": "Note: This talk is inspired by Armin Ronachar's (creator of Flask & a key-note speaker at this PyCon) blog post and a talk by a fellow Mozilla Tech Speaker - Vigneshwer. Armin Ronacher: A Python and Rust love story Dan Callahan - My Python's a little Rust-y - PyCon 2015 Extending Python with Rust (Samuel Cormier-Iijima) All you need to know about FFI", - "Description": "Python is a great language, we all know that. Although, sometimes Python\ncan be a bit of a slowcoach when it comes to performing certain tasks. That's where developers have\nbeen using C/C++, building extensions and integrating them with Python to speed up processes. However, writing C/C++ extensions with strict deadlines and timelines is a bit difficult and also, these low level languages tend to introduce bugs with respect to memory management, lead to segmentation faults and data races. How often have we all faced the dangling pointer error in C/C++ just because we forgot the de-reference a pointer somewhere? Enter Rust , a modern systems programming language that's much better in terms of memory safety, libraries and owing to it's amazing ownership & borrowing principles - keeps the bugs few. documentation up to date and a whole lot more! Bonus - it's completely a open sourced programming language, supported by Mozilla, the non-profit behind the Firefox browser. Basic outline of the talk Python's performance story and the need for native extensions [ 4-5 minutes ] Problems with C/C++ [ 4-5 minutes ] Rust and its success stories [ 8-10 minutes ] Why is Rust so cool!? [ 10-12 minutes ] Ownership & Borrowing, Garbage Collection, FFI (Foreign Function Interface) - along with code snippets Get started with Rust! - links to community & reach-out [ 2 minutes ] Q/A - [ 2 minutes ] Who is this talk for? Python developers who deal with performance issues on a daily basis The curious folk who want to know what Rust is, and why it's growing steadily C/C++ developers who'd like to check out a new systems level programming language Key takeaways A fresh perspective to improve performance metrics in python projects Preview of Rust code and samples Sample of Rust's FFI to ensure python developers can easily call Rust code Note: This talk is inspired by Armin Ronachar's (creator of Flask & a key-note speaker at this PyCon) blog post and a talk by a fellow Mozilla Tech Speaker, Vigneshwer", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic scripting in Python Coding experience in C / C++", - "Section": "Others", - "Speaker Info": "Abhiram has been a part of the open source world in Bangalore for over 3 years now. As a student volunteer in Bangalore, he started contributing to Mozilla as well as FSMK (Free Software Movement Karnataka). After becoming a Mozilla Rep, he has presented over 40 sessions and workshops on python scripting, web dev, Rust and git version control at various venues all over India. Being an internet activist, he was an integral part of the #SaveTheInternet campaign in India during the fight against net neutrality violations. In 2016, he was invited to Mozilla\u2019s Leadership Summit in Singapore to present a talk on running a successful campus club for ~3 years. Currently, he is a Mozilla Tech Speaker well versed in topics like full stack web development, decentralization, scalable infrastructure set up, open source contribution practices and mentoring web enthusiasts . For the past 2 years, he is working at SAP Labs in Bangalore as a full stack web developer and continues to contribute to Mozilla India on a voluntary basis. Recently, he was invited to record a programming course on Rust by the educational website Lynda.com at Los Angeles, California. The course is titled First Look: Rust went live last week", - "Speaker Links": "Events and speaking engagements Mozillians profile - endorsements Mozilla Reps profile - activities and speaking engagements LinkedIn - professional career GitHub - code base & projects Slides.com Speakerdeck.com - presentations and decks Blogs and social media Personal blog Twitter - @abhi12ravi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Abhiram Ravikumar (~abhiram89)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speed-up-your-python-modules-using-rust~elNrb/", - "title": "Speed up your Python modules using Rust" - }, - { - "Content URLs": "Will Update Shortl", - "Description": "I swear by the Dutch, this is not an ML Workshop * If you are one of the Cool Kids doing Style Transfer , Visual Translation or lurking at arxiv-sanity for what is hot, but wondering how would you take the model beyond Jupyter notebooks? It is my impression that the world of deep learning research is starting to plateau.\nWhat's booming: deploying DL to real-world problems. Fran\u00e7ois Chollet I trod the same path when I started as a founding ML Engineer, over the past two years I have learned that solid engineering is essential for building ML Application at web scale. Productionizing ML model is the last mile journey, the most dreaded and less talked about topic, knowing the right toolchain to automate your build pipeline is essential for APIfiying your ML Models. Typical ML pipeline is accompanied by a big data infrastructure to de-normalize and preprocess the application data to prepare training data, then a microservice to expose the trained model artifact on a runtime component as a service. In this workshop, we will explore the DevOps toolchain to build, train, test, deploy and monitor an ML Model. The focus will be on the toolchain and how to automate the entire process from commit to deployment. To illustrate the whole process we would build a toy recommendation application for an on-demand streaming service provide Pyflix . Application Architecture: Here is the reference Application Architecture for our Pyflix Recommendation Engine. Tentative Agenda Introduction to DevOps Culture Quick Introduction to ML/Big Data tools used in the Application - PySpark, Scikit-Learn (if required) Introduction to Containers and Cloud Infrastructure (Docker and AWS) Introduction to Infrastructure as Code (Terraform and Ansible) Building CI/CD pipeline with Jenkins Building Data Pipeline with Airflow Building RESTful Service with Django Rest Framework Application Architecture Introduction - Pyflix Putting All Together to Build Recommendation Engine", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "The workshop will spin around DevOps tools to build ML Pipeline. We will implement a rudimentary recommendation engine so a basic understanding of ML is enough. We will start with an introduction to DevOps and tools used, however good understanding of DevOps culture will help participants get the most out of the workshop. The edx course on DevOps by Microsoft is a great resource, but not necessary for this workshop. The Demo could be set up either in local with Docker or in the cloud. Basic understanding of Containers Basic understanding of Cloud Infrastructure (AWS) Basic understanding of ML/BigData(PySpark) A little bit of googling on Jenkins and Airflow will help Required Tools For local demo A Linux PC with preferably 8GB Ram, Windows or Mac users needs to perform some additional steps to install Docker. Docker Docker Compose For AWS awscli with configured credentials Terraform", - "Section": "Developer tools and Automation", - "Speaker Info": "By profession, Prabakaran Kumaressha designs algorithms to score complex user interactions, classify use generated contents, derive insights and APIfying them to run at scale. He has been data wrangling for 5+ years, specialized in NLP, uses Jupyter to analyze data that fits his PC memory, PySpark for anything that doesn't, uses Django+DRF to create microservices embracing DevOps culture, mostly on AWS. Occasionally he gives talks at local meetups", - "Speaker Links": "@iPrabakaran Github LinkedI", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Prabakaran Kumaresshan (~prabakaran16)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/devops-for-machine-learning-deploying-ml-models-at-scale~enjEe/", - "title": "DevOps for Machine Learning: Deploying ML Models at Scale" - }, - { - "Description": "Vyper is a recently launched python based smart contract programming language. The talk will focus on the features and benefits of Vyper and compare it to Solidity which is similar to Javascript and will include brief demos comparing smart contract implementations.\nTopics to be covered: Features of Vyper and their comparisons to solidity Design pattern of smart contracts Creating smart contracts : demos in both languages", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic knowledge about Blockchain and the Ethereum ecosystem would be helpful", - "Section": "Others", - "Speaker Info": "The speaker is currently working as a research associate at IIIT Delhi and has worked on the Ethereum blockchain as smart contract developer building decentralised applications and web3js based frontends for these applications", - "Speaker Links": "You can reach me at : https://aerophile.github.io https://twitter.com/shubham0075_", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shubham Gupta (~shubham98)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/vyper-vs-solidity-smart-contracts-in-the-python-ecosystem~bok3b/", - "title": "Vyper vs Solidity: Smart contracts in the Python ecosystem" - }, - { - "Content URLs": "http://slides.com/dascommunity/gnupg-for-developers#", - "Description": "\u201cArguing that you don't care about the right to privacy because you have nothing to hide is no different from saying you don't care about free speech because you have nothing to say.\" -Edward Snowden. One\u2019s data is the extension of the person, the digital self. It should be treated as the part of our body. In the present age of massive digital surveillance, it is very difficult to protect the right to privacy. While the developers code or communicate in the digital sphere, she needs to safeguard the privacy rights of the users and the person she is communicating with, respectively. Encryption makes our life easy by protecting the digital self, whereas it makes life difficult for different surveillance agencies. GnuPG is the most trusted tool on that front. GnuPG is the free software version of the OpenPGP cryptographic software suite. This command line application permits one to encrypt and put the signature on your data and communication. There are Python modules which allow easy access to GnuPG\u2019s key management, encryption and signature functionality from Python programs. In the talk, we will learn how to use the same in your Python application, which will in turn help to protect the privacy of the users for your application. Why does this talk matter in current times? Keeping the users safe, keeping their right to privacy protected is one of the major concern for the modern application developers. Using the GnuPG tool with Python binding makes it easier for the application developers to protect the information. This talk will help new Python programmers to use GnuPG to jumpstart using GnuPG in their application safeguarding the users. This talk will also throw some light on the general usage of the GnuPG for the community at large. \u201cPower of community, which is at the heart of the GPG encryption,\u201d says Thenmozhi Soundararajan the Executive Director of Equality Labs", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic Python knowledg", - "Section": "Networking and Security", - "Speaker Info": "Anwesha Das, an Advocate, a PyLady and a core believer of Free and Open Source Software ideology. She provides consultation regarding legal, policy-making and community-related issues in the Free Software and Open Source Software world. She is the Organiser of PyLadies Pune and also leads the PyLadies efforts in India. Privacy and Freedom in the software space are the two of her very close to heart topics. She maintains her personal blog at https://anweshadas.in/. She currently blogs for PSF", - "Speaker Links": "Blogs at https://anweshadas.in/ Previous talk experiences: Keynote at PyCon UK 2017, [Communities and education - exploring together ] (https://www.youtube.com/watch?v=89Kc9ap0h6o&t=8s) PyCon US 2017, [The trends in choosing licenses in Python ecosystem PyCon 2017] (https://www.youtube.com/watch?v=ikT2i4I2LYY) ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anwesha Sarkar (~anwesha)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gnupg-for-the-python-application-developers~eplNe/", - "title": "GNUPG for the Python Application Developers" - }, - { - "Content URLs": "Content url will be provided after the session in the form of github repo", - "Description": "The human visual system is one of the wonders of the world. The difficulty of visual pattern recognition becomes apparent if you attempt to write a computer program to recognize digits. Neural networks approach the problem in a different way. The idea is to take a large number of handwritten digits, known as training examples, and then develop a system which can learn from those training examples. In other words, the neural network uses the examples to automatically infer rules for recognizing handwritten digits. Furthermore, by increasing the number of training examples, the network can learn more about handwriting, and so improve its accuracy", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic python programming. Certain basic knowledge about neural networks. Curiosity and enthusiasm", - "Section": "Core python and Standard library", - "Speaker Info": "The speaker is Aditya Patil who is pursuing his carrier in Computer Science Engineering at Government Engineering College Aurangabad,Maharashtra.\nHe is a coding enthusiast familiar with python and java and has major interest in Data science especially Spark, also have background knowledge of hadoop ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aditya Patil (~aditya89)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fun-with-visual-pattern-recognition~bqmGb/", - "title": "Fun with visual pattern recognition!" - }, - { - "Description": "tes", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "tes", - "Section": "Data science", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/attention-networks~ernKe/", - "title": "Attention networks." - }, - { - "Content URLs": "https://pypi.org/project/pbr", - "Description": "Python is a great language to get started quickly, it's very easy to learn and it has a huge number of libraries available. One of the biggest challenges I found was how do you package is your code for distribution. Building and packaging is kind of a black box for me when I started with it. How to package your code/library in python and publish to PyPI? What's the difference between wheels and eggs? Do I use setuptools or pbr? What is pbr? Why should I use twine? Should define dependencies in setup.py or requirements? How to push my package in PyPI? History of python packaging. Do I use setuptools or distutils? What is pbr and history or pbr? What is setup.py and what goes in it Features of pbr How to manage versions using pbr ? Demo.", - "Last Updated": "10 Jul, 2018", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-and-shipping-python-packages-with-reasonableness~avrXa/", - "title": "Building and shipping python packages with Reasonableness" - }, - { - "Description": "At Genpact we built product recommendation category engine which helped our client to avoid practical challenges in current product recommendation algorithms as either consumers ignore their recommendations or the sales team sees no value due to familiarity with the customer\u2019s\nrequirements and preferences from past experience.Our system intelligently categorises the recommendation generated by existing recommendations into three types of opportunities, viz. \u2018Default\u2019, \u2018Linked\u2019, and \u2018Hidden\u2019.\u2018Default\u2019 opportunities are generic recommendations that are independent of customer\u2019s past purchases.\u2018Linked\u2019 opportunities are obvious recommendations that are easy to identify from past experience of the\ndomain. \u2018Hidden\u2019 opportunities go beyond the \u2018Default\u2019 and \u2018Linked\u2019 opportunities, which even the sales team may not be aware of", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Python,Recommendation Engine,Market Basket Analysis", - "Section": "Data science", - "Speaker Info": "Ladle Patel has 6+ years of experience with a focus in Machine learning, Big data and Deep Learning", - "Speaker Links": "https://www.linkedin.com/in/ladlepatel", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Ladle Patel (~ladle)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/intelligent-categorization-of-product-recommendations-for-enhanced-customer-experience~dwvMb/", - "title": "INTELLIGENT CATEGORIZATION OF PRODUCT RECOMMENDATIONS FOR ENHANCED CUSTOMER EXPERIENCE" - }, - { - "Description": "The rapid rise of Artificial Intelligence (AI) poses fundamental challenges for the creative industry. Although AI technologies are being adopted at an ever faster pace, Design as an academic discipline has so far failed to provide a convincing answer to the opportunities and challenges of AI. As the number of interfaces between humans and information multiplies, so do the amount of design frameworks that are required to support this technology. When it comes to the Internet of Things (IoT), it\u2019s easy to focus on technological aspects. You can talk about different platforms or discuss which IoT solution might be the best to solve a specific problem. Looking below this layer of technology, it quickly becomes apparent that there are many more aspects that determine the success of the IoT. Not the least of which is the matter of how today\u2019s connected products are designed. Artificial Intelligence (AI), which was designed initially to replace highly repetitive, manual work, has exceeded expectations to complete tasks involving emotional creativity. A limiting factor of IoT is it adds devices and buttons which makes your life more complicated. Now with AI, you\u2019re able to say things like \u2018turn on the lights\u2019 instead of pushing buttons, and it makes life simpler. It is the AI layer of natural language processing that helps IoT improve our lives. In tapping into technology\u2019s potential, it\u2019s important to remember the end user \u2014 us humans. But as more and more experiences are built with ML, it\u2019s clear that UXers still have a lot to learn about how to make users feel in control of the technology, and not the other way round. How do we create experiences that are user friendly and human-centric, while taking advantage of technology? This talk will discuss some of the guidelines focusing on human-centered approach and can be used as reference by any UX designer to help navigate the new terrain of designing ML-driven products. As ML starts to power more and more products and experiences, let\u2019s step up to our responsibility to stay human-centered, find the unique value for people, and make every experience great", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Non", - "Section": "Data science", - "Speaker Info": "I am currently working as an Ecosystem Engagement Manager at Beahead Private Limited. I am an Intel Software Innovator and Organizer for Google Cloud Developer Community, New Delhi. I have been involved in delivering trainings on topics like: Internet of Things, Artificial Intelligence, Machine Learning, Deep Learning, Scratch and App Inventor at various national as well as international platforms. I also execute Google Design Sprints \u2013 a Design Thinking and Agile Development Methodology focused workshop series to improve the UX of applications by focusing on Unified User Experience. In addition to my professional pursuits, I am a volunteer at Headstart Network Foundation, India's largest grass-roots level organization that supports entrepreneurship and start-ups where he helps support and mentor various early stage start-ups and aspiring entrepreneurs. I am also an Oracle Certified Java Professional, Google AdWords Certified Professional and recipient of Google India Challenge Scholarship 2018", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/sidagarwal04/ Article : https://software.intel.com/en-us/blogs/2018/06/03/bringing-artificial-intelligence-to-the-edge Github : https://github.com/sidagarwal04 Mentions : https://medium.com/@jap.jolly/international-womens-day-celebration-gdg-and-wtm-new-delhi-a2067ae44714, https://pydelhi.org/blog/pydelhi-meetup-31-march-2018.html, https://software.intel.com/en-us/blogs/2018/03/19/intel-black-belt-software-developers-intel-software-innovators-intel-studen", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "sidaxy", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-design-of-things-designing-for-ai-iot-conversations-and-the-future~axxqa/", - "title": "The Design of Things: Designing for AI, IoT, Conversations, and The Future" - }, - { - "Description": "Data quality is a common concern. This talk is about common patterns of data quality errors, how these can be automatically detected in Python, and how they can be fixed (automatically where possible", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Prior experience in data sourcing and transformation, no matter how simpl", - "Section": "Data science", - "Speaker Info": "Anand is a co-founder of Gramener, a data science company, and an aspiring data storytelle", - "Speaker Links": "https://YouTube.com/sanand", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anand S (~anand40)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cleaning-data-with-python~azzma/", - "title": "Cleaning data with Python" - }, - { - "Content URLs": "TB", - "Description": "The Problem As technology becomes cheaper and more available, we start taking it for granted. Nowhere is this more true than in\nmachine learning. As machines become cheaper and data becomes more and more voluminous, our approach to specific\nmachine learning problems often, and understandably, becomes haphazard. Since GPUs are much cheaper and more widely\navailable than ever before, we implicitly believe that throwing enough artificial neurons at a problem will eventually\nsolve it. While this by itself may be true, it is not uncommon for ML practitioners to realize - unfortunately only in\nhindsight - that most of the iterations required to build a successful predictive model were unnecessary. Ironically,\nthese 'missteps' are often what lead us to the correct answer. Solving a machine learning problem is like traversing a\nminefield, where the safest path can only be determined by blowing up a significantly large number of mines. You can\nonly figure out the right approach after making a bunch of mistakes. Since there is no general rule for determining a\n'best model', most things in deep learning can only be solved with trial and error. To a large extent, this 'see what\nsticks' approach cannot be avoided. However it can be curbed significantly, with a structured approach to running\nmachine learning experiments. This structured approach is what this talk is about. The Solution The building blocks of neural networks and the science behind them, including that of their efficiency and\ntrainability, are already very well understood [1]. The heuristics required to ascertain reasonable convergence and\npredictive accuracy have also been studied in detail [2]. On a very high level, these best practices are simply a\nresult of studying and understanding the underlying mathematics of neural networks. However, the lack of a structured\napproach prevents us from fully utilizing these best practices. The ideal way of managing machine learning experiments is\nwith a lab journal. Each machine learning experiment can be reasonably characterized by a hypothesis, a procedure and\nfinally drawing inferences from it's results. A well kept journal would help practitioners from repeating mistakes,\nand narrowing down to the right approach. The Tools This talk will introduce a lab journal powered by Python, and optimized for deep learning experiments. It will allow\nusers to log experiments carried out on sklearn estimators and keras models. The journal also behaves like a\nhyperparameter grid manager, which also alerts the user if the user accidentally re-runs the same experiment on the\nsame data with the same parameters. It will have some meta-learning features which allow for an end-to-end approach to\nmachine learning experiments. [1]. Efficient BackProp [2]. Improving Deep Neural Network", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "An understanding of basic neural network optimization techniques", - "Section": "Data science", - "Speaker Info": "I'm a data scientist based in New Delhi, India. I build data-driven products and the tooling around them for a living. My research interests are in signal processing and computational harmonic analysis. I'm obsessed with applications of machine learning in personal productivity and recommendation systems. I blog about these here ", - "Speaker Links": "https://twitter.com/jaidevd https://github.com/jaidevd https://jaidevd.github.i", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Jaidev Deshpande (~jaidev)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-the-scientific-method~dyyPd/", - "title": "Deep Learning with the Scientific Method" - }, - { - "Description": "Hands training for developers ,data scientists ,researchers in deep learning using TensorFlow and Keras. Approach: Instructor led hands-on bootcamp to implement deep learning based applications for Computer Vision and Natural language processing. Topics covered . 1.Deep learning concepts\n a)Neurons\n b)Neural newtork\n c)Activation functions\n d)Back propagation algorithm\n e)Stochastic gradient descent\n f)Adaptive learning\n g)Momentum\n2.Installation and setup of GPU server on aws/gcloud 3.Deep learning for computer vision\n a)Image classification\n b)Object detection\n c)Image segmentation\n4.Deep learning for Natural language processing\n a)Word Embedding\n b)LSTMs Packaging Deep Learning models\n6.Case Studies", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Python,Basics of linear algebra, Basics of calculu", - "Section": "Data science", - "Speaker Info": "Ladle Patel has 6+ years of experience in Machine learning, Big data and Deep Learning", - "Speaker Links": "https://www.linkedin.com/in/ladlepatel", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Ladle Patel (~ladle)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-deep-learning-using-tensorflow-and-keras~aAlPe/", - "title": "Hands on Deep learning using TensorFlow and Keras" - } -] \ No newline at end of file diff --git a/cfp_crawler/proposal/spiders/test.json b/cfp_crawler/proposal/spiders/test.json deleted file mode 100644 index 68ecda0..0000000 --- a/cfp_crawler/proposal/spiders/test.json +++ /dev/null @@ -1,18 +0,0 @@ -{ - "1": { - "speaker_name": " Megha Sharma", - "topic_name" : "Optimizations in Web Development: Journey from a college project to a product using Django", - "date" : "26 Jun, 2018", - "Description" : "There lies a huge gap between a website made as a hobby/college project and that made for professional purposes. The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! My talk is going to be about highlighting the flexibility and power python gives in this case. I'm going to share my experience of building a tool for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/).", - "Prerequisites" : "Basic knowledge of Python, Django, Javascript and querying RDBMS is required.", - "Content URLs" : "Slides will be uploaded soon Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv/", - "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia. Other than coding, I love reading, writing and trying out new things.", - "Speaker Links": ["Blog: https://medium.com/@meghasharma4910", "Github: https://github.com/MeghaSharma21","Outreachy project: https://github.com/MeghaSharma21/WikiCV", "Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018"], - "Section" :"Web development", - "Type" : "Talks", - "Target Audience" :"Beginner", - "Last Updated" : "27 Jun, 2018" - - } - -} \ No newline at end of file From 123d323c6471fd585011b08b0aacbd75f24823a4 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Sun, 22 Jul 2018 12:07:40 +0530 Subject: [PATCH 09/17] made changes as requested by @ananyo2012 --- cfp_crawler/proposal/spiders/crawler.py | 26 ++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/cfp_crawler/proposal/spiders/crawler.py b/cfp_crawler/proposal/spiders/crawler.py index 4610f26..fce8661 100644 --- a/cfp_crawler/proposal/spiders/crawler.py +++ b/cfp_crawler/proposal/spiders/crawler.py @@ -26,26 +26,26 @@ def parseProposal(self, response): created_on = response.xpath("//p[@class='text-muted']/small/b/time/text()").extract()[0].strip() section = response.xpath("//section[@class='col-sm-8 proposal-writeup']/div") - some_dic = {} + proposal = {} for div in section: heading = div.xpath(".//h4[@class='heading']/b/text()").extract()[0] data = self.format_data(div.xpath(".//text()").extract(), heading) data = data[2:-2] - some_dic[heading[:-1]] = data + proposal[heading[:-1]] = data - table = response.xpath("//table/tr") - for col in table: - heading = col.xpath(".//td/small/text()").extract()[0].strip() - data = col.xpath(".//td/text()").extract()[0].strip() - some_dic[heading[:-1]] = data + table_rows = response.xpath("//table/tr") + for row in table_rows: + extra_info_heading = row.xpath(".//td/small/text()").extract()[0].strip() + extra_info_content = row.xpath(".//td/text()").extract()[0].strip() + proposal[extra_info_heading[:-1]] = extra_info_content - some_dic["title"] = title - some_dic["link_to_proposal"] = response.request.url - some_dic["author"] = author - some_dic["created_on"] = created_on - some_dic["Last Updated"] = response.xpath("//time/text()").extract()[0] + proposal["title"] = title + proposal["link_to_proposal"] = response.request.url + proposal["author"] = author + proposal["created_on"] = created_on + proposal["Last Updated"] = response.xpath("//time/text()").extract()[0] - self.proposals.append(some_dic) + self.proposals.append(proposal) def format_data(self, data, head): return " ".join([d.strip() for d in data if d != "" and d!=head ]) From 26632bf08b0e4403af5e18a613777e39e66c2e81 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Sun, 22 Jul 2018 12:09:57 +0530 Subject: [PATCH 10/17] Delete logs.log --- cfp_crawler/logs.log | 2947 ------------------------------------------ 1 file changed, 2947 deletions(-) delete mode 100644 cfp_crawler/logs.log diff --git a/cfp_crawler/logs.log b/cfp_crawler/logs.log deleted file mode 100644 index 106a3f5..0000000 --- a/cfp_crawler/logs.log +++ /dev/null @@ -1,2947 +0,0 @@ -2018-06-27 12:25:46 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:25:46 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:25:46 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:25:46 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:25:46 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:25:46 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:25:46 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:25:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:25:47 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:25:49 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:25:49 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:25:49 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:25:49 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 6, 55, 49, 588705), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52924416, - 'memusage/startup': 52924416, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 6, 55, 46, 910135)} -2018-06-27 12:25:49 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:27:09 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:27:09 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:27:09 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:27:09 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:27:09 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:27:09 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:27:09 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:27:10 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:27:10 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:27:11 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:27:12 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:27:12 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:27:12 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 6, 57, 12, 425249), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52613120, - 'memusage/startup': 52613120, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 6, 57, 9, 832012)} -2018-06-27 12:27:12 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:29:19 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:29:19 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:29:19 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:29:19 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:29:19 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:29:19 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:29:19 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:29:19 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:29:19 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:29:21 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:29:21 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:29:21 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) -Traceback (most recent call last): - File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks - current.result = callback(current.result, *args, **kw) - File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 34, in parseProposal - proposal[index] = some_dic -NameError: global name 'proposal' is not defined -2018-06-27 12:29:21 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:29:21 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 6, 59, 21, 772162), - 'log_count/DEBUG': 5, - 'log_count/ERROR': 1, - 'log_count/INFO': 7, - 'memusage/max': 52531200, - 'memusage/startup': 52531200, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'spider_exceptions/NameError': 1, - 'start_time': datetime.datetime(2018, 6, 27, 6, 59, 19, 112984)} -2018-06-27 12:29:21 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:29:40 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:29:40 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:29:40 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:29:40 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:29:40 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:29:40 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:29:40 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:29:40 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:29:41 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:29:42 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:29:42 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:29:42 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) -Traceback (most recent call last): - File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks - current.result = callback(current.result, *args, **kw) - File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 34, in parseProposal - proposals[index] = some_dic -NameError: global name 'proposals' is not defined -2018-06-27 12:29:42 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:29:42 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 6, 59, 42, 909398), - 'log_count/DEBUG': 5, - 'log_count/ERROR': 1, - 'log_count/INFO': 7, - 'memusage/max': 52936704, - 'memusage/startup': 52936704, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'spider_exceptions/NameError': 1, - 'start_time': datetime.datetime(2018, 6, 27, 6, 59, 40, 371316)} -2018-06-27 12:29:42 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:29:56 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:29:56 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:29:56 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:29:56 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:29:56 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:29:56 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:29:56 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:29:57 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:29:57 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:29:59 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:29:59 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:29:59 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:29:59 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 6, 59, 59, 471957), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52756480, - 'memusage/startup': 52756480, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 6, 59, 56, 844075)} -2018-06-27 12:29:59 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:31:00 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:31:00 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:31:00 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:31:00 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:31:00 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:31:00 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:31:00 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:31:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:31:01 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:31:03 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:31:03 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:31:03 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:31:03 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 1, 3, 782442), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52920320, - 'memusage/startup': 52920320, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 1, 0, 897261)} -2018-06-27 12:31:03 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:32:43 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:32:43 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:32:43 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:32:43 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:32:43 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:32:43 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:32:43 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:32:43 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:32:43 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:32:45 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:32:45 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:32:45 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:32:46 [scrapy.core.engine] DEBUG: Crawled (200) (referer: 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'downloader/response_count': 195, - 'downloader/response_status_count/200': 194, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 2, 52, 969550), - 'log_count/DEBUG': 196, - 'log_count/INFO': 7, - 'memusage/max': 52461568, - 'memusage/startup': 52461568, - 'request_depth_max': 1, - 'response_received_count': 194, - 'scheduler/dequeued': 194, - 'scheduler/dequeued/memory': 194, - 'scheduler/enqueued': 194, - 'scheduler/enqueued/memory': 194, - 'start_time': datetime.datetime(2018, 6, 27, 7, 2, 43, 144637)} -2018-06-27 12:32:52 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:33:45 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:33:45 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:33:45 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:33:45 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:33:45 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 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- 'scheduler/dequeued/memory': 194, - 'scheduler/enqueued': 194, - 'scheduler/enqueued/memory': 194, - 'start_time': datetime.datetime(2018, 6, 27, 7, 4, 51, 422132)} -2018-06-27 12:35:00 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:35:17 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:35:17 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:35:17 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:35:17 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:35:17 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 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datetime.datetime(2018, 6, 27, 7, 5, 27, 905766), - 'log_count/DEBUG': 196, - 'log_count/INFO': 7, - 'memusage/max': 53112832, - 'memusage/startup': 53112832, - 'request_depth_max': 1, - 'response_received_count': 194, - 'scheduler/dequeued': 194, - 'scheduler/dequeued/memory': 194, - 'scheduler/enqueued': 194, - 'scheduler/enqueued/memory': 194, - 'start_time': datetime.datetime(2018, 6, 27, 7, 5, 17, 943679)} -2018-06-27 12:35:27 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:39:23 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:39:23 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:39:23 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:39:23 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:39:23 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:39:23 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:39:23 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:39:23 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:39:23 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:39:25 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:39:25 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:39:25 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:39:25 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 9, 25, 917780), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 53276672, - 'memusage/startup': 53276672, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 9, 23, 163264)} -2018-06-27 12:39:25 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:39:58 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:39:58 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:39:58 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:39:58 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:39:58 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:39:58 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:39:58 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:39:59 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:39:59 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:40:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:40:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:40:01 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:40:01 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 10, 1, 705240), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 53010432, - 'memusage/startup': 53010432, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 9, 58, 989745)} -2018-06-27 12:40:01 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:40:37 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:40:37 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:40:37 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:40:37 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:40:37 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:40:37 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:40:37 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:40:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:40:37 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:40:39 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:40:39 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:40:39 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:40:39 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 10, 39, 785433), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52920320, - 'memusage/startup': 52920320, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 10, 37, 132524)} -2018-06-27 12:40:39 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:41:49 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:41:49 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:41:49 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:41:49 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:41:49 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:41:49 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:41:49 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:41:50 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:41:50 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:41:52 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:41:52 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:41:52 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:41:52 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32130, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 11, 52, 626632), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52723712, - 'memusage/startup': 52723712, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 11, 49, 919731)} -2018-06-27 12:41:52 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:42:37 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:42:37 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:42:37 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:42:37 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:42:37 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:42:37 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:42:37 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:42:38 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:42:38 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:42:40 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:42:40 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:42:40 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) -Traceback (most recent call last): - File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks - current.result = callback(current.result, *args, **kw) - File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 39, in parseProposal - heading = col.xpath(".//tbody/td[@class='text-muted text-right']/small/text()").extract()[0] -IndexError: list index out of range -2018-06-27 12:42:40 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:42:40 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32131, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 12, 40, 576442), - 'log_count/DEBUG': 5, - 'log_count/ERROR': 1, - 'log_count/INFO': 7, - 'memusage/max': 53067776, - 'memusage/startup': 53067776, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'spider_exceptions/IndexError': 1, - 'start_time': datetime.datetime(2018, 6, 27, 7, 12, 37, 989769)} -2018-06-27 12:42:40 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:42:53 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:42:53 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:42:53 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:42:53 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:42:53 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:42:53 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:42:53 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:42:54 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:42:54 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:42:55 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:42:56 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:42:56 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:42:56 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32131, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 12, 56, 291246), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52514816, - 'memusage/startup': 52514816, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 12, 53, 970524)} -2018-06-27 12:42:56 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:43:30 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:43:30 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:43:30 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:43:30 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:43:31 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:43:31 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:43:31 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:43:31 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:43:31 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:43:31 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:43:31 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:43:31 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:43:33 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:43:33 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:43:33 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:43:33 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32131, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 13, 33, 519041), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52486144, - 'memusage/startup': 52486144, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 13, 31, 41207)} -2018-06-27 12:43:33 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:44:10 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:44:10 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:44:10 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:44:10 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:44:10 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:44:10 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:44:10 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:44:11 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:44:11 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:44:12 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:44:13 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:44:13 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:44:13 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32129, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 14, 13, 259668), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52674560, - 'memusage/startup': 52674560, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 14, 10, 957543)} -2018-06-27 12:44:13 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:44:35 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:44:35 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:44:35 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:44:35 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:44:35 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:44:35 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:44:35 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:44:35 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:44:35 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:44:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:44:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:44:37 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) -Traceback (most recent call last): - File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks - current.result = callback(current.result, *args, **kw) - File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 40, in parseProposal - heading = col.xpath(".//tr/td/small/text()").extract() -AttributeError: 'unicode' object has no attribute 'xpath' -2018-06-27 12:44:37 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:44:37 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32129, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 14, 37, 663396), - 'log_count/DEBUG': 5, - 'log_count/ERROR': 1, - 'log_count/INFO': 7, - 'memusage/max': 53157888, - 'memusage/startup': 53157888, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'spider_exceptions/AttributeError': 1, - 'start_time': datetime.datetime(2018, 6, 27, 7, 14, 35, 465093)} -2018-06-27 12:44:37 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:44:51 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:44:51 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:44:51 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:44:51 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:44:51 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:44:51 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:44:51 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:44:51 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:44:51 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:44:53 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:44:53 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:44:53 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:44:53 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32129, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 14, 53, 898515), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52920320, - 'memusage/startup': 52920320, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 14, 51, 342070)} -2018-06-27 12:44:53 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:45:56 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:45:56 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:45:56 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:45:56 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:45:56 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:45:56 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:45:56 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:45:56 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:45:57 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:45:58 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:45:58 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:45:58 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:45:58 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32129, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 15, 58, 910613), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 53002240, - 'memusage/startup': 53002240, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 15, 56, 622123)} -2018-06-27 12:45:58 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:51:26 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:51:26 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:51:26 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:51:26 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:51:26 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:51:26 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:51:26 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:51:26 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:51:26 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:51:28 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:51:28 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:51:29 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:51:29 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 21, 29, 82414), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52928512, - 'memusage/startup': 52928512, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 21, 26, 272238)} -2018-06-27 12:51:29 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:52:12 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:52:12 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:52:12 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:52:12 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:52:12 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:52:12 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:52:12 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:52:12 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:52:13 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:52:14 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:52:14 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:52:14 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:52:14 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 22, 14, 975094), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 53293056, - 'memusage/startup': 53293056, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 22, 12, 613721)} -2018-06-27 12:52:14 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:53:13 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:53:13 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:53:13 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:53:13 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:53:13 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:53:13 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:53:13 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:53:14 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:53:14 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:53:16 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:53:16 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:53:16 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:53:16 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 23, 16, 507293), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52613120, - 'memusage/startup': 52613120, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 23, 13, 861019)} -2018-06-27 12:53:16 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:53:54 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:53:54 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:53:54 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:53:54 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:53:54 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:53:54 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:53:54 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:53:55 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:53:55 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:53:57 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:53:57 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:53:57 [scrapy.core.scraper] ERROR: Spider error processing (referer: https://in.pycon.org/cfp/2018/proposals/) -Traceback (most recent call last): - File "/usr/local/lib/python2.7/dist-packages/twisted/internet/defer.py", line 653, in _runCallbacks - current.result = callback(current.result, *args, **kw) - File "/home/nivesh/Desktop/proposal/proposal/spiders/crawler.py", line 43, in parseProposal - print(last_updated) -NameError: global name 'last_updated' is not defined -2018-06-27 12:53:57 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:53:57 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 23, 57, 573534), - 'log_count/DEBUG': 5, - 'log_count/ERROR': 1, - 'log_count/INFO': 7, - 'memusage/max': 52543488, - 'memusage/startup': 52543488, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'spider_exceptions/NameError': 1, - 'start_time': datetime.datetime(2018, 6, 27, 7, 23, 54, 982346)} -2018-06-27 12:53:57 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:54:14 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:54:14 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:54:14 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:54:15 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:54:15 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:54:15 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:54:15 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:54:15 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:54:15 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:54:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:54:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:54:17 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:54:17 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 24, 17, 709732), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 53067776, - 'memusage/startup': 53067776, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 24, 15, 58725)} -2018-06-27 12:54:17 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:55:18 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:55:18 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:55:18 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:55:18 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:55:18 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:55:18 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:55:18 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:55:18 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:55:19 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:55:20 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:55:20 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:55:21 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:55:21 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 25, 21, 2368), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52969472, - 'memusage/startup': 52969472, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 25, 18, 636989)} -2018-06-27 12:55:21 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:56:16 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:56:16 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:56:16 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:56:16 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:56:16 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:56:16 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:56:16 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:56:16 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:56:17 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:56:18 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:56:18 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:56:18 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:56:18 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 26, 18, 940953), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52805632, - 'memusage/startup': 52805632, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 26, 16, 512313)} -2018-06-27 12:56:18 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:56:33 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:56:33 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:56:33 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:56:34 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:56:34 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:56:34 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:56:34 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:56:34 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:56:34 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:56:35 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:56:36 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:56:36 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:56:36 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32123, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 26, 36, 423425), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52862976, - 'memusage/startup': 52862976, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 26, 34, 66003)} -2018-06-27 12:56:36 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:58:59 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:58:59 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:58:59 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:58:59 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:58:59 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:58:59 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:58:59 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:59:00 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:59:00 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:59:01 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:59:02 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:59:02 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:59:02 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32122, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 29, 2, 301957), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 53014528, - 'memusage/startup': 53014528, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 28, 59, 410614)} -2018-06-27 12:59:02 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 12:59:15 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 12:59:15 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 12:59:15 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 12:59:15 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 12:59:15 [scrapy.core.engine] INFO: Spider opened -2018-06-27 12:59:15 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 12:59:15 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 12:59:15 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:59:15 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 12:59:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 12:59:17 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 12:59:17 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 12:59:17 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32122, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 29, 17, 978718), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52961280, - 'memusage/startup': 52961280, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 29, 15, 266848)} -2018-06-27 12:59:17 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 13:00:35 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 13:00:35 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 13:00:35 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 13:00:35 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 13:00:35 [scrapy.core.engine] INFO: Spider opened -2018-06-27 13:00:35 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 13:00:35 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 13:00:36 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 13:00:36 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 13:00:37 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 13:00:38 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 13:00:38 [scrapy.core.engine] INFO: Closing spider (finished) -2018-06-27 13:00:38 [scrapy.statscollectors] INFO: Dumping Scrapy stats: -{'downloader/request_bytes': 1008, - 'downloader/request_count': 4, - 'downloader/request_method_count/GET': 4, - 'downloader/response_bytes': 32122, - 'downloader/response_count': 4, - 'downloader/response_status_count/200': 3, - 'downloader/response_status_count/301': 1, - 'finish_reason': 'finished', - 'finish_time': datetime.datetime(2018, 6, 27, 7, 30, 38, 251195), - 'log_count/DEBUG': 5, - 'log_count/INFO': 7, - 'memusage/max': 52572160, - 'memusage/startup': 52572160, - 'request_depth_max': 1, - 'response_received_count': 3, - 'scheduler/dequeued': 3, - 'scheduler/dequeued/memory': 3, - 'scheduler/enqueued': 3, - 'scheduler/enqueued/memory': 3, - 'start_time': datetime.datetime(2018, 6, 27, 7, 30, 35, 928535)} -2018-06-27 13:00:38 [scrapy.core.engine] INFO: Spider closed (finished) -2018-06-27 13:03:03 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: proposal) -2018-06-27 13:03:03 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 2.7.14 (default, Sep 23 2017, 22:06:14) - [GCC 7.2.0], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful -2018-06-27 13:03:03 [scrapy.crawler] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'proposal.spiders', 'ROBOTSTXT_OBEY': True, 'SPIDER_MODULES': ['proposal.spiders'], 'LOG_FILE': 'logs.log', 'BOT_NAME': 'proposal'} -2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled extensions: -['scrapy.extensions.memusage.MemoryUsage', - 'scrapy.extensions.logstats.LogStats', - 'scrapy.extensions.telnet.TelnetConsole', - 'scrapy.extensions.corestats.CoreStats'] -2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled downloader middlewares: -['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', - 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', - 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', - 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', - 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', - 'scrapy.downloadermiddlewares.retry.RetryMiddleware', - 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', - 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', - 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', - 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', - 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', - 'scrapy.downloadermiddlewares.stats.DownloaderStats'] -2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled spider middlewares: -['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', - 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', - 'scrapy.spidermiddlewares.referer.RefererMiddleware', - 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', - 'scrapy.spidermiddlewares.depth.DepthMiddleware'] -2018-06-27 13:03:03 [scrapy.middleware] INFO: Enabled item pipelines: -[] -2018-06-27 13:03:03 [scrapy.core.engine] INFO: Spider opened -2018-06-27 13:03:03 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) -2018-06-27 13:03:03 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023 -2018-06-27 13:03:03 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 13:03:03 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to from -2018-06-27 13:03:05 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None) -2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 13:03:06 [scrapy.core.engine] DEBUG: Crawled (200) (referer: https://in.pycon.org/cfp/2018/proposals/) -2018-06-27 13:03:06 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+----------------------------------- 1 file changed, 1 insertion(+), 4895 deletions(-) diff --git a/cfp_crawler/proposals.json b/cfp_crawler/proposals.json index b9ec0a7..66a9d0d 100644 --- a/cfp_crawler/proposals.json +++ b/cfp_crawler/proposals.json @@ -1,4898 +1,4 @@ [ - { - "Content URLs": "Will add slides later. Have added links to papers in my description", - "Description": "Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources. Compression of Neural Networks (NN) has become a highly studied topic in recent years. The main reason for this is the demand for industrial scale usage of NNs such as deploying them on mobile devices, storing them efficiently, transmitting them via band-limited channels and most importantly doing inference at scale. A number of papers have been published in last few years, proposing different approaches to minimize the footprints of neural networks. The aim of my talk will be to summarize recent developments and techniques in this field, by quoting benchmarks, algorithms and results from papers. On a superficial level, there are two basic types of compression are Network Pruning and Quantization. Network Pruning The motive behind network pruning is to selectively nullify or remove some nodes in order to reduce the size of the NN without losing much accuracy. Not only does this reduce the space required to store the model but also reduces the number of computations for sample. A number of papers in the last 2 years have suggested using Bayesian inferences and Variational Dropout , a probabilistic approach to estimating deterministic weights and selectively pruning some of them after sparsifying respective weight matrices. Quantization Conventionally, weights are stored and operations are performed with 32bit floating point numbers but with the rising need for running models on constrained devices, neural networks can be further compressed by either reducing the number of unique weights by clustering or by reducing the number of bits required represent weights , which also adds a regularizing effect, often resulting in higher accuracy than raw models", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Knowledge of Bayes Theorem, Convolution Neural Networks and common Image Classification datasets", - "Section": "Embedded python", - "Speaker Info": "Hello world. I\u2019m Vishal Gupta, a final year CSE undergrad at SSN, Chennai, India. A Python programmer by heart and ML enthusiast by inspiration, I have worked on a number of different projects, some out of boredom and some for startups. This summer I had to chance to work at Microsoft Research India (Bangalore), on using Bayesian Compression on Object Detection Networks (tiny-yolo) and deploying it on an FPGA board. I was working with a team from IIITD guided by Prof. Saket Anand. I'm also participating in Google Summer of Code 2018 under Debian. Past Experience : Chatbot intern at GoBumpr, Chennai CV intern at XR Labs, Chennai NLP intern at BicycleAI, Banglore", - "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vishal Gupta (~vishal11)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/compression-of-neural-networks~dBmNb/", - "title": "Compression of Neural Networks" - }, - { - "Content URLs": " Winning Solution for Analytics Vidhya Hiring Hackathon Winning Solution for TechGig Machine Learning Hackathon Feature Engineering by Kaggle Expert Organization for learning competitive data science solutions - MLByte ", - "Description": "With advancements in machine learning and artificial neural networks, the answers to previously unknown questions are surfaced. It is the data and the feature engineering aspect that makes this development a great hype of the 21st century. Albeit the algorithm being super complex and extraordinary at solving a task there is always need of feature engineering and crunching the numbers right that help models and neural networks understand the trend and classes better. This proposal shall cover the feature engineering for competitive machine learning problems that are used at platforms like Kaggle, Analytics Vidhya, and HackerEarth. Additionally, this will cover a case study of a winning solution and the inferences from the competitions", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Python Pandas Scikit-learn", - "Section": "Data science", - "Speaker Info": "Mohammad Shahebaz is a data scientist intern at Analytics Vidhya. He is also India's finalist in Microsoft World Championship 2013, the finalist at Master Orator Champion 2016, and has bagged a regional gold medal in International Maths Olympiad (IMO). Currently pursuing out the latest trends in Machine Learning and Artificial Intelligence while winning a competitive position at National level competitions and on Kaggle platform. He loves open-source and have contributed to organizations like Google Web Fundamentals, Scikit Learn, FOSSASIA and is serving as Social Committee Lead at Oppia.org in Google Summer of Code. On a path to set machine learning and artificial intelligence to Indian masses, he open-sources his code and approaches at GitHub and organization MLBYTE", - "Speaker Links": " LinkedIn Profile GitHub Profile - shaz13 Rank 2 at Analytics Vidhya overall leaderboard Mentions Master Orator Champion 1st runner-up of TechGig Machine Learning Hackathon - June 8, 2018", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Mohammad Shahebaz (~shaz13)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/feature-engineering-for-kaggle-and-machine-learning-competitions~e0Pye/", - "title": "Feature Engineering for Kaggle and Machine Learning Competitions" - }, - { - "Description": "draf", - "Last Updated": "10 Jul, 2018", - "Section": "Core python and Standard library", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/repurposing-yolo-for-detecting-country-stamps~e72yd/", - "title": "repurposing yolo for detecting country stamps ." - }, - { - "Description": "IBM came up with PowerAI Vision to grab its share - out of available AI Vision 1.2$ billion market opportunity.\nPowerAI Vision Minimum Viable Product (Vision 1.1.0) was GA'ed on May 25th, which can run on standalone Linux and Ubuntu OS, on Nimbix cloud and can also run on IBM Cloud Private. This was an important achievement for IBM as it is expected to accelerate IBM latest Power processor P9 revenue.\nIBM PowerAI Vision is a video and image analysis platform that is built for IBM Power Systems servers, which includes tools and interfaces for anyone with limited skills in deep learning technologies. One can use PowerAI Vision to easily label images and videos that can be used to train and validate a model and perform image / video inferencing. The first regular PowerAI Vision release was MVP. Vision MVP is composed of different Docker images maintained and managed by Kubernetes", - "Last Updated": "10 Jul, 2018", - "Section": "Data science", - "Speaker Info": "Durgarao Simhadri, Sourav Biswas, Madhuri Katragadda - All are working for IBM PowerAI Vision Project in IBM Hyderaba", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sourav Biswas (~sourav31)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/ibm-powerai-vision~b2Q1a/", - "title": "IBM PowerAI Vision" - }, - { - "Content URLs": "https://github.com/Imaginea/i-tagge", - "Description": "This talk focuses on below two points Software architecture which helps to try different models on different data sets. In the end we will take a real world use case where our architecture helped in speeding up the development process. Bi-Directional LSTM with CRF. ", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Knowledge of Python, ML and DL", - "Section": "Data science", - "Speaker Info": "Anil and Gaurish are part of Data Science team at Pramati technologies. They work on building ML and DL models to solve real world problems", - "Speaker Links": "Anil Kumar - https://www.linkedin.com/in/anil-kumar-reddy-309552ab/ Gaurish - https://www.linkedin.com/in/gaurishthakkar", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anil Kumar Reddy (~anil_kumar46)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-model-for-sequence-tagging~egNGd/", - "title": "Deep Learning model for sequence tagging" - }, - { - "Content URLs": "https://www.jaegertracing.io", - "Description": "Distributed tracing is a technique for monitoring & profiling systems built on microservices architecture. Distributed tracing is quickly becoming a must-have component in the tools that organisations use to monitor their complex, microservice-based architecture. Jaeger is an open source tool and part of CNCF project released and worked by Uber. Outline: Introduction to Microservices\nDistributed Tracing & OpenTracing standards\nUsing Jaeger to monitor microservices-based distributed systems covering: - Distributed context propagation\n - Distributed transaction monitoring\n - Root cases analysis\n - Service dependency analysis\n - Performance / Latency optimization Implementing Tracing with python library live and transforming existing code to traceable code.\nDemo Jaeger with an (python code) example from a monitoring perspective (specific to solve latency issue).\nDemo of tracing to collect application metrics. And more", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Knowledge of Python and application development", - "Section": "Core python and Standard library", - "Speaker Info": "Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "https://www.linkedin.com/in/vivsridh/ https://twitter.com/vivek_sridha", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Vivek Sridhar (~vivek861)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tracing-http-request-latency-using-jaeger-with-python~e3POa/", - "title": "Tracing HTTP request latency using Jaeger with Python" - }, - { - "Description": "draf", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "draf", - "Section": "Core python and Standard library", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mlops-in-draft~e5XKd/", - "title": "MLOps in draft" - }, - { - "Content URLs": "tes", - "Description": "tes", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "tes", - "Section": "Core python and Standard library", - "Speaker Info": "tes", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/ner-in-legalcontracts~b64Ve/", - "title": "NER in legalcontracts" - }, - { - "Content URLs": "https://drive.google.com/file/d/18-0JPLC7d8NduXd00DOk9HzaoJYaXLDd/view?usp=sharin", - "Description": "DevOps is evolving fast with the massive growth that chat-based automation and processes has seen in the recent years. We focus on how to leverage the bot-enabled chat platforms like Slack, MSTeams, Mattermost to your advantage in the context of DevOps using various ChatOps techniques. We also focus on the building and deployment of ChatOps using Python, Django, Docker and Kubernetes. An entire array of DevOps processes such monitoring, CI/CD, analytics can be streamlined through different aspects of ChatOps - bots, cross-application workflows and tying together the internal tools, external tools and microservices in any team's DevOps tool-chain. Productivity, speed and transparency in DevOps can be achieved with the use of ChatOps. Our intention with this workshop would be to focus on the development of ChatOps using Python, Django, Docker and Kubernetes. While several tools are available for developers to build and implement ChatOps for their organization, we believe that the combination of these tools allows for the most versatile, scalable, flexible product. Through our talk, the participants will learn to use these platforms for advanced ChatOps development to automate Dev and DevOps in their teams. We will cover various use cases for all stages of Dev and DevOps cycle. This would give the audience a chance to identify their needs and current state. Next comes the ways these requirements can be tackled through various tools like Python, Django, Docker and Kubernetes(we also cover the advantages and drawbacks of the same). After a well-rounded view of how to implement ChatOps for all kinds of DevOps teams - based on requirements, preferable architecture and choice of language, we end with an interactive Q&A session", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic Python \nDjang", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Ankur, founder and CTO at YellowAnt . I take care of Managing the product architecture, system design and infrastructure design. I have been working on Python for 5 years now. I have intensive knowledge of AWS, Scalling application, Kubernetes, Docker, Databases, etc, and have been conducting developers sessions, meetups and workshops for the same. Prior to founding these companies, I worked with Sasken Communication and IBM India Software labs for 5 years. There, I worked on Perl, C/C++, DB2, XML and other technologies. I have also worked with universities in structuring their Data Mining courses to incorporate real-world use cases, and as a judge for events in TGMC (Organised by IBM) and Engineer (Annual TechFest organised by NITK Surathkal). I have also consulted with Banks, Startups and NGOs for their Tech Stacks", - "Speaker Links": "https://github.com/yellowanthq/\nhttps://twitter.com/YellowAntHQ\nhttps://github.com/ankurrawal\nhttps://twitter.com/ankurrawal1987\nhttps://www.linkedin.com/in/ankur-rawal-53230b13/ https://blog.yellowant.com/6-reasons-why-chatops-make-workplace-better-875659187d0c\nhttps://blog.yellowant.com/how-to-build-a-yellowant-application-in-7-easy-steps-c0feb38c3e5d\nhttps://blog.yellowant.com/advanced-chatops-with-microsoft-teams-part-1-1845acdc11a5\nhttps://blog.yellowant.com/advanced-chatops-with-microsoft-teams-part-2-real-world-use-cases-6470975e574", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ankur Rawal (~ankurrawal)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/accelerating-devops-with-chatops-using-python-django-docker-and-kubernetes~b80gb/", - "title": "Accelerating DevOps with ChatOps using Python, Django, Docker and Kubernetes" - }, - { - "Content URLs": "https://github.com/RushikeshJachak https://github.com/Heisenberg020", - "Description": "Many people are claiming to learn machine learning using standard libraries while not knowing the math behind it. My objective is clear to implement and give a intuition of linear regression model while at the same time telling what steps makes a model good fit for training sets. It includes:- A. Getting comfortable with libraries by actual implementation Introduction to numpy, pandas and matplotlib Exploring data using pandas Exploring relation between various variables using matplotlib. Knowing what are the problems are for a bad model. B.Exploratory Data Analysis :- Classifying features as continuous or categorical. Handling missing data. Feature Extraction and Selection. Correlation and causation. Dummy Variables Visualizing Data C. Implementation of Model Cost function Gradient Descent Normal Equations ", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic knowledge of python like defining function, declaring variables. Knowledge of Matrix Basic Mathematics.", - "Section": "Data science", - "Speaker Info": "I am Rushikesh Jachak, Currently pursuing computer science and engineering in government college of engineering, Aurangabad. I moved towards python from last two months due to my interest in data science field especially machine learning. I am complete novice in python environment, i do not know the hooks and crux of python but i do believe the more you share more you learn.So i would definitely like to share my journey till know and and knowledge of maths and intuition behind the most common algorithm of ML. I also have a bit knowledge of Big-data technologies such as Hadoop hive, and poses a keen interest in field of Data Science", - "Speaker Links": "https://github.com/Heisenberg0203/Kaggle https://github.com/Heisenberg0203/MachineLearning/tree/master/Week1 https://www.linkedin.com/in/rushikesh-jachak-44b723135", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "rushikesh jachak (~rushikesh)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/implementation-of-linear-regression-from-scratch-using-numpy-pandas-and-matplotlib~e9PBd/", - "title": "Implementation of Linear Regression from scratch using numpy, pandas and matplotlib" - }, - { - "Content URLs": " Research paper - Vritthi framework for IT recruitment based on machine learning techniques Slides of other talks can be found on Speakerdeck", - "Description": "Abstract Want to learn how you can use the huge amounts of open data available on social platforms like Twitter, GitHub and StackOverflow to build a profile for a software developer? Yes, it's possible using python's sci-kit library. Mine data, extract features, compute quotients and finally, visualize! Detailed description The talk will start with an overview of data mining and machine learning concepts, during the course of which common misconceptions about data science would be cleared. As a real life example, the problem statement of job-seekers and recruitment is introduced. This then leads to the solution Vritthi , an open source project and then the technical aspects follow. Vritthi uses data mining and machine learning to help job-seekers to understand their skill sets and take up courses that would help them improve their technical expertise. Vritthi can automatically calculate a professional quotient by collating data from websites like GitHub, StackOverFlow and LinkedIn. This analysis is a result of parsing thousands of similar profiles available through the APIs of the above websites. GitHub archive is one of our data sources which actually helps set standards to coding competencies of individual profiles. Collection of data from GitHub using its API is explained in detail, along with the feature-set used to analyze profiles. Once the data is collected from the API, it passes through the data cleaning phase after which a set of features are extracted. These features could be as simple as number of commits, number of projects in a particular programming language, and so on. Right after this, python sci-kit is used to build the data model that\u2019s required for analysis. A supervised learning model is used which consists of two phases - clustering profiles and computing quotient values. Once the data model is ready, computing technical quotient values per programming language or skill is focused upon. For example, \u201cprogramming languages used\u201d is one of the attributes of the feature vector. Finally, the computed quotients are visualized using a web application which uses Python\u2019s Bokeh visualization library. Thus, classic data mining and machine learning have been employed on openly available data to solve a specific problem statement. Who is this talk for? Python developers who\u2019d like to explore sci-kit Web developers who\u2019d like to explore python\u2019s bokeh library for data viz. Entrepreneurs who would like to see how a practical use case is solved using open data What will participants take away? Live example of machine learning and how to adopt python sci-kit library in a ML use case A solid understanding of data science and how it can solve problems in real life Deeper understanding of GitHub\u2019s API for data extraction and mining", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic programming knowledge in any object-oriented language would be helpful", - "Section": "Data science", - "Speaker Info": "Abhiram has been a part of the open source world in Bangalore for over 3 years now. As a student volunteer in Bangalore, he started contributing to Mozilla as well as FSMK (Free Software Movement Karnataka). After becoming a Mozilla Rep, he has presented over 40 sessions and workshops on python scripting, web dev, Rust and git version control at various venues all over India. Being an internet activist, he was an integral part of the #SaveTheInternet campaign in India during the fight against net neutrality violations. In 2016, he was invited to Mozilla\u2019s Leadership Summit in Singapore to present a talk on running a successful campus club for ~3 years. Currently, he is a Mozilla Tech Speaker well versed in topics like full stack web development, decentralization, scalable infrastructure set up, open source contribution practices and mentoring web enthusiasts . For the past 2 years, he is working at SAP Labs in Bangalore as a full stack web developer and continues to contribute to Mozilla India on a voluntary basis. Recently, he was invited to record a programming course on Rust by the educational website Lynda.com at Los Angeles, California. The course is titled First Look: Rust and it went live last week", - "Speaker Links": "Events and speaking engagements Mozillians profile - endorsements Mozilla Reps profile - activities and speaking engagements LinkedIn - professional career GitHub - code base & projects Slides.com Speakerdeck.com - presentations and decks Blogs and social media Personal blog Twitter - @abhi12ravi", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Abhiram Ravikumar (~abhiram89)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/harnessing-open-data-to-build-user-profiles-using-python-sci-kit~ejNPe/", - "title": "Harnessing Open Data to build user profiles using python sci-kit" - }, - { - "Content URLs": "Coming Soo", - "Description": "While majority of the time is spent in differentiating the programmer and designer, this talk aims to use python to mix the two to produce art. Don\u2019t understand read more: Disclaimer! \nYou won\u2019t be taught: What is art or programming. Writing Python syntax How to start loving python How to live life How to make money How to design You will learn about: How to use python to evolve as a designer Eventually, how to appreciate art and art in nature A different perspective towards art Ease your work as a designer and hence be more productive Make visually compelling art with python Generate complex art that would be exhausting to produce with GUI based softwares How to go beyond just making basic geometry shapes in your Computer Graphics class at University Typographic scripting i.e. Python scripting for font design Scripting with python to edit images Python to design layouts This talk is not just about the technology used. Hence, you might start loving python eventually or at least love for it might increase. Mine increased 10-folds, but you aren\u2019t expected for the same. Still, don\u2019t understand? Come to the talk", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Must know python\u2019s basic syntax Have desire to be creative but technical with code Interested in exploring the thin line between chaos and order", - "Section": "Others", - "Speaker Info": "Tanya Jain has been designing and making art for about 10 years now, and plans to start a design studio of her own with the name of Magvaari. She has previously designed for various conferences including PyDelhiConf. She has publically spoken at tech communities like PyDelhi, LinuxChix India. Tanya is currently in 3rd year of her BTech degree at Amity University, Noida and is an active member at the ALiAS tech club. While out in public places, she has a constant thought on how can a place be evolved with design. And hence it also reflects her love for travel! She has a keen interest in learning computer related technologies. Other than designing, Tanya is interested in Data Science and Machine Learning. Yet whatever she learns, she somehow finds the way to join various topics and that is how this talk proposal emerged", - "Speaker Links": " LinkedIn , GitHub://Tanya-Jain Website: tanya-jain.xyz Blog: stellaradventurer.com", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanya Jain (~Tanya-Jain)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-scripting-for-graphic-designers~bkNNa/", - "title": "Python Scripting for Graphic Designers" - }, - { - "Description": "Over the years, machine learning has been on the rise. It is so powerful that it almost tempt us to skip the Exploratory Data Analysis phase. It is not a very good idea to just feed data into a black box and wait for the results.\nExploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods.Pandas is a Python library that provides extensive means for data analysis.In conjunction with Matplotlib, Pandas provides a wide range of opportunities for visual analysis of tabular data", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic knowledge of python", - "Section": "Data science", - "Speaker Info": "I am Purva Chaudhari ,3rd year student of computer science and engineering from Government Engineering College ,Aurangabad.I have a bit knowledge of Big-data technologies such as Hadoop,hive,spark etc.I have started python from last 2 months as I'm interested in Data Analytics and Data Science", - "Speaker Links": "https://www.linkedin.com/in/purva-chaudhari-044007165", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Purva_Chaudhari", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploratory-data-analysis-using-pandas-matplotlib~elNgb/", - "title": "Exploratory Data Analysis using pandas ,matplotlib" - }, - { - "Description": "In this hands-on course using Python, participants will learn how to use Python for various aspects of Data Engineering Participants will work on a real-life scenario of Ingesting data Cleaning & Transforming data Perform Exploratory Data Analysis (EDA) on the dataset As part of this exercise participants will be introduced to various useful Python libraries that every Data Engineer should know. The session will cover various other aspects of a robust, scalable data pipeline", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "This is an intermediate level hands-on course on Python. To benefit from this course the participants are expected to have Basic familiarity with Python programming Conceptual knowledge of data pipelines, relational data and big data Using Jupyter Python notebook environment", - "Section": "Data science", - "Speaker Info": "Arijit Saha Arijit Saha is a data professional with over sixteen years of industry work experience in architecting, designing & developing large-scale data products, platforms & solutions for both big & medium size enterprises. Currently he is busy architecting Enterprise AI data platform & products in one of the fastest growing startup Noodle.ai. He is an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Data Architecture, Big Data Analytics, Geospatial Analytics and application of Artificial Intelligence in Enterprises. Sumit Sen Sumit Sen is a software development professional with more than 15 years of development experience in areas of embedded systems, mobile and virtualization technologies. Currently he is working on the architecture of the AI as a Service offerings of Noodle.ai, an exciting startup in the Enterprise AI space. He is passionate about High Performance Computing, virtualization and IoT systems", - "Speaker Links": "Arijit Saha LinkedIn: https://www.linkedin.com/in/arijitsaha/ Twitter: @arijitsaha Sumit Sen LinkedIn: https://www.linkedin.com/in/sumitsenddn", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "arijit.saha", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-for-data-engineers~bmg9e/", - "title": "Python for Data Engineers" - }, - { - "Content URLs": "Body to body movement transfer using GANs: https://github.com/rahulbaburaj/body2bod", - "Description": "The workshop will be divided into two sessions spent learning about generative modelling. Both sessions will touch upon Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). We will be teaching about the different types of GANs and VAEs and their architectures in general. We will conduct a demo at the end of each session, where we will be generating images of new types of Pokemon. At the end of the sessions, we will be comparing the results from the images that each generative model's AI has produced. It will be interesting to witness the unfolding of new Pokemon, and learn the reasoning behind the output.", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Participants should have a basic understanding about how python works. Also, some basic knowledge on machine learning concepts will be useful", - "Section": "Others", - "Speaker Info": "Lovish, Rahul and Vishnu are all Research Fellows at the Center for Visual Information Technology at International Institute of Information Technology, Hyderabad", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Vishnu Sashank (~vishnu59)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gotta-gan-em-all-pokecon~enjWe/", - "title": "Gotta GAN 'em all! PokeCON!" - }, - { - "Content URLs": " Github Repo : https://github.com/raptor419/uavtalk Slides : http://blueraptortech.com/uavtalk", - "Description": "They might not be delivering our mail ( or Pizzas ) yet , but drones are now intelligent, simple, and reliable enough that they cannot be considered as just toys but as formidable business tools. This talk will briefly go into the inner workings of UAV systems and will demonstrate how python tools can be used to make fully autonomous drones for various purposes. The contents of this talk include: Flight Controllers and control theory ( Ardupilot ) MAVLink ( pymavlink , mavproxy ) Real-time computer vision ( OpenCV , Tensorflow ) DroneKit-Python Obstacles and Implications of IoD We will go extensively into the abilities of DroneKit-Python and into the future of the Internet of Drones using real-life examples such as pest control ( ScAIRcrow ), \ncommercial mapping ( Drone Deploy ) and delivery ( Flirtey ) etc. The talk will end with a small drone taking a picture of all of us, autonomously ofcourse, demonstrating the discussed topics and the formidable ability of autonomous drones", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Python Programming, the concept of APIs and libraries Computer Vision basics The IoT concept An eager mind", - "Section": "Embedded python", - "Speaker Info": "Harsh has been tinkering with technology since he was 9, he received the presidential gold award for National Child Award for Exceptional Achievement by Shree Pranav Mukherjee in 2012. A CS undergrad at IIIT Delhi, he is also the Director of the establishment BlueRaptorTech , which is venturing into the field of big data based algorithmic day trading. A CV Specialist for Aurora , the aerial robotics team of IIIT Delhi, and an AI/ML HackerSpace Intern for Flytbase , a US-based Internet of Drones specialized platform, he has worked extensively and is passionate about drones and has attended many AUV events. His expertise in UAVs lies in making intelligent solutions by the intersection of Computer Vision and Precision Robotics", - "Speaker Links": " LinkedIn GitHub Facebook Website BlueRaptorTech", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harsh Bandhey (~harsh31)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/making-uavs-autonomous-and-the-internet-of-drones~bokBb/", - "title": "Making UAVs autonomous and the Internet of Drones" - }, - { - "Description": "DNS is a non-encrypted protocol. DNS responses which are sent over UDP or TCP lack confidentiality, privacy and security. DNS often contains password files, geolocations, email service and fax numbers, certificate identity and pinning for TLS and much more. Parsing DNS without encryption would lead to different vulnerabilities such as eavesdropping and spoofing. DNS over HTTPS(DoH) is a web protocol that argues for sending DNS requests and receiving DNS responses via HTTPS connections, hence providing query confidentiality. DoH provides more than just privacy \u2013 it also helps guarantee the integrity of the response users receives their requests. Because the DNS response is invisible between responder and user, ISPs and others in the end-to-end network chain can't interfere with the responses. Moreover, Responses from the use of recursive resolvers to clients are the most vulnerable to undesired or malicious changes, because generally recursive resolvers do not encrypt any of your queries. Henceforth, we would be discussing the implementation and parsing of DNS over HTTPS. Further, we provided added support for handling IPv4 and IPv6 DNS packets (A + AAAA records) as well as support for EDNS for edns-client-subnet usage. The integration with HTTP provides a transport suitable for traditional DNS clients seeking access to the DNS. In the end, we will discuss how our client will be sending DNS queries and get DNS responses over HTTP using https:// and implies TLS security integrity and confidentiality. Furthermore, I plan to put some light on how DNSSEC validation is getting involved here with DNS resolution through HTTP to provide ultimate privacy and security support for \n the DNS packets", - "Last Updated": "06 May, 2018", - "Section": "Networking and Security", - "Speaker Info": "I\u2019m currently in my sophomore year, pursuing an undergraduate degree in Computer Science and Engineering from Amrita University. I\u2019m an active member of a FOSS club in our university(FOSS@Amrita). I started actively contributing to various open source organizations from the year 2016. Initially, I started my career in Open Source by contributing to KDE. I was selected for Season of KDE(KDE-SoK) 2016-17 in which I worked on an astronomy software named called Kstars. Further, I was selected for Google Summer of Code 2017 under KDE, where I worked on a project for a libre graphics software, Krita. My work involved introducing a data sharing module in it. The module enables communication between Krita and a remote KDE server in order to help users save and publish their data online. This also required modifying the underlying framework to enable client/server communication. I have been selected for Google Summer of Code for the 2nd time, where I am working on the project Wget2 under GNU organisation. I GSoC project involves adding support for DNS over HTTPS in Wget2. I was invited as a speaker for KDE India Conference 2017 in IIT Guwahati, where I gave a talk on the topic \u201cObject tracking using OpenCV and Qt\u201d. Further, I will be travelling to Austria on August to give a talk in KDE conference, Akademy and will be talking on the topic \"Strengthen Code Review Culture: rm -rf \u2018Toxic Behaviors", - "Speaker Links": "http://anikethfoss.wordpress.com http://gitlab.com/aniketh01/ https://conf.kde.org/en/Akademy2018/public/speakers/1", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Aniketh Girish (~Aniketh01)", - "created_on": "06 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/privacy-concerns-how-dns-resolves-over-https~avLnd/", - "title": "Privacy concerns: How DNS resolves over HTTPS" - }, - { - "Content URLs": " Slides for the talk - DotPython Demo Dotfiles Repository - DotvFiles", - "Description": "Almost all developers spend countless hours on configuring, tweaking and micro-managing their dotfiles with an obsession to exactly have them like one wants them to be. I do too . Dotfiles are just configuration files like .vimrc and .gitconfig on your OS, that stores the settings you have for applications/environments/tools to make life easier while giving you more portability. Well, do you have to use bash scripts for initial setups of your dotfiles? or do you want to setup your dotfiles but don't want to learn or be limited by Bash? Do you forget to update/maintain your dotfiles periodically? Do you struggle with the installation of applications later on? \n Well, Python could be the answer to all of your problems. With Python, one can easily manage , maintain and do a lot more with their dotfiles. My talk would start with a basic intro of what exactly are Dotfiles? and what is the common way of setting them up? This helps beginners who are new to the topic, get interested and a quick recap of why dotfiles are important for all developers. Building up the momentum by visual queues and comparisons through slides, I would show how exactly Python does the same using Homely as Bash does. Later, work through the more intricate details by talking about the features one can implement using Homely and Python highlighting limitations of bash. Like Automation , Logging , git control , debugging , installation of applications and so much more . Summing up by demonstrating a number of scripts that I will be preparing in-advance to showcase the same features that we just talked about. This helps people grasp the talk, the topic, and \" the why we are doing, what we are doing \" part. Ending the talk , with a round of questions and showing the setup I use after months of searching through dotfiles repositories to leave them open to all the options they can choose from for setting up their dotfiles and pick the best setup from the knowledge they just gained. Sub Category : Developer Tool", - "Last Updated": "07 May, 2018", - "Prerequisites": "A laptop computer running any flavor of Linux. It would help if python 3 is already installed. Coming without a laptop is also fine. The presentation would be enough to understand", - "Section": "Others", - "Speaker Info": "I am a student, a Linux enthusiast, loves to code in Python, currently, part of Google Summer of Code 2018 under Sugar Labs, mentoring the GirlScript Summer of Code project, WTF Python and an active volunteer for PyDelhi since 2016 and managing an open-source community in my college, ALiAS . I friviously collect C&H comic strips because I believe everyone should have a hobby and that is mine. I have spoken before at Local User Meetup groups and this would be my first time speaking for PyCon India. When I am free, I devote my time towards closing issues on GitHub and scooping through my Twitter feed. I like to share my thoughts and meet new people. Hence, been writing for a year now, for many organizations such as OpenEBS and TheGeekyWay. Also, I have my own blog, Mixster ", - "Speaker Links": "Professional Profile available @ LinkedIn , Contribute to FOSS projects @ GitHub , Blog @ Mixster I go by vipulgupta2048 all over the web. Feel free to connect/talk with me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vipul Gupta (~vipulgupta2048)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/keeping-your-dotfiles-in-check-with-python~dw7Xd/", - "title": "Keeping your Dotfiles in check with Python" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1DE-_l9N8Scu-M8d_bFxuKQak3TYipEDsGX5HIsB59s0/edit?usp=sharing PS: First Draft, need to organize it better and improve the demos", - "Description": "Dask is a general purpose parallel computing system capable of Celery-like task scheduling, Spark-like big data computing, and Numpy/Pandas/Scikit-learn level complex algorithms, written in Pure Python. Dask has been adopted by the PyData community as a Big Data solution. This talk focuses on the distributed task scheduler that powers Dask when running on a cluster. We will start by comparing Dask with the other solutions that are available for big data ETL and analytics . We will talk about how easily you can parallelize the work loads that you do with your favourite scipy libraries for eg Numpy, Pandas etc. Lastly we will also talk about how you can integrate Dask with your existing code and parallelize it's work load", - "Last Updated": "07 May, 2018", - "Prerequisites": " Good understanding of Python Programming Must have used any scipy library before Nice to have some idea regarding the big data tools available for analytics and ETL", - "Section": "Data science", - "Speaker Info": "I am an enthusiastic developer and aspiring entrepreneur who holds a particular passion for the intersection of web development and emerging technologies. I am constantly exploring innovative ways to solve real world problems and improve existing solutions. I genuinely enjoy working with people, taking risks, and developing new applications. I am currently working at Dubizzle as a Associate Software Engineer. Previously I worked at Corridor Funds as a Technology Architect where I built and Architected a data driven Loan valuation and Portfolio Management tool for retail and institutional lenders. I am open source contributor at Gluster, FOSS Asia, NGUI and GDG. Previously I lead a GDG Chapter in Gujarat. I have also spoken at tech meet ups and conferences like Women techmakers, Google Devfest, Google Cloud Next Extended, Mozilla Gujarat, Local GDGs and Startup Gujarat. In addition to that, I am always experimenting with new and interesting side projects", - "Speaker Links": " Github: http://github.com/smitthakkar96 Linkedin: http://linkedin.com/in/smitthakkar96", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "smit thakkar (~smitthakkar96)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/dask-distributed-data-science-in-a-pythonic-way~axLPa/", - "title": "Dask: Distributed Data Science in a pythonic way" - }, - { - "Content URLs": "https://github.com/rahulbajaj0509/Automation-with-Ansibl", - "Description": "Ansible is software that automates software provisioning, configuration management, and application deployment. Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications\u2014 automate in a language that approaches plain English, using SSH, with no agents to install on remote systems. This workshop introduces a beginner to basic fundamentals of Ansible with easy to do hands-on exercises. The workshop introduces basic use cases of Ansible followed by an introduction to Ansible Inventory, Playbooks, Modules, Variables, Conditionals, Loops and Roles. Each mentioned topic is accompanied by a set of coding exercises giving the attendees a hands-on experience in developing Ansible Playbooks. Introduction to configuration management [15 mins] What is configuration management?\nAgent vs Agent-less\nPush and Pull configurations.\nImperative vs Declarative DevOps Concepts [10 mins] Infrastructure as code.\nDeterministic Builds/Deployments.\nIdempotency.\nCommunications channels \u2013 Message Queueing vs SSH Introduction to Ansible [30 mins] Requirements\nInstallation\nConfiguration Working with Ansible [100 mins] Ansible Inventory\nPlaybooks\nModules\nVariables\nConditionals\nLoops\nRoles\nAnsible Galaxy Ansible in DevOps environment [20 mins]\nQuestions and Answers [10 mins", - "Last Updated": "07 May, 2018", - "Prerequisites": "Pre-Requisites Basic Linux Administrator Skills\nOpen mind and spirit to learn. Software Requirements We will be using two centos7 vagrant machines for the workshop. Make sure you are using a Linux distribution and have vagrant configured with any of the providers like libvirt, virtual box, etc.\nIf you are unable to install vagrant on your Linux systems, then you might want to install Fedora operating system and come for the workshop, we can do the rest together", - "Section": "Developer tools and Automation", - "Speaker Info": "Rahul is an Associate Software Engineer, Red Hat. He is a part of the official foreman organization(https://github.com/rahulbajaj0509). He contributes mostly to the Foreman project and is a \u2018Red Hat Certified Specialist in Configuration Management\u2019. He is also the organizer of Foreman Pune Meetups", - "Speaker Links": "Blog: https://rahulbajaj05.wordpress.com/\nGithub: https://github.com/rahulbajaj050", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Rahul Bajaj (~rahul56)", - "created_on": "07 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automation-with-ansible-beginner-to-advanced~azY2e/", - "title": "Automation with Ansible: beginner to advanced" - }, - { - "Description": "React has been out there for quite some time now and its arguably one of the hottest front end frameworks out there. But MERN architecture hasn't caught up. And that's what I want to teach/discuss in my talk at pycon. How MERN could be the hottest kid on the block in the upcoming days", - "Last Updated": "08 May, 2018", - "Prerequisites": "Javascript\nBeginner level React.\nLittle to no knowledge of Node, Express and Mongo", - "Section": "Web development", - "Speaker Info": "https://himanshuc3.github.io/\nSolving problems bit by bit. After all, computer is just bits. Cracking PJs and living life to not make the most of it but make the most of me", - "Speaker Links": "https://github.com/himanshuc3\nhttps://medium.com/@himan\nhttps://drive.google.com/file/d/1wzhC56jvrriO6XOogapWE2aOMN8Afsiz/view?usp=sharin", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "08 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mern-could-be-the-buzz-word~bDEkd/", - "title": "MERN could be the buzz word" - }, - { - "Content URLs": "Github and presentation will be uploaded shortly", - "Description": "Functional programming is an essential part of any programming language. It allows you to harness the language, performing tasks which can replace tens of lines with just one. This is one programming paradigm which enables the programmer to give more importance to functions than classes. Instead of the traditional approach, we shall solve problems by using functions. A ramp up with Collections and a little bit of Object Oriented concepts in python, Functional Programming can be a great curve to harness python's usability and simplicity. At the end of this session, participants will be able to use the collections library in python, list comprehensions , deal with classes , objects and write anonymous functions , lambda expressions and resolve traditional snippets to reduce , map and filters for each of the use case", - "Last Updated": "09 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college folks", - "Section": "Core python and Standard library", - "Speaker Info": "Currently working as a Software Development Engineer at Olacabs. http://sameera.me https://www.linkedin.com/in/sameera-sy During my freetime I try the below. https://stackoverflow.com/users/4303216/sameera-sy https://www.hackerrank.com/sameerasy https://leetcode.com/sameerasy https://doselect.com/@sameera.sy", - "Speaker Links": "Below are some of my sample works. https://github.com/sam95 I have also conducted a webinar on JS for JavaScript Meetup Bangalore group. https://github.com/sam95/js-for-newbies-3 https://www.youtube.com/watch?v=JXg1GT6zDGQ", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sameeras", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/functional-programming-with-python~eEQle/", - "title": "Functional Programming with Python" - }, - { - "Content URLs": "The work in progress repository of all the associated code - fromscratchtoml . The official website of fromscratchtoml . The work in progress python notebooks . The author's github profile . Sample slides will be uploaded here ", - "Description": "The aim of this workshop is to give a hands on coding experience for writing machine learning / deep learning algorithms from scratch without using external frameworks alongside visualising the model and explaining its predictions using LIME. from-scratch-to-ml The primary goals of this library is - - This framework is intended to be and educational tool to learn deep Learning . - To bridge the gap between the theoretical and coding aspects of machine learning algorithms. - To write intuitive blogs as python notebooks so as to juxtapose theory and code . Explaining the fundamentals of the algorithm from the very basics. - To minimise the use of external dependencies except the fundamental ones like numpy and matplotlib .\n - To make sure that the developed algorithms are coherent with already existing machine learning frameworks. The library is still in a nascent stage but will take shape in a couple of months. Given that the commit frequency is huge. The audience is requested to be patient. LIME (Local Interpretable Model-Agnostic Explanations) - When you are writing a machine algorithm from scratch you want to make sure that your results are coherent and your model is learning the features it is meant to learn. LIME explains why your model behaved the way it did. I will quote excerpts from their blog below - Imagine we want to explain a classifier that predicts how likely it is for the image to contain a tree frog. We take the image on the left and divide it into interpretable components (contiguous superpixels). As illustrated below, we then generate a data set of perturbed instances by turning some of the interpretable components \u201coff\u201d (in this case, making them gray). For each perturbed instance, we get the probability that a tree frog is in the image according to the model. We then learn a simple (linear) model on this data set, which is locally weighted\u2014that is, we care more about making mistakes in perturbed instances that are more similar to the original image. In the end, we present the superpixels with highest positive weights as an explanation, graying out everything else. Even from a human's perspective these explanations do make sense. SOURC", - "Last Updated": "11 May, 2018", - "Prerequisites": "Just a bit of curious dabbling around with some basic machine learning", - "Section": "Data science", - "Speaker Info": "I have graduated from IIT ISM Dhanbad in 2017. Formerly I worked for a London based startup - ALIS labs , currently I am a research fellow at CVIT Lab IIIT Hyderabad alongside being the author of fromscratchtoml . I am also RaRe's incubator program member - the same organization which looks after the reputed topic modelling library gensim . I have given prep talks and mentored dev sprint on the same in Hyderabad Python Meetup group twice", - "Speaker Links": "Author's open source contribution can be seen at his github profile where it all started. Author's current blog where he discussed a 'bit' about the impact of AI. Author's old blog archive where he talked about random developer stuff. Author's another delusional repository which he has trouble explaining to people. Author sometimes also blogs for RaRe technologies . Author is omnipresent on the web by the handle markroxor ", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Mohit Rathore (~markroxor)", - "created_on": "11 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/from-scratch-to-ml-the-machine-learning-library-you-really-understand-and-explaining-its-predictions-with-lime~dJXya/", - "title": "From scratch to ML - The machine learning library you really understand and explaining its predictions with LIME." - }, - { - "Description": "So you started learning python, and you have been able to stitch few lines of code together and it worked, but you do not know why, then this is the talk for you. We will delve into elementary yet obscure concepts that are more often than not skipped by beginners eg why is if _ name_ == _ main_ required in python scripts. et el. In a 3 hour power packed interactive and fully-hands on workshop we shall be learning python from ground up using examples from the real world. Basics of python will be covered with less emphasis on the basics of programming itself. The topics to be covered during the workshop shall include but not be limited to: Hello World Variables Loops and conditionals String Lists, Dictionaries and Tuples. functions File handling classes modules and imports lambda, map and reduce decorators and generators raising and handling exceptions sample exercises for the attendees to work on based on the concepts covered in the first half of the workshop.", - "Last Updated": "12 May, 2018", - "Prerequisites": "The person should be familiar with a *nix based operating system, and the shell should not be alien to them. Attendee should be familiar with the concepts of a hierarchical file system and at least be able to find where their editor saved the file they just created. Knowledge / experience of at least one other programming language will give them an unfair edge", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat, along with his team at https://essentiasoftserv.com consults for python based projects which need help in maintaining, sanitizing and scaling to achieve their true potential.\nHe was one of the four who revamped the https://pydelhi.org community and volunteered for over a dozen https://pythonexpress.com workshops", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/yet-another-introduction-to-python~aKE8d/", - "title": "Yet another introduction to Python" - }, - { - "Content URLs": "", - "Description": "A short and crisp interactive session for the first time attendees of PyCon India to help them navigate through the conference and make the most of the next 4 days. 2011 was my first PyCon and in hindsight was a major turning point in my professional life. The experiences I had, the people I met and the friends I made during the conference are still shaping the choices I make and the decisions I take even today. PS: This will be a heavily opinionated talk and the attendees will be requested to weigh the advice being shared and adapt the ones that suit them the most. The audience will be implored to introspect and answer the following and more for them Which talks to attend? How to decide which talks to attend. Can I walk out of a talk in the middle? Should I attend every talk? What is the hallway track? Should I talk to strangers at the conference? How to start talking to strangers? Can I volunteer now that the conference is already happening? The volunteers are awesome people will they accept my help? How can I help? Should I help the volunteers? What is the dev-sprint? How to make the most of the dev sprint? I just started learning python, will people make fun of me if I speak? i need a job, what should I do? I need to hire, what can I do?", - "Last Updated": "12 May, 2018", - "Prerequisites": "A ticket to the conference, willingness to learn, un-learn and re-learn", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has been a part of PyCon India since 2011 where he found enlightenment and confidence to take charge of his education and steered his career in a direction that feels like success at least to him. These days, along with his team at https://essentiasoftserv.com he consults for companies that need assistance maintaining, scaling, and sanitizing their python based codebase", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-make-the-most-of-pycon-india-2018~dLBva/", - "title": "How to make the most of PyCon India 2018" - }, - { - "Content URLs": "https://github.com/DL4Jets https://docs.google.com/presentation/d/1dDxxsMkfg8vwMi7QDkDaVwCQnxsaXVh9-6xrgrkLvnY/edit?usp=sharin", - "Description": "Ever wondered if you could build your own deep learning framework for hundreds of users? Well, we did build one and turns out it's not as hard as it sounds. With thousands of people working towards democratising artificial intelligence (AI) , we have seen an explosion in the availability of machine learning libraries that make it simpler to build and deploy models for a wide range of tasks. From finance to art, every field has been revolutionised by the introduction of AI. At the European Organisation for Nuclear Research (CERN) we work on understanding the fundamental particles that constitute the universe by performing various experiments in particle physics. Of late, we have experienced a stratospheric rise in deep learning applications to various problems - RNNs, CNNs, and GANs - that have yielded promising results. Like, this stuff is so cool. It works! We delve into the development of one such project as it evolves from a set of scripts into a full-blown framework for supervised learning in high-energy physics. In this talk we will detail the evolution on the DeepJet Framework. It will delieate the development isssues, and how it evolved from a set of scripts hastily patched together to a structured, cross-platform framework built on top of Tensorflow and Keras. The library is a WIP so we're shipping updates on a daily basis with the goal of improving usability with focus on documenting our existing code base. Initially envisaged to support the development of the namesake jet-tagger in the CMS Experiment at CERN, it has grown to encompass multiple purposes within the collaboration. It is aimed at outlining how to go from a set of scripts to building a library that is used by hundreds of scientists in the world's largest physics research collaboration. The presentation will describe the major features the environment sports: simple out-of-memory training with a multi-threaded approach to maximally exploit the hardware acceleration, simple and streamlined I/O to help bookkeeping of the developments, and finally Docker image distribution, to simplify the deployment of the whole ecosystem on multiple datacenters. The talk will also cover future development aimed at improving user experience. ", - "Last Updated": "12 May, 2018", - "Prerequisites": "Preferred: Experience working with virtual environments or Anaconda Knowledge of basic ideas within machine learning such as training, testing, and evaluation of models Basic knowledge of particle physics helpful but not require", - "Section": "Data science", - "Speaker Info": "Swapneel is a computer scientist working at Compact Muon Solenoid (CMS) Experiment at the European Organisation for Nuclear Research where physicists and engineers are probing the fundamental structure of the universe. They use the world's largest and most complex scientific instruments to study the basic constituents of matter \u2013 the fundamental particles. His work at CERN encompasses the creation of a framework that can facilitate the use of deep neural networks and provide a suite of functions to serve multiple use-cases such as jet classification, particle identification, and so on. He is an open-source enthusiast, writing and contributing to various projects in his free time", - "Speaker Links": "Personal Website Github Medium Blog Writing - Open Source for You Magazin", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Swapneel Mehta (~SwapneelM)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-deep-learning-framework-for-high-energy-physics~dN18b/", - "title": "Building a Deep Learning Framework for High-energy Physics" - }, - { - "Content URLs": "https://nim-lang.org http://slides.com/akapatkar/nim-for-python-programmer", - "Description": "Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org As Python programmers, we are used to a language which is expressive, intuitive and versatile. Python is widely lauded for its productivity, minimalistic syntax, standard library feature set and is an inspiration to newer languages like Go, Swift, and Julia. However, there are some areas like speed, distribution, and multicore processing where it lacks a good solution. Nim is a statically typed and high-performance garbage-collected language which builds upon Python\u2019s strengths and addresses someone its weakness in an innovative way. This talk introduces Nim to Python programmers by diving into powerful language design, syntax, data and control structures, static analysis, metaprogramming, portability/distribution and standard library features. At the end of this talk, you should have learned enough to a) get started with Nim on a project b) get familiar with Nim\u2019s growing ecosystem c) leverage/extend existing Python skills on a Nim project. Timeline breakdown: 1) Intro to Nim (10mins) 2) Language tour from Python\u2019s point of view (20 mins) 3) Things you can do with Nim + ecosystem (5 mins) 4) Q&A (5mins", - "Last Updated": "12 May, 2018", - "Section": "Others", - "Speaker Info": "I am a language enthusiast and a Python developer at Netflix. I\u2019ve been learning and using Nim for over a year now and I have benefited immensely from its learnings. There is a strong correlation between Nim and Python and I would like to explain that to the audience and show them a way to think problems using Nim\u2019s construct which I am sure will help them improve their Python skills. I am currently using Nim to write an interpreter for \u2018lox language\u2019. More details here https://github.com/cabhishek/nimlo", - "Speaker Links": "International Conference Talks: PyCon Ukraine 2018 https://2018.uapycon.org/#schedule PyCaribbean 2018 http://pycaribbean.com/schedule.html Python San Sebastian 2017 http://pyss17.pyss.org/", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Abhishek Kapatker (~abhishek69)", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/nim-for-python-programmers~aO9Ed/", - "title": "Nim for Python Programmers" - }, - { - "Content URLs": "https://github.com/bhagvank https://ingeniopythonis.wordpress.co", - "Description": "Video content management, AI, Blockchain and Virtual/Augmented reality technologies are changing the learning management platforms. Customer focused learning systems are emerging in enterprises. Enterprises are structuring their curriculum products to help solve the high value use cases of their customers. Members of the LMS system (python/ Django stack) can tailor their educational experience by choosing courses based on their learning styles. The courses are becoming more effective and helping members retain information. Platforms are differentiating by providing better, faster ways to find relevant content, whenever and wherever learners need it. Modern learning management platform is an end-to-end eLearning solution which has capabilities to create, distribute, edit and manage entire courses from start to finish independent of the content. Educational success and fulfilment are achieved through personalization and optimization of the learner\u2019s path through courses and gaining of competencies. This new class of learning technology vendors is making it possible to augment their systems with cloud-based applications which can be easily integrated with an enterprise-scale technology ecosystem. Enterprises are now tracking and analyzing learning experiences with incredible precision which can be used to improve ongoing program and business outcomes. Tracking and reporting comes in learner-oriented dashboards and reports built for the staff", - "Last Updated": "12 May, 2018", - "Prerequisites": "python, djang", - "Section": "Data science", - "Speaker Info": "Co-Founder of Architect Corner, Bhagvan has around 18 years experience in the industry, ranging from large scale enterprise development to helping incubate software product startups. He has completed a Masters in Industrial Systems Engineering at Georgia Institute of Technology, and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras", - "Speaker Links": "https://www.youtube.com/channel/UChu9J4M85CC7C8hMYp5cgRg/video", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhagvank", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-management-next-generation-platform~dPJ6a/", - "title": "Learning Management : Next Generation Platform" - }, - { - "Content URLs": "For workshop home here and here such as to get sample data, Jupyter notebooks, slides etc For workshop slides pls see her", - "Description": "Geospatial representation are so prevalent in day to day life, such as even in simple travel related conversation to maps, aerial/satellite images etc. In digital era, geospatial data is extensively produced and consumed in ever growing proportion. Python with its free and open source libraries are giving wide variety yet simple and effective set of tools to visualise and analyse geospatial data. The current workshop is directed for beginners of Python programming language, who have basic understanding on computing and data formats. The primary objective of the workshop is to introduce and give hands on training on selected list of FOSS libraries for geospatial analysis. The workshop as a do it yourself fashion tries to solve two real world problems in Geographical Information System (GIS) and its geospatial data sources. The workshop comprised of three components: Component 1 Python environment and work flow setup, an assisted task of setting up the Docker and Jupyter notebook setup. Setting up the Geographical Information System (GIS) environment with extended discussion. Setting up of GIS tools such as FOSS QGIS and Google earth. This component is comprised of four exercises. 1. Introduction to vector data, 2. Introduction to raster data, 3. binary and text file formats of geospatial data, 4. Introduction to tools of GIS, 5. Introduction to literal programming- Jupyter notebook Component 2 Find characteristics of road network(type of road network, length of the type) within a 1X1 km grid. The data source is Open Street Map (OSM) road network data on a city level (60X60km size). This operation is operationally simple such as measure a line feature but computationally intensive as the operation comprised of geometry within operation on dense road network seen in urban setup. Libraries such as Shapely, Fiona, Geopandas and rtree index will be used for the fast processing of this operation. This component comprised of three exercises 1. Find distance between two points 2. Find distance between two points constrained by another vector 3. Find distance between large number of points in for loop Component 3 Find cloud cover percentage over area of interest. The data source is Landsat satellite imagery. Searching cloud free Landsat images over an Area of Interest for a temporal extent of a year or more is manual and time consuming. Applying cloud cover detection algorithm could make this operation automatic. Libraries such as rasterio, Geopandas, Fiona, and libraries related to landsat algorithms will be used for this task. This component comprised of two exercises 1. Convert the imagery in geotiff into numpy arrays 2. Apply the algorithms to find the cloud cover Workshop Plan Introduction and setup- 30 minutes Component 1- 30 minutes Component 2- 45 minutes Component 3- 45 minutes", - "Last Updated": "12 May, 2018", - "Prerequisites": " Laptop 32bit/64 bit Workshop material is tested on 64 bit computer, it is said to be working in 32 bit, lets experiment! A copy of Docker container image from here , file from the link foss-pt-gsa_v3.tar.gz is 2.5 GB in size, will be using this container for DIY Local copy of Docker toolbox from here for windows 64 bit, for 32 bit Windows, follow this link , if any issue, don't worry, we have a session for setting up the docker! Local copy boot2docker.iso from here , we will be following old method of docker toolbox instead of docker native software for Windows.", - "Section": "Data science", - "Speaker Info": "I am a research associate at UrbanEmissions.info . My doctoral study was related to interoperable management of data from air pollution monitors and atmospheric models. I used free and open source libraries of Python for the study, especially on geospatial data compilation, analysis and visualization. Freedom and customization of free and open source languages such as of R and Python were immense. After Conda python package manager came into existence, the world of Python was so easy and I started to use Python for most of computing", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "nishadhka", - "created_on": "12 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/free-and-open-source-libraries-of-python-for-geo-spatial-analysis-and-visualisationmaps-and-satellite-imageries~aQL5e/", - "title": "Free and Open Source libraries of Python for Geo spatial Analysis and Visualisation(Maps and Satellite imageries)" - }, - { - "Description": "Millions of visitors visit business websites every day and each one of them takes different set of steps in order to seek the right information/product. Yet most of them leave disappointed or dejected for some reason and very few get to the right page within the website. In this kind of situation, it becomes difficult to find out if the visitor actually got the information that he was looking for? Also, the individual journeys of these visitors can\u2019t be compared to each other since every visitor has done different set of activities. So, how can we know more about these journeys and compare these visitors to each other?\nSequence Embedding is a powerful way that offers us the flexibility to not only compare any two distinct visitors entire journey in terms of similarity but also to predict the probability of visitor\u2019s conversion. Sequence embeddings essentially helps us to move away from using traditional features to make predictions and considers not only the order of the activities of a user but also the average time spent on each of the unique pages to translate into more robust features and used in Supervised Machine Learning across multiple use cases (next possible action prediction, converted vs non-converted, product classification)\u00a0.Using traditional Machine learning models on the advanced features like sequence embeddings, we can achieve tremendous results in terms of prediction accuracy but the real benefit lies in visualizing all these user journeys and observing how distinct are these paths from the ideal ones. This session will unfold the process creating sequence embeddings for each user\u2019s journey in python and use them to build machine learning classification model to predict visitor conversion along with comparing all the user journeys in terms of similarity score", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic understanding of Machine Learning ,\nPython Basic", - "Section": "Data science", - "Speaker Info": "Co-Founder of DataScienceBridge and currently Sr. Data Scientist at SapientRazorfish core Data Science Team has around 8 years\u2019 experience in the industry, ranging from large scale IT enterprise business development to building complex Machine Learning models by applying state of the art techniques. He has completed his Master\u2019s in Business at Symbiosis International University and certified professional in Machine Learning from IIM-Calcutta.\nHis core expertise involves Machine Learning, Deep Learning, Recommendation Systems using python, spark and Tensorflow for various projects. He is president of Data Science meet up group at SapientRazorfish and conducts multiple webinars on Machine Learning. Along with that he is also a speaker and recently presented a talk at \u201cGreat Indian Developer Summit \u201c(GIDS 2018).\nIn his spare time, he likes to read, code and help aspiring Data Scientists", - "Speaker Links": "https://www.youtube.com/watch?v=Nbpz79v2y5", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pramod Singh (~pramodchahar)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sequence-embeddings-in-python-classification-user-journey-comparison~dRBwd/", - "title": "Sequence Embeddings in Python: Classification & User journey Comparison" - }, - { - "Description": "A lot of budding programmers use print() function or logging module to display the state of the program. However, it soon becomes untenable to reason about the program in a barrage of print statements. At that time, a debugger is a must. Debuggers are a better and structured way to inspect a program. A practical and basic understanding of debuggers will help in locating bugs easily and save developer's time and unnecessary frustration. In this talk, we are going to learn the terminology associated with debugging and explore the most commonly used commands of pdb", - "Last Updated": "14 May, 2018", - "Prerequisites": "Beginner experience and interest towards python programming. Ideal for college students or people who just started programming in Python", - "Section": "Core python and Standard library", - "Speaker Info": "I'm currently a Senior Web Developer and Curriculum Designer at Pesto Tech. I've programmed in Python and Flask since the last 3 years. Open source enthusiast, and frequent blogger", - "Speaker Links": "Medium - https://medium.com/@arfatsalman Twitter - https://twitter.com/salman_arfat GitHub - https://github.com/ArfatSalman LinkedIn - https://www.linkedin.com/in/arfatsalman", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Arfat Salman (~ArfatSalman)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-basics-and-debugging-python-scripts-with-pdb~eVZoe/", - "title": "Debugging basics and debugging python scripts with pdb" - }, - { - "Content URLs": "https://github.com/devxp", - "Description": "My talk is related to my work on ZProc , a library for doing multiprocessing in python Its provides a high-level wrapper over zeroMQ, the distributed messaging library. I will provide a basic introduction to the ways we can natively implement concurrency/parallelism in our applications and how ZProc is a better way to do multi-tasking", - "Last Updated": "14 May, 2018", - "Prerequisites": " A good knowledge of basic python. Some knowledge about the python Process/Thread interface is appreciated If you ever had your hands on the zguide , I have a hunch you'll like this. ", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm 19 year old python programmer, picked up python when I was around 15. My adventures with multi-tasking applications started when I was 17, trying to build a concurrent youtube downloader. I am since, trying to find ways to make writing concurrent, multi-core applications simpler in python", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Dev Aggarwal (~devxpy)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/zproc-process-on-steroids~bWBoa/", - "title": "ZProc - Process on steroids" - }, - { - "Content URLs": "https://atad.xyz\n[ Will share the GitHub repo during the talk with sample web crawlers ", - "Description": "Introducing to Web Scraping. A complete walkthrough the below items: Challenges in scraping websites and parsing the data, Introducing Scrapy, a widely used framework to extract data Dos & Don'ts Usage of Proxies & IP Rotation Crawling hundreds of websites, running and scaling them to huge volumes", - "Last Updated": "14 May, 2018", - "Prerequisites": "Laptop with Ubuntu or a similar OS. \nPython and MySql latest versions Basic understanding of Python and MySql\nGood to have knowledge in writing Xpaths and usage of proxie", - "Section": "Data science", - "Speaker Info": "I am Raja Emmela, \nI Run Headrun Technologies, Bangalore - helping clients in Data Scraping and Web Applications We are in this space for the last seven years, extracting data and parsing them. My experience helps do share the challenges we faced with domestic and NA & APAC clients while scraping websites and the don'ts in particular", - "Speaker Links": " LinkedIn Twitter Blog", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "rajaemmela", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-intro-to-web-scraping-dos-donts-and-the-challenges-in-scaling-it-to-huge-volumes~eXVVb/", - "title": "An intro to Web Scraping, dos & don'ts and the challenges in Scaling it to huge volumes" - }, - { - "Content URLs": "Sensor Fusion Introduction\nhttps://youtu.be/C7JQ7Rpwn2k Sklearn Quick Tutorial\nhttp://scikit-learn.org/stable/tutorial/basic/tutorial.htm", - "Description": "Abstract The primary purpose of this talk to describe how we are using python and Sklearn to model and analyse time series sensor data. In particular, I will walk through how we use Python to process data from an IoT enabled sensor attached to a cricket bat, build machine learning models on the data, and use open source tools to deploy our models in the sensor device as a smart IoT application. Description With the steep increase in the number of smart-things connected to the internet, the amount of data that is being generated by such devices is increasing exponentially. However, much of that data is not useful and therefore filtering unuseful data is an important task. How do we filter the important part and remove the noise from sensor data streams to generate actionable insights? To demonstrate the problem we are placing a sensor device on a cricket bat. The IoT device is a miniaturised, wireless MEMS inertial measurement unit (IMU). The IMU incorporates three-axis sensing of bat acceleration and angular velocity with a low-power Bluetooth to transmit this data to a mobile. First, we gather event-based data rather than storing the entire stream. This again poses the question: how do we define an event? What makes an event unique from the surrounding \u2018non-event\u2019 context? These are some of the questions that need to be answered in order to define an event. Watching a cricket batter stand and prepare to swing, the human brain continuously filters its visual perception and is able to detect and differentiate a swing from the pre- and post-swing activity. We need to be able to automate that same process. Some data instances can be tagged while other can\u2019t be. This helps in training and evaluating machine learning models later. Secondly, After we have extracted time series data based on the instances, we can start analysing these event-based sets of data to understand the language of sensor data. For this, we are using Jupyter Lab to interactively work with data. How does an accelerometer data depict the real world physical motion? This step helps us find the relation between the real world actions and the sensor data set. Well, the extraction process will be prone to noises. The data comes in CSV files, python seems the right choice for us to read and analyse the data. Pandas and offer data frames that come handy to rapidly form and validate hypothesis interactively in Jupyter notebooks. Any analysis is incomplete without visualisation, that's where Matplotlib helps us understand the data better. We quickly test the machine learning models by using Sklearn, which has most of the standard algorithms already implemented. This keynote will describe some of the analysis (along with python code) to show how we have taken several steps right from forming the hypothesis to implementing a solution in the device level layer. All of this demonstrates how Python and its rich set of libraries are helpful in forming solutions to some of the product related features. Thirdly, we need to automate the task of classifying a particular instance from the stream. For this to happen, we can either feed a machine learning model or create a rule-based algorithm which can classify the events into buckets. Now every step has its own set of challenges, firstly the application we are working on involves using motion sensors attached to the back of a cricket bat. There are network constraints in the field. If a sportsperson wants to know real-time analytics from the device, the segregation needs to happen offline. We have to deploy the models on the miniature sensor devices because sometimes the players don\u2019t even carry their mobile phones to the playing area. Therefore our objective is to enable the devices to remain independent in running machine learning algorithms by themselves", - "Last Updated": "14 May, 2018", - "Prerequisites": "Participants should have an understanding of python basics", - "Section": "Data science", - "Speaker Info": "Sanjiv Soni is a data scientist at Str8bat, Bangalore. He currently an international fellow at University of San Francisco for Deep Learning Programme. Sanjiv has experience with Software and product ecosystem. He has interests in building software devised solutions to problems solved by humans", - "Speaker Links": "https://twitter.com/sanjivsoni7 https://www.linkedin.com/in/sanjiv-soni", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "sanjiv soni (~sanjiv)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/swing-and-a-miss-deploying-machine-learning-models-for-iot-enabled-devices-using-python~bYXYa/", - "title": "Swing and a Miss: Deploying machine learning models for IoT enabled devices using Python" - }, - { - "Content URLs": "I will soon share presentation, resources, and code soon on GitHub", - "Description": "Abstract Think of wireless internet, but has the wire somewhere. Serverless architecture still has the server behind :P. What serverless actually means that developer should focus on the code rather than thinking about the servers. As a technique, it removes most of the manel parts of an application, so you can actually spend your day coding. This means that you, developers, can quickly create apps that handle production-ready traffic. You do not have to actively manage scaling for your applications. You do not have to provision the server, or to pay for resources that are unused. The serverless movement started with the release of AWS Lambda, a Function-as-a-Service (FaaS) compute service. But serverless is much more than just FaaS Chatbots have been around for quite a long time. But why this sudden surge and interest in chatbots now? Well, there are various reasons. Unlike the earlier days, many AI and NLP capabilities are now available as consumable services. Also, serverless technologies make chatbots easier to build and scale. The question is, how is the backend served? Would you set up a dedicated server (or a cluster of servers)? That\u2019s costly, painful, and time-consuming! or You will deploy it to Heroku, which will eventually sleep (only happens in the free tier) if no one uses your chatbot. Imagine suddenly, traffic increased your chatbot is used by thousands of people at a time. When Heroku free tier is over, the application crashed or you exceeded memory limit. What would you do now? That\u2019s where serverless technology can help. Benefits of serverless No Administration - We can deploy our code without provisioning anything beforehand, or manage anything afterward. There is no concept of a fleet, an instance, or even an operating system. Scalability - One doesn't have to care about auto-scaling, No need to show alerts or write scripts to scale up and down. With serverless, we can handle quick bursts of traffic. Cost - Function-as-a-service (FaaS) compute and managed services charged based on actual usage rather than pre-provisioned capacity. This means one pay the amount we use, so if we use service for 10 sec then we pay for 10 sec. Faster Development - Now loop between having an idea and deploying to production is shortened because no one need to manage anything after deployment, smaller teams can ship more features. It's easier than ever to make your idea live. Easy Integration With Other Services Going serverless allows a seamless integration to various other cloud services from the same provider. For example, if you are using the AWS platform for chatbots, then you can use DynamoDB for the database, write programming logic as Lambda functions, and expose them through the API Gateway. Session key Takeaways The main question is how to write code which is serverless compliant. This is where this session will help you. This talk will help people to move a step ahead of the traditional way of writing code as some of you had already developed chatbot, I will share how can you can write the simple chatbot in python and can take leverage of serverless to deploy and publish. I will cover Serverless Framework principals AWS Lambda, Amazon Lex and API Gateway How to write a chatbot in python and create a Lambda function How to troubleshoot in a serverless world", - "Last Updated": "14 May, 2018", - "Prerequisites": "Basic knowledge of python and development in general", - "Section": "Others", - "Speaker Info": "Vaibhav Singh is an undergrad final year student of BML Munjal University, Gurugram. He had worked with AWS services as a solution architect intern in Amazon and he is also open source enthusiast and contributed to many open source organization like Fossasia, coala, etc. He is now Google Summer Of Code intern with FOSSASIA. Previously, He was the finalist winner in Codeheat competition. I write mostly in python ;). I had written various small scripts to make my life easier :", - "Speaker Links": "Website GitHub Twitter Facebook Linkedin Mai", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vaibhav Singh (~vaibhavsingh97)", - "created_on": "14 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-serverless-framework-build-a-chatbot~eZXgb/", - "title": "The Serverless Framework - Build a Chatbot" - }, - { - "Content URLs": " Coming soon...", - "Description": "Take it from someone who has introduced an exorbitantly high number of bugs in empty files for most of his life: debugging is hard indeed. But since the dawn of time, developers have been debugging code: there's no escaping that. Software testing, as the elders would tell you, is one of the greatest weapons in your arsenal against those bugs. It's easy to write tests. It helps you write more robust software. And it really helps you sleep at night: and your on-call ops team would love you! But testing is also deeply mystified, unfortunately. Beginners, and sometimes even seasoned developers, generally have a difficult time just to get started: so they eventually miss out on this easy way to attain peace of mind. This talks aims at removing all the mystery around software testing in Python, and give the attendees a head-start into the easiest way of writing tests for their code. As part of being a Python developer for the past 8 years and leading a team of developers building enterprise-grade software for the past 4 years, I've learnt immensely about the important role of software testing in building scalable, durable software; and also a better, pragmatic way of thinking about testing in Python. This talk aims at providing a distilled version of my learning to the audience: both beginners to Python, and seasoned Pythonistas. The talk would broadly cover these topics: A formal way of thinking about software testing / Why you should even bother about writing tests? Writing the simplest of tests in Python / Brief exploration of unittest and pytest Introduction to mocking in Python / In-depth exploration of mock and how to effectively use it for mocking any type of scenario in your code Writing tests for complex applications / working code examples from real life \u2014 This section would contain walkthrough of tests written in a few real-life applications and Python libraries, and a discussion on how to add test coverage for things that might not seem very straightforward to mock in a unit test. A few (opinionated) recommendations about testing Apart from providing to the audience an easy-to-grasp framework of thinking about software testing, this talk aims to teach by examples from real world. Complex and not so straightforward concepts would be explained with code samples and tests from production, so it's easy for the audience to truly grasp them. The talk also features anecdotes from my own experience in building software to give the audience better context", - "Last Updated": "15 May, 2018", - "Prerequisites": "This talk is intended for newcomers to Python (who might never have written a test yet), as well as experienced developers (who might not be writing tests effectively). There are no technical pre-requisites for this talk. The key takeaways would be patterns you can directly start using in writing tests for your own code", - "Section": "Developer tools and Automation", - "Speaker Info": "Sanket ( @sanketsaurav ) is co-founder and Chief of Geeks at DoSelect . He\u2019s 50% developer and 50% designer. He\u2019s been dabbling with computers since the age of 10, and had started his first venture at 18. He loves the Web and likes building cool stuff that matter. His languages of choice are Python, Go and JavaScript, and he\u2019s been building production apps using these for the past two years. He\u2019s also spoken at more than 50 events and hackathons across the country on open source technologies including Python, HTML5 and web applications in general. Sanket also contributes extensively to open-source, with contributions to projects like Django, Celery and Docker, and original Python modules like S3Tree and mimelib ", - "Speaker Links": "Social presence: GitHub Website DoSelect Past talks: Talk at PyCon India 2017 Talk at PyCon Pune 2017 Talk at PyCon India 2013 Django on Steroids -- Slides Lessons from Scale: Django", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sanket Saurav (~sanket)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/debugging-is-hard-testing-is-easy~e17qb/", - "title": "Debugging is hard, testing is easy!" - }, - { - "Content URLs": "https://games.renpy.org/category/rpg https://www.renpy.org", - "Description": "Ren'Py is one of the most versatile and easy-to-use frameworks, written in Python, for the development of Visual Novels and smaller Role-playing games. The talk will explore the details about creating your own development environment for development of visual novels, writing a script and developing GUI, porting your game to Android and iOS and how you can get help for issues in development process. The talk will also explore some of the games which have been developed in Ren'Py like Katawa Shoujo, Doki Doki Literature Club, Imre's Curse: The Prologue etc. The talk will be an interactive one and have a very light and humorous note", - "Last Updated": "15 May, 2018", - "Prerequisites": "No prerequisites required. An open mind and familiarity with Python is all what is needed to attend the talk", - "Section": "Others", - "Speaker Info": "I am currently involved with Lernr Project, a startup based in Ahmedabad and have been working with Python for 3+ years, certified as a\nSoftware Carpentry Instructor and one of the organizers of Django Girls Bangalore. Contributor to Biopython, Galaxy Project, bioconda and conda-forge communities. My interests are in the field of Bioinformatics, High-Performance Computing and am working under Prof. V.K. Jayaraman in the field of Proteomics", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sourav Singh (~sourav)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/make-your-own-visual-novel-in-renpy~b2JAb/", - "title": "Make your own Visual Novel in Ren'Py" - }, - { - "Description": " Understanding Neural Networking using NumPy Implementing CNN using Keras & understanding foundations Using Pretrained models. Transfer training for doing dog breed identification", - "Last Updated": "15 May, 2018", - "Prerequisites": " Python Basics NumPy Machine Learning Basics", - "Section": "Data science", - "Speaker Info": " 10 + Industry Experience. Machine Learning & Deep Learning Trainer/Consultant for more than 20 companies https://www.linkedin.com/in/awantik/ Co-Founder EdYoda & Zekelabs", - "Speaker Links": "https://www.linkedin.com/in/awantik", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Awantik Das (~awantik)", - "created_on": "15 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-using-python-from-scratch-image-classification~b4KJa/", - "title": "Deep Learning using Python from Scratch - Image Classification" - }, - { - "Content URLs": "https://github.com/sdonapar/data_analysis_pytho", - "Description": "Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data. Data Visualisation helps to get hidden insights quickly . Data Visualisation is key for summarising and communicating your insights. This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis and visualisation Following will be covered as part of this session How does data analysis fit in the life cycle of data science project Dealing with numpy arrays - quick overview Reading data using various formats and sources Data scrubbing/cleansing - dealing with missing values, data transformation Introduction to data visualisation and quick overview of libraries available Using visualisation to understand and communicate results Analysing one of the open source data set By the end of the session Audience will have very good understanding of how to apply numpy, pandas to analyse, visualise understand and communicate the results Scrub/Cleanse the data and prepare data set required for machine learning", - "Last Updated": "16 May, 2018", - "Prerequisites": "Hands on exposure with basic python programming language Software requirements: Please install Anaconda ( https://www.anaconda.com/download/) with Python 3.6 Download the git hub repo - https://github.com/sdonapar/data_analysis_pythonwe would be using jupyter notebooks for this worksho", - "Section": "Data science", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company. I have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar linkedin profile - https://www.linkedin.com/in/sasidonaparthi twitter handle - @sdonapa", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-visualisation-using-python~e50Xd/", - "title": "Data Analysis & Visualisation using Python" - }, - { - "Description": "You only look once (YOLO) is a state-of-the-art, real-time object detection algorithm. The model has several advantages over classifier-based systems. It looks at the whole image at test time so its predictions are informed by global context in the image. It also makes predictions with a single network evaluation unlike systems like R-CNN which require thousands for a single image. This makes it extremely very fast. This talk teaches you to develop your own real-time object detection python application to detect and classify objects in images as well as videos in real-time, which you can use in your next self driving car", - "Last Updated": "16 May, 2018", - "Prerequisites": " Knowledge of basic Python and its syntax Idea/Overview of deep learning as a technology", - "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune. I'm currently working in HSBC Technology India, as a software developer. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": " LinkedIn Twitter Recent talk on WebVR", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-object-detection-coz-yolo~b6VNb/", - "title": "Real-time object detection coz YOLO!" - }, - { - "Description": "The human voice is becoming an increasingly important way of interacting with devices, but current state of the art solutions are proprietary and strive for user lock-in. Mozilla\u2019s DeepSpeech and Common Voice projects are there to change this. In contrast to classic STT approaches, DeepSpeech features a modern end-to-end deep learning solution. Based on Baidu's Deep Speech research paper, it trains a model by machine learning techniques. This model directly translates raw audio data into text - without any domain specific code in between. To train systems like DeepSpeech, an extremely large amount of voice data is required. Most of the data used by large companies isn\u2019t available to the majority of people. That's why Mozilla launched Common Voice, a project to help make voice recognition open to everyone", - "Last Updated": "16 May, 2018", - "Section": "Data science", - "Speaker Info": "I am a deep learning enthusiast and have been exploring it since the past year and it has indeed been the first time technology has made me feel so excited ever since I came to know about the internet. Other than that, I am the initiator and organizer of Django Girls Pune, and a Mozilla TechSpeaker. I am also a decent artist, and love to play the piano in my free time", - "Speaker Links": "Mozilla Research machine learning home page: https://research.mozilla.org/machine-learning/ Speaker's LinedIn: https://www.linkedin.com/in/shaguftagurmukhdas/ Speaker's twitter: https://twitter.com/shaguftamethwa", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Shagufta Gurmukhdas (~ShaguftaMethwani)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mozillas-deepspeech-and-common-voice-projects~e7JBd/", - "title": "Mozilla's DeepSpeech and Common Voice projects" - }, - { - "Content URLs": "OpenFaas Docs: https://docs.openfaas.com/ OpenFaas Website: https://www.openfaas.com", - "Description": "OpenFaaS makes Serverless Functions simple with any programming language through the use of Docker containers. The project can be hosted on any cloud, or on your own hardware - even your laptop. Learn how to build Serverless functions with OpenFaaS and Python in this self-paced workshop lead by the community behind the project. Start by deploying OpenFaaS to your laptops with Docker for Mac or Windows and then learn how to build, deploy and invoke serverless functions in Python. Topics will include: Managing dependencies with pip, dealing with API tokens through secure secrets, monitoring functions with Prometheus, invoking functions asynchronously and chaining functions together to create applications. We'll finish by building a custom action for Google Home/Google Assistant for managing slack notifications using Google's DialogFlow and Slack API. The workshop will have the following labs: Prepare for OpenFaas Test things out Introduction to functions Go Deeper with functions HTML for your functions Asynchronous functions Advanced feature - Timeouts Advanced feature - Auto Scaling Advanced feature - Secrets Create a Slack bot using DialogFlow, Slack API and OpenFaaS", - "Last Updated": "16 May, 2018", - "Prerequisites": " Basic knowledge of Docker Functions will be written in Python, so prior programming or scripting experience is preferred. Requirements: We can use - https://labs.play-with-docker.com/ or any VM / box with the latest docker installed", - "Section": "Web development", - "Speaker Info": "Vivek Singh: Currently working as Software Engineer - II at Akamai Technologies. Been an active contributor to OpenFaaS project. Co-organizer and Speaker at OpenFaaS Bangalore meetup group . Loves to code in Python and Golang. Contributes to Open Source projects in free time. Vivek Sridhar: Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "Vivek Singh: Contributions: https://github.com/viveksyngh LinkedIn Profile: https://www.linkedin.com/in/viveksyngh/ Twitter: https://twitter.com/viveksyngh Website: https://www.viveksyngh.info Blog: https://www.viveksyngh.info/blog/ Vivek Sridhar: https://www.linkedin.com/in/vivsridh https://twitter.com/vivek_sridhar https://github.com/vivsridh4 https://hasgeek.tv/rootconf/2018-day-2/1509-distributed-tracing-with-jaeger-at-scale https://hasgeek.tv/rootconf/cloud-sever-management-delhi/1435-auto-remediation-at-scale-using-watchers-vivek-sridha", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Vivek Kumar Singh (~viveksyngh)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-serverless-with-openfaas-and-python~e9Xzd/", - "title": "Hands-On Serverless with OpenFaaS and Python" - }, - { - "Description": "DevOps is gaining momentum and we at Microsoft want our users to have great CI/CD story for any language targeting any platform. In this session, we will be talking about how easy is to get started on Cloud and DevOps for Python developer in this new generation of Microsoft We're going to start from scratch and before we're done we will use Visual Studio Team Services (VSTS) to setup Continuous Delivery for Python Applications on Cloud and demonstrate the DevOps strategy in action. The solution grows up to the most demanding needs of a modern software developers powered by VSTS. Whether you are starting new, bringing your own tool chain or inter-operating with existing tools and assets, you can accelerate your delivery of value with Azure and VSTS", - "Last Updated": "16 May, 2018", - "Prerequisites": "N", - "Section": "Developer tools and Automation", - "Speaker Info": "Alok Agrawal is Product Manager for Microsoft Visual Studio Team Services where he and his team are building next generation cloud based developer tools. He has been with Microsoft for over 7 years. Previously he has worked with Windows Application Compatibility and Azure Application team. Alok has Bachelor's degree in Computer Science and completed his business management from IIM Calcutta", - "Speaker Links": "http://www.imalokagrawal.com https://twitter.com/imalokagrawal https://github.com/imalokagrawa", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Alok Agrawal (~imalokagrawal)", - "created_on": "16 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-plumber-building-deployment-pipeline-in-minutes~e03Nd/", - "title": "Becoming a Plumber: Building deployment pipeline in minutes" - }, - { - "Content URLs": " http://haridas.in https://github.com/haridas", - "Description": "Data-science mainly involves understanding your data and identify suitable models based on the data. Mastering the standard tools like pandas and seaborn will be key to gain insights about ML problems. This tutorial coverers, Basics of pandas and seaborn Different plotting patterns using seaborn for your data. Plotting Single and bivariate distributions, categorical plots with distribution. Understand two variable behaviour using regression plots. One usecase:- How I decided to buy a petrol car instead of diesel car by analysing my fuel spending.", - "Last Updated": "17 May, 2018", - "Prerequisites": "Lapatop with following packages installed. pip install seaborn pand", - "Section": "Data science", - "Speaker Info": "Haridas is a Principal Engineer in Pramati Technologies, part of Labs team. He has 8+ years of experience in multiple domains like, Web development, SOA, ML, Devops. He has been working extensively in different ML use-cases and applying them in real scenarios", - "Speaker Links": " http://haridas.in Twitter @haridas_n", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "haridas n (~haridas)", - "created_on": "17 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/find-patterns-in-your-data-using-seaborn-and-pandas~ejJ4e/", - "title": "Find patterns in your data using Seaborn and Pandas" - }, - { - "Content URLs": "Shall be updated soon", - "Description": "You have got this super awesome REST API served through Django/DRF based project and suddenly these requirements come in: We need to have a local support for Chinese language! In case, you've not written your application with localization and internationalization in mind, then \"Boy! You're in danger! You should better start praying to almighty to give you strength and endurance to support yet another language in your app\". In this talk, we'll see how do we support localization and serve our app in different languages, based on what language the client wants to communicate in. As a backend, we should be language agnostic and allow all clients to communicate with us in one of the languages we support. We'll see how to support translation for static data (using makemessages / compilemessages) and dynamic data, using various third-party services such as django-translations and transifex. Here, static data is translations for all the fields, error messages etc. that the app already has and dynamic data is the custom data input by the user in the app. This would enable you to have your admin panel, as well as RESTful APIs, served in different languages", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic knowledge of Python and Django", - "Section": "Web development", - "Speaker Info": "Why do you want this person to speak? Sanyam is a self-taught programmer with a \"can-do\" attitude who developed his interest in Computer Science and Software Development over the years. He mostly goes by CuriousLearner all over the web and you might run into him at various Python Conferences and local meetups. In his free time he contributes to FOSS. Some of his noticeable contributions are in Gecko Engine from Mozilla and CPython. You can read about his latest hacking CPython and other projects at http://www.SanyamKhurana.com/blog & http://medium.com/@CuriousLearner Highlights : Goes by CuriousLearner all over the web. Bug Triager and contributor to CPython (bugs.python.org) GSoC 2018 Mentor for Debian RGSoC 2016 Mentor Mozilla Reps Mentor and contributor to Mozilla's GeckoEngine, Add-ons ecosystem, and other few projects. Core-organizer for PyCon India 2016 & PyCon India 2017 Volunteer for PyCon India 2015.", - "Speaker Links": "Blog: http://www.SanyamKhurana.com/blog Website: http://www.SanyamKhurana.com Github: https://github.com/CuriousLearne", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sanyam Khurana (~CuriousLearner)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/becoming-a-multilingual-superhero-in-django~bkMve/", - "title": "Becoming a Multilingual SuperHero in Django" - }, - { - "Description": "Sometimes it can be a laborious task for developers to build android apps using Java. Though Java supports Android apps in a powerful way but it also increases the code complexity for a high end app. Now, if you are a python enthusiast and also want to develop Android apps then Kivy comes to your rescue. Kivy is an open source python library for rapid development of cross platform apps. Using the Kv design language and the Kivy framework for Python, you can build amazing interactive multi-touch apps in just a matter of minutes. Kivy framework solves the complexity problem any android developer face while writing complex codes. It also serves the advantage of being cross platform which saves a great amount of time for any app developer. If you love Python, you will also love Kivy", - "Last Updated": "18 May, 2018", - "Prerequisites": "Python Basic Knowledge of Androi", - "Section": "Web development", - "Speaker Info": "The speaker goes by the name amanraj209 all over the web. I've been interested in learning new technologies since high school and I've been developing apps using Python, Javascript, Java, Go since the last 3 years. I've also done some small projects in Machine Learning. Being a developer gives me a great sense of feel to build apps for the users and contribute to the community. It has always been my passion to dive into the technology and contribute to the community something useful", - "Speaker Links": "Github: https://github.com/amanraj209 LinkedIn: https://www.linkedin.com/in/amanraj209 Facebook: https://www.facebook.com/amanraj20", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aman Raj (~amanraj209)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/developing-android-apps-using-kivy~el61b/", - "title": "Developing Android apps using Kivy" - }, - { - "Content URLs": "Coming up soon (related to this workshop", - "Description": "Convolution Networks - Framework = Vision in vanilla python. This workshop aims at providing the attendees an experience of implementing convolution neural from scratch without any big framework working in the backend supplementing the need for computation. This would give the attendees an overall understanding of what are Convolution Neural Networks and why do they work so exceedingly well! One does not simply code in vanilla python. What can you expect from this workshop! You'll understand what are convolution neural networks Why they work so well on image data? All the different implementation of Convolution network and how they improve the vanilla network What are the best ways to implement convolution network on a given data What this workshop is not! Just another workshop telling you to use frameworks Maths will not be looked over. (It's important) This workshop is not any other university lecture where you'll not understand anything. I find this image to be so apt given all the abstraction provided by frameworks", - "Last Updated": "18 May, 2018", - "Prerequisites": " Command over Python Familiarity with Numpy and basic math packages Intermediate Mathematics Familiarity with algorithms common in machine learning", - "Section": "Data science", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a deep learning enthusiast who loves mathematics and astronomy. I've been exploring machine learning/deep learning for about 2 years now and fiddling with the basic mathematics and scratch implementations always excite me. I'm currently mentor of deep learning in a Delhi based startup Greatech Soft Solutions and interning at Startup labs and a Google Summer of Code '18 student under the organization OpenAstronomy", - "Speaker Links": " http://prsr.me https://www.linkedin.com/in/prakharcode https://github.com/prakharcode", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/convolution-neural-networks-without-any-frameworks~bmX3a/", - "title": "Convolution Neural Networks without any frameworks" - }, - { - "Content URLs": " https://docs.julialang.org/en/release-0.4/ https://julialang.org/ Ppt (soon)", - "Description": "Julia Programming Language The Julia programming language is proving to be a new paradigm shift in the data science community due to it's easy to pick up syntax like python but and execution speed equivalent to C , this is possible due to flexible types and JIT compiler. The speed and user-friendliness are only some of its good parts. This talk delves deeper into understanding, how can Julia be the next language on your learning list. Outcomes of the talk What is Julia? How can I get it into my daily workflow What Julia offers that Python does not Understanding benefits of shifting to Julia How can a python-ista shift to Julia", - "Last Updated": "18 May, 2018", - "Prerequisites": " Laptop with Julia up and running", - "Section": "Others", - "Speaker Info": "Hello World! I'm Prakhar Srivastava, junior year undergrad, a recently born Julia-n, I do a lot of code in Julia and move back and forth from Julia to Python to C. I'm a deep learning practitioner and loves Astronomy. I recently got selected into Google Summer of Code under OpenAstronomy org and my project's fundamental language is Julia. I'm a computer science by day and dancer by night. Currently, I'm fiddling with Julia and it's awesomeness and I'll offer you nothing less than awesome", - "Speaker Links": " http://prsr.me https://linkedin.com/in/prakharcode https://github.com/prakharcode", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "prakhar srivastava (~prakhar91)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/julia-an-upgrade-to-python-programming-language~enJpe/", - "title": "Julia. An upgrade to Python Programming Language" - }, - { - "Content URLs": "Slides: https://speakerdeck.com/satwikkansal/do-you-really-think-you-know-strings-in-python Also relevant: https://github.com/pydelhi/talks/issues/77 Most of the snippets and concepts to be discussed are taken from various resources I came across during my 6 months long research about Python. I have collected such snippets in a project called \"What the f*ck Python!\". Here's the source: https://github.com/satwikkansal/wtfpytho", - "Description": "Do you know that, 'a'[0][0][0][0][0] is a semantically valid statement in Python. print(r\"\\ some string\") is a valid statement, but print(r\"\\ some string \\\") raises a SyntaxError . print('wtfpython''') is valid but print(\"wtfpython\"\"\") raises SyntaxError . Do you know why, >>> a = \"some_string\"\n>>> id(a)\n140420665652016\n>>> id(\"some\" + \"_\" + \"string\")\n140420665652016 the id of both the objects in above snippet is same? And do you know why, >>> timeit.timeit(\"s1 = s1 + s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.25748300552368164\n# using \"+=\", three strings:\n>>> timeit.timeit(\"s1 += s2 + s3\", setup=\"s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000\", number=100)\n0.012188911437988281 s1 = s1 + s2 + s3 is much slower than s1 += s2 + s3 . And finally, >>> 'a' * 20 is 'aaaaaaaaaaaaaaaaaaaa'\nTrue\n>>> 'a' * 21 is 'aaaaaaaaaaaaaaaaaaaaa'\nFalse\n\n# one last attack!\n>>> a = \"wtf\"\n>>> b = \"wtf\"\n>>> a is b\nTrue\n\n>>> a = \"wtf!\"\n>>> b = \"wtf!\"\n>>> a is b\nFalse\n\n>>> a, b = \"wtf!\", \"wtf!\"\n>>> a is b\nTrue Do you know the reason behind all the above-discussed facts and snippets? Some of them are really puzzling, right? I felt the same when I first came across all these intricacies. But don't worry, such behaviors, are mostly the consequences of strings being [immutable] [sequences] in Python. In this talk we'll be going through the concepts behind such snippets in detail, so that next time when you see such examples, the answer seems natural to you. Finally, we'll try to answer some interesting questions like, How does string concatenation work? What's the best way of building large strings in Python? (It may actually depend on your use-case) What happens when you multiply a string by a boolean? How strings in Python differ from strings in other languages like JavaScript, C++? and many more", - "Last Updated": "18 May, 2018", - "Prerequisites": "Basic familiarity with programming. Prior experience with Python would make the talk more interesting for the attendee", - "Section": "Core python and Standard library", - "Speaker Info": "I'm a Software Developer experienced with Decentralized Applications and Data Science. In my leisure time, I love doing pointless things with programming. Currently on a quest to learn as much as I could about Computer Science. And lastly, I prefer all things Python! (A humble brag ", - "Speaker Links": "Website | Github | Archives Past Speaking Experience PyCon India 2017 (Speaker for a DevSprint ) EuroPython 2017 ( Invited as a Speaker for a workshop , unable to attend though) IWD-Delhi 2018 ( Speaker ) PyDelhi biweekly meetup (Gave a small talk ) OSS DTU (Instructor and moderator)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Satwik Kansal (~satwik)", - "created_on": "18 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/do-you-really-think-you-know-strings-in-python~boJLa/", - "title": "Do you really think you know strings in Python?" - }, - { - "Content URLs": ">>> import thi", - "Description": "Tim Peters preached and we memorized that Explicit is better than implicit, but how many understood the deeper meaning enough to imbibe the essence of the zen? In this 20 min talk, we shall go through the zen and look at live examples where the golden words make a programmer's life easy", - "Last Updated": "19 May, 2018", - "Prerequisites": "Familiarity with the syntax of Python", - "Section": "Core python and Standard library", - "Speaker Info": "Anuvrat has spent countless hours wading through utterly un-pythonic, non-modular codebases that contain > 8000 lines in one file and >500 in one function, with nested try-except statements and has almost mastered the skill of keeping his calm and understanding even that", - "Speaker Links": "https://anuvrat.i", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anuvrat Parashar (~bhanuvrat)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-python-with-real-life-examples~epVyb/", - "title": "The Zen Of Python: with real life examples" - }, - { - "Content URLs": "This talk is going to be based on a series of blog posts I have written about the same topic - Python Project Workflows - Part 1 Python Project Workflows - Part 2 (Pipenv) Python Project Workflows - Part 3 (pylint)", - "Description": " Have conflicting dependencies (unpleasantly) surprised you? (Darn: It worked on my laptop!) Do deterministic builds matter? What about those run-time errors, which were a typo while accessing an attribute of a class? Has the codebase already started smelling a bit? Unit tests and what about Dockerization? Typically, when your Python project grows beyond a few modules and your team size is more than a couple of developers, having the right tools built into your project development workflow saves one from a lot of surprises (and perhaps late night calls). In this talk, we start with challenges typically seen in Python Projects and look at ways of overcoming them, so that the velocity of code deployment increases. Specifically we are going to be looking at tools that are out there that allow you to - Properly track dependencies ( pip , virtualenv and the new Pipenv ) Have a separate Dev and Production environment - so that dependencies in Dev environment don't spill into Production environment. Ensure that the builds are deterministic (across developer/build machines and time.) Enforce certain coding guidelines and capture the potential 'run-time' errors right during the development ( pylint ) and Eventually Dockerize your application.", - "Last Updated": "19 May, 2018", - "Prerequisites": "It's an intermediate level talk where you have already done some Python development and are at a point where you want to package, distribute or deploy your pet Project. If you are a beginner in Python, but have been involved in build/release of packages in any other languages, likely this talk is for you. If you do an equivalent of sudo pip install or sudo apt-get install when you want to download and use package foo , chances are you will benefit from this talk quite a bit", - "Section": "Developer tools and Automation", - "Speaker Info": "Running a Consulting Company 'hyphenOs Software Labs' in Pune, India. Python/Go programmer - Mostly for things that pay the bills and ideas that I want to try out. Datacenter Networking Enthusiast (hacking a yet another Container Networking technology, borrowing ideas from different Projects) Eternally grateful to whoever wrote tcpdump and the new Wireshark . Number of problems solved using these tools could run into triple digits. Hates trailing white spaces in a file.", - "Speaker Links": " Stack Overflow Github LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Abhijit Gadgil (~gabhijit)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-project-workflows-continuous-deployment-friendly~bq8ya/", - "title": "Python Project Workflows - Continuous Deployment Friendly" - }, - { - "Content URLs": " https://pytorch.org/docs/stable/index.html Slides (https://slides.com/rahulbaboota/deck)", - "Description": "Talk Abstract This talk aims to introduce Facebook's Deep Learning library - PyTorch. PyTorch is increasing becoming popular due to it's powerful features and shallow learning curve, making it accessible and easy to use to a larger community. This talk discusses about the 'Autograd' package, which is central to all neural networks in PyTorch. It also entails details about the different features and functionalities of PyTorch as well as equip the audience on how to create simple and complex Neural Networks in PyTorch. PyTorch helps to create dynamic computation graphs that allow you to change how the network behaves on the fly unlike static computation graphs. It offers modularity which enhances the ability to debug or see within the network. Outline of the Talk The talk will be broadly divided into 3 broad parts. Part 1 will be an Introduction to PyTorch. This part will focus on the use and need for PyTorch as a deep learning framework. This will be followed by instructions on how to setup PyTorch and a look at the basic building blocks behind the framework. Part 2 will dive more into the features of PyTorch, mainly it's AutoGrad package which lies at the heart of all Neural Networks created in PyTorch and PyTorch's ability to create dynamic computational graphs as opposed to the static computational graphs offered by some of it's counterparts (such as TensorFlow and Caffe). Part 3 will be a more 'hands on' part where the talk will focus on how to create and build simple as well as complex neural networks (such as Convolutional Neural Networks) with the framework", - "Last Updated": "19 May, 2018", - "Prerequisites": " A basic understanding of how Neural Networks work would be beneficial. Some knowledge about Numpy.", - "Section": "Data science", - "Speaker Info": "I am Rahul Baboota, a 3rd Year Undergraduate in India studying Computer Science and Engineering. I have an avid interest in the domain of Data Science, Machine Learning and Deep Learning. I have worked at various Data Science and Machine Learning based startups and labs. In my freshmen year, I worked at a data journalism startup to create and analyze smart data stories. I was also a part of a project funded by the Government of India for the development of a social media based analytics tool for the analysis of healthcare and nutrition in India. I am currently working at the Center for Artificial Intelligence at IIITD in the Autonomous Vehicle Lab 'Swarath'", - "Speaker Links": " https://www.linkedin.com/in/rahulbaboota/ https://github.com/RahulBaboota", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "rahul baboota (~rahul93)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/throwing-light-on-pytorch~er7La/", - "title": "Throwing Light on PyTorch" - }, - { - "Content URLs": "(Slides to be uploaded soon", - "Description": "In computer vision, object detection is scanning and searching for an object in an image or a video (which is just sequence of images). Whereas, object tracking is like you are spying on someone and following it. Done in motion images like in animated gifs or videos, we want to track how an object is moving, where is it going, or its speed. Although it has been studied for dozens of years, object detection and tracking remains an open research problem . The difficulty level of this problem highly depends on how you define the object to be detected and tracked. If only a few visual features, such as a specific color, are used as representation of an object, it is fairly easy to identify all pixels with same color as the object. On the other extremity, the face of a specific person, which full of perceptual details and interfering information such as different poses and illumination, is very hard to be accurately detected, recognized and tracked. Thus, I believe it is important to address such challenges via a comparative study of object tracking and object detection in python. Here, I aim to present my own experience in tackling the problems while I tested different algorithms for the same", - "Last Updated": "19 May, 2018", - "Prerequisites": "Basic understanding of pytho", - "Section": "Data science", - "Speaker Info": "Anand Zutshi is currently pursuing his undergraduate B.E. degree from Netaji Subhas Institute Of Technology, Delhi. He has experience in developing and testing basic as well as advanced algorithms in C, C++. He has experience in developing a Learning Management System which uses dynamically trained neural network for scoring its users, and a LDA based tagging in its queries. He has in depth knowledge of Natural Language Processing, mainly with emphasis on word sense disambiguation and language models. His recent work of interest primarily focusses on object detection and object tracking in Python and sound classification and recognition. Currently, he is working on testing a biometric database management system along with predicting self and non-self processes in Operating system using Neural Networks", - "Speaker Links": "https://github.com/zutshianan", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "anand zutshi (~anand09)", - "created_on": "19 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-tracking-vs-object-detection-a-comparative-analysis~avJna/", - "title": "Object tracking vs Object detection- a comparative analysis" - }, - { - "Content URLs": " https://github.com/rahulkumaran/Telegram-Syntaxdb-bot There will be some slides that I'll prepare too but most of it is going to be an explanation from the GitHub repo and my talk https://github.com/python-telegram-bot/python-telegram-bot https://syntaxdb.com https://syntaxdb.com/api/v1 https://core.telegram.org/api", - "Description": "In this particular topic, I'll basically be telling people about how easy it is to create a Telegram Bot. The reason I'm interested in taking this up is because there are people who develop beautiful things and might want to let people to use it even on a mobile interface. The problem is not everyone's good with app development. So in such cases, deploying the beautiful things in the form of a bot would be a great idea. Bots can be of 2 types : Conversational Command based I'll be taking up the command based bot to help people get a feeling of this topic. Also, through the example I'll be giving, I'll try to make people understand as to what APIs are and how to use existing one. Later I'll show them how to create your own Python APIs because APIs make lives easier for programmers and it's always a good practise to know how to create an API as you never know when someone else might need it. CONTENTS AND ORDER OF THE TALK I'll be starting off with an introduction about myself and then I'll move on to what are bots. I'll then be explaining about why we could probably use these bots on Telegram, Discord, Slack and so on. Thereafter I'll be talking about the Telegram API for Python to help you interact with the bot and telling you how to use it. Before this, I'll show them how to prepare a bot on Telegram and get the Token. After this, I'll be talking about the importance of an API and utilizing existing ones as it makes your job much simpler. Slowly, I'll shift my focus on to how to build an API. I'll be explaining this using an example. Then using the Telegram Bot API and the API we build for Syntaxdb.com, we'll be creating a Telegram bot. Lastly, I'll summarise and entire talk and will take up a couple of questions. The entire talk will be based on a GitHub repository. The code links will be given to everyone for future reference", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Usage of libraries in Python", - "Section": "Others", - "Speaker Info": "The speaker, in this case is me, Rahul Arulkumaran . I'm an engineering undergrad currently going into my 3rd year. I'm also the Founder of the startup Free Flow . We still haven't registered it yet though. I started learning how to code when I came into engineering and Python was the first language I learnt. I never really developed anything until last year. It was after creating my first application that I got the interest to develop more using Python. From then to now, I've learnt a lot. I might not be an expert but yes, for my age, I think I'm better than most others. I'm also the President of the Computer Science Club, Enigma in my college Mahindra Ecole Centrale . I'm a Python developer and an open source enthusiast . I also am a Contributing and Managing member of PSF . I work on a lot of open source projects I love learning anything and everything related to coding. I'm also a Machine Learning and Data Science enthusiast ", - "Speaker Links": " https://rahulkumaran.github.io https://github.com/rahulkumaran https://www.linkedin.com/in/rahul-arulkumaran-101a63127", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-and-working-with-apis-to-develop-a-telegram-bot~dwgXd/", - "title": "Creating and working with APIs to develop a Telegram Bot" - }, - { - "Content URLs": "Repository for the content", - "Description": "Orbital Mechanics/Astrodynamics is one of the most difficult things to understand and take care of! For this simple reason it is called \"Rocket Science\". poliastro is a python package intended to make Astrodynamics Open Source, and easy to understand and visualise. Through the talk, various modules of the poliastro package will be introduced. I will show how we can solve very complex Orbital Mechanics problem in 2 minutes that takes years for a scientist to solve manually! The talk will cover some parts of AstroPy, numba and a bunch of plotting libraries such as matplotlib and plotly", - "Last Updated": "09 May, 2018", - "Prerequisites": "Basic introduction to plotly , matplotlib . Knowledge of some core packages like numpy, etc is beneficial. Knowledge of some of the core Astronomy libraries such as AstroPy is also beneficial", - "Section": "Data science", - "Speaker Info": "I am Shreyas Bapat, half \"Electrical Engineer\" and a passionate developer. I study at Indian Institute of Technology Mandi and constantly contribute to open-source projects. I have contributed to some projects like plotly, dash, poliastro and astroquery. I like Astronomy and related fields a lot and hence keep searching for projects related to that. Also, I am into Deep Learning from quite a time and love tweaking Neural Networks to get amazing results. I am the co-ordinator and maintainer at STAC-IITMandi . I have mentored the Astronomy Code Camp organised by Nehru Planetarium and Astronomical Society of India", - "Speaker Links": "GitHub Profile : shreyasbapat My Website: shreyasb.com My Portfolio: Click here Find my contibutions in Poliastro at #4 : https://github.com/poliastro/poliastro/graphs/contributor", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shreyas Bapat (~shreyasbapat)", - "created_on": "09 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/through-python-to-the-stars-orbital-mechanics-made-easy-and-open-source~dGK5d/", - "title": "Through Python to the Stars! - Orbital Mechanics Made Easy and Open-Source" - }, - { - "Content URLs": "Few resources that I will be using in the workshop. https://github.com/koshikraj/proof-of-ownership https://github.com/koshikraj/neo-python-contracts https://github.com/koshikraj/neo-ico-template", - "Description": "Bitcoin has been gaining popularity in the recent years due to its market value. But more importantly, the underlying technology is gaining the attention among the developers. Many developer communities inspired by bitcoin have created their own platform to use the underlying technology widely known as \"blockchain\" to achieve decentralization. Ethereum is one such platform that has created a blockchain platform which allows developers to develop their own decentralized applications (dApps) in the ethereum network by coding the logic in the execulatable contracts called \"smart contracts\" . Although ethereum has gained a huge fame due to its smart contract implementation to create decentralized applications, it imposes developer to write the logic in an ethereum's domain-specific language called Solidity. In addition to coding in a new language, it mandates the developer to set up a new develop environment. NEO blockchain platform provides a convenient way to develop smart contracts in general purpose programming language. NEO achieves this by providing compilers to compile code written in most of the languages to bytecode that can be executed in NEO virtual machine. Currently, NEO allows compilation of python smart contracts through neo-python project. This is the first blockchain project to provide such a freedom to the developer. NEO project provides plenty of benefits over other blockchain platforms out there. \nIt plans to achieve smart economy by creating a strong digital identity. It achieves faster transaction rate which is the key to scale any platform. NEO is being referred to as the \"New Ethereum\" due to its increasing popularity. I plan on conducting a workshop to create a decentralized application by developing and deploying smart contract using neo-python. Following would be the agenda of the workshop. Introduction to Bitcoin, Blockchain, and consensus to achieve decentralization. (30 mins) Introduction to NEO and Setting up a NEO platform (30 mins) Creating and deploying Hello World contract using Python (15 mins) Creating a Proof of Ownership system (30 mins) Creating a user interface to create a complete Proof of Ownership DApp. (20 mins) Creating an Initial Coin Offering (ICO) using an existing template and Q&A (25 mins) ** This is a rough estimation of time and topics as of now. I will try to fit more topics if possible. An attendee will be able to create an asset management DApp such as document ownership system or launch a basic ICO after attending the workshop", - "Last Updated": "20 May, 2018", - "Prerequisites": " Novice level experience in python programming. Basic knowledge of how bitcoin or blockchain technology is\n implemented would help to grasp the topic pretty well. Although I will be using Ubuntu Linux distribution for the demo, Attendees can use any platform which has python 3.6 installed. Windows users might have to install a docker container manager as installation might create some issues.", - "Section": "Networking and Security", - "Speaker Info": " I completed my masters in Computer science and Information Security after getting fascinated by the security and cryptography field. I have a demonstrated history of working in the computer and network security industry (RSA Security) where I had worked for more than a year. I worked as a senior fullstack developer for a start-up called CoWrks. In the meantime, I got involved in the blockchain and decentralized application. I started devoting my entire time to blockchain and I'm currently writing a research book on the blockchain technology called Foundations of Blockchain", - "Speaker Links": " My Linkedin profile. Few of my opensource contributions. My semi active social profile. Check out my detailed bio at koshikraj.com", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Koshik Raj (~koshikraj)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-decentralized-smart-contracts-using-python~egXra/", - "title": "Creating decentralized smart contracts using Python" - }, - { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "Abstract In this talk, I would be telling people how to write better and faster Python. I've been developing Python programs, scripts and softwares for over 2 years now and I come across people who have a problem of Python being slow. \nWhenever someone has to write a faster python code they are left with one option of just shifting their entire code from Python to C or C++. This talk will clear that misconception. People can actually write faster codes in Python, the only missing fact is how? . And this is exactly why I am interested to give this talk. Contents of the talk The talk will start with a basic introduction of myself as a Python developer. I will then talk about the misconception about shifting the code to C or C++. Then I will proceed onto some basic usage of Python Programming Language. Introduction to optimization techniques in Python. Then I will talk about when and why should one optimize their application. I will introduce the basic concepts of optimization in Python. Tell people about the available/built-in functions that can come in handy. Then I will proceed onto giving a demonstration on 'Writing better functions'. The talk will conclude with some examples of optimized code that performs better than conventional approaches. The talk will be open to questions, to make it more interactive and fun. The slides will be shared to the audience after the talk", - "Last Updated": "20 May, 2018", - "Prerequisites": " Basic Python Will to learn See, It does not require much", - "Section": "Core python and Standard library", - "Speaker Info": "My name is Manish Devgan . I am a second year Information Technology student at Netaji Subhas Institute of Technology, Delhi . I am an Open Source Contributor and a learner . I have contributed to various different open source projects and won many hackathons . I was FOSSASIA Codeheat 2017 - Grand Prize Winner and Google Code-In 2017- Mentor . Currently I am a GSoC 2018 Student under FOSSASIA and RGSoC 2018 - Coach . I have contributed to Python's ChatterBot Machine Learning Engine , variety of FOSSASIA's Projects , and a wide variety of OSS projects like Github Linguist etc. Python is my favourite programming language . From writing small scripts to building small Machine Learning libraries , I've tried a lot :", - "Speaker Links": " https://github.com/gabru-md https://twitter.com/gabru_md https://facebook.com/gabrumd https://www.linkedin.com/in/gabru-md/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Manish Devgan (~gabru-md)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-faster-python-optimizing-your-code~ejJye/", - "title": "Writing Faster Python : Optimizing your code" - }, - { - "Content URLs": " Slides on Introduction to NLP : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction%20to%20NLP%20%26%20Spacy.pdf Jupyter Notebook : https://github.com/py-ranoid/IntroNLP/blob/master/Introduction.ipynb Note : The above slides are not complete and are suited for a quick introduction to NLP in 20 mins I will be introducing the following Libraries (and use them to create chatbots) NLTK : https://www.nltk.org/ SpaCy : https://spacy.io/ I will be developing a bot on the following Chat Platforms with emphasis on Messenger: Messenger : https://developers.facebook.com/docs/messenger-platform/ Slack : https://api.slack.com/ Telegram : https://core.telegram.org/bots", - "Description": "Introduction to NLP Natural Language Processing is a prominent field in Artificial Intelligence that deals with parsing and understand Natural language, (an ordinary language such as English is any language that has evolved naturally in humans through use). NLP lies at the core of Google Duplex and other smart assistants that respond to questions in English and natural languages. I will be explaining the following : Corpus and Datasets Processing and tokenizing Text Tagging, Stemming and Lemmatizing Words WordNet Introduction to libraries NLTK Spacy Sentiment Analysis Word Embedding using BOW and word2vec Developing Chatbots With rising need for customer support, Chatbot are one of the most common applications of NLP. These are applications that are trained conversation with a human by answering some preset list of questions. I will be developing a chatbot on three platforms : Messenger (Facebook) Slack Telegram These will be deployed locally using Django with ngrok for tunneling. Additionally, due to the immense popularity of Messenger, I'll be also explaining the different message templates and other features that Messenger has. If you'd like to see me cover another platform such as Discord, Skype, Google Assistant or Alexa, feel free to drop a commen", - "Last Updated": "20 May, 2018", - "Prerequisites": "Basic knowledge of Python, English Grammar and HTTP Requests", - "Section": "Others", - "Speaker Info": "About me Hello world. I\u2019m Vishal Gupta, a 3rd yr CSE undergrad at SSN, Chennai, India. \nWhile most people generally pick up a topic, or a concept (like say Computer Vision, Big Data, or just Algorithms), understand it and aspire to excel at it\u2026 I fell in love with a language, Python. As someone who has started out by learning C++ in school, learning Python was as easy as surprising. The speed at which I could translate ideas to code was amazing, and oh boy, all I wanted to do was make things, write simple scripts to automate everyday tasks. And hence I continued to explore Python, the countless modules and possibilities with Python. I went to Hackathons, won some but more importantly made something that others could use. Chatbots and me UI/UX has never been my strong suit but Chatbots made it simple to use serve any application in a conversational manner. Over the last 2 years, I have developed over a dozen chatbot for a variety of purposes, from fetching torrent links to code education to keeping track of events. One of my best messenger chatbots is still functional with nearly ~500 subscriptions. PyGeon , scrapes a number of sites everyday for developer events such as meetups, hackathons and contests in 7 indian cities. Newly added events are sent to users every day. Experience : Chatbot intern at GoBumpr , Chennai CV intern at XR Labs , Chennai NLP intern at BicycleAI Google Summer of Code participant with Debian", - "Speaker Links": "Complete list of projects LinkedIn - Vishal Gupta GitHub - py-ranoi", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Vishal Gupta (~vishal11)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-nlp-and-chatbots~bkMJe/", - "title": "Introduction to NLP and Chatbots" - }, - { - "Content URLs": "I will post presentation and Relevant codes soon on github. For reference please find the code here :\nhttp://magneplane.readthedocs.io/en/latest/index.htm", - "Description": "Content of My talk will have : Hyperloop : An Introduction How Python plays an Important role? Python Applications in the Project: Project Management, \nScripting the repeating processes, \nPython - ML in CFD, \nRaspberry Pi in Communications.", - "Last Updated": "20 May, 2018", - "Prerequisites": "An intermediate level knowledge of Python Knowledge of a Python and basic Math", - "Section": "Others", - "Speaker Info": "Suyash Singh is post graduate Student of Indian Institute of Technology, Madras Chennai. He is Head of Team Avishkar Hyperloop More Details about Avishkar Hyperloop : http://avishkarhyperloop.com/ He carries 4 years of work experience in Big Data and Data Science. Later his interest in fifth mode of transportation took him to IIT Madras. He has been pure pythonist. He has been a adviser to two small scale startups based out of Indore which deals with data science. He has a vision of transforming Transportation making it more efficient. He thinks Python will be an important tool to make it possible", - "Speaker Links": "LinkedIn Profile: https://linkedin.com/in/suyashao", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Suyash Singh (~suyash_singh)", - "created_on": "20 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hyperloop-how-python-helps-building-fifth-mode-of-transportation~el6jb/", - "title": "Hyperloop : How Python helps Building fifth mode of Transportation?" - }, - { - "Content URLs": "https://github.com/atulsinghphd/NL", - "Description": "In this hands-on course using Python, we will learn how to use machine learning for Natural Language Processing (NLP) through interactive notebooks. Natural Language Processing (NLP) is a field that covers computer understanding and manipulation of human language. Machine learning is a branch of Artificial Intelligence that focuses on the ability to automatically learn from existing information. Language processing uses models that attempt to understand and represent the information at various levels that includes morphology, syntax, semantics, pragmatics and discourse. In this training, we will learn how to use machine learning to build these models. This training includes the following topics: Representing text as a vector using count, TF-IDF and co-occurrence matrix Detecting similar documents Sentiment Analysis Identifying the themes in a set of documents Extracting the entities and the relationship between the entities (stretch goal depending on time) The course will introduce the participants to NLP libraries such as nltk, gensim and Spacy", - "Last Updated": "21 May, 2018", - "Prerequisites": "This is an advanced machine learning course. To benefit from this course the participants are expected to have:\n1. Understanding of supervised and unsupervised machine learning \n2. Knowledge of python, or a high-level programming language like Java or C#.\n3. Using jupyter Python notebook environmen", - "Section": "Data science", - "Speaker Info": "Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), geo-spatial analytics, and reinforcement learning. Sasidhar Donaparthi I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company", - "Speaker Links": "Linkedin Profiles https://www.linkedin.com/in/sasidonaparthi https://www.linkedin.com/in/atulsinghphd/ Twitter Profiles @sdonapa", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Atul Singh (~atul98)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deciphering-human-language-using-machine-learning~bm0Ra/", - "title": "Deciphering human language using Machine Learning" - }, - { - "Description": "In this talk the main aim is to demystify data science and introduce the audience with the concepts of data science and machine learning in python. Goals : What is Data Science ? What is Machine Learning ? Why Python for Data Science ? How to solve a Real world problem with data science ?", - "Last Updated": "21 May, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Data science", - "Speaker Info": "Jatin Ahuja is a self taught data scientist and machine learning practitioner. He's currently working in Data Science domain . He's the core team member (designated as PR Director) and city ambassador of AI Saturdays which is a community of over 5000+ students(over 100+ cities) to spread the knowledge of AI free of cost. He actively blogs about machine learning in his personal blog site named as everythingai . He mentors the aspirants in their journey to become a successful data scientist , machine learning engineer or deep learning engineer at MentorCruise.com ", - "Speaker Links": " Website ; https://everythingai.co.in Github : https://github.com/A-Jatin LinkedIn : https://linkedin.com/in/jatin-ahuja-89677614a/ ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "JATIN AHUJA (~jatin)", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-science-with-python~enm5d/", - "title": "Data Science with python" - }, - { - "Content URLs": "wikipedia article on the brain computer interface Text Summarizer neural network model code is in the following lin", - "Description": "Brain Mapping Using Python: Over the past few years, machine learning and artificial intelligence has been making headlines and advancing quickly by creating products that can make optimistic decisions. Now this machine learning technology can be implemented in making a machine which can perform complex actions just like in brain which can make human life easier. Now the real challenge is can we create a neural network model which can perform complex\nactions like human brain? How Python can be used to accomplish this task and how far we can achieve this feat?\nThis talk will be focusing on the methods approached by brain to generate conclusions or make decisions which can be replicated in computers and generate results. Contents of the talk About me - Basic introduction of myself. What is Brain Mapping? Functionalities of Human Brain. Neural Networks Using Python. Types of Data Summarisation techniques in Python. How Computers can make decisions. What can we expect from Brain Mapping in future.", - "Last Updated": "21 May, 2018", - "Prerequisites": " basic syntax knowledge of python basic machine learning terminology neural network models functionality", - "Section": "Data science", - "Speaker Info": " ROHITH PUDARI Rohith is a B Tech student who is passionate about integrating the most complex organ known to human which is brain with computers. He is winner of the Hyderabad best coder championship conducted by JNTUH. He is one of the few persons in India who is selected for the google Udacity scholarship. He is always interested in decreasing the interaction gap between computers and humans and started his research in creating an interface which will allow humans to interact with computers in a more natural way. He created a neural network model which generates a summary of a given essay which won the title \"Best innovative idea\" at IIT Kanpur", - "Speaker Links": "you can see the projects and previous work of Rohith in the following link to his github profile. and linkedIn profile Rohith contributed to the following open source projects: Atom- open source code Editor OpenWISP- software platform that implements a complete Wi-Fi service Sugar Labs- desktop environment and learning platform Sustainable Computing Research Group (SCoRe)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "dvlpr_rohith", - "created_on": "21 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/brain-mapping-with-python~bonYa/", - "title": "Brain Mapping with Python" - }, - { - "Content URLs": " Will share my slides after my talk as a Github repository.", - "Description": " Abstract This talk is for Python web developers interested in learning what are\nthe core ideas behind microservices, what problems they try to solve,\nand what are the viable options to implement them in Python, both from\ntechnical and teamwork point of views. Some of the topics that will be\ndiscussed include the role of APIs, the improvements microservices\nbring to application scalability, upgrades, and maintenance, and the\nchallenges in breaking up a monolithic application. Contents of the talk About me - Basic introduction of myself. What are Microservices? Monolithic Python Web Application. Problems with Monoliths. Microservice Example. Advantages of Microservices. Disadvantages of Microservices. How to refactor a monolithic application into microservices? ", - "Last Updated": "22 May, 2018", - "Prerequisites": " Basic Python", - "Section": "Core python and Standard library", - "Speaker Info": " My name is Kasam Sharif (Passionate Programmer | Startup Enthusiast |\nProblem Solver). I am currently Software Engineer at Agrostar, Pune.\nPreviously was working at Symantec having 3 year of experience in IT\nindustry. In free time love to learn new things.", - "Speaker Links": " Linkedln : https://www.linkedin.com/in/kasam-sharif-2027628b/ Twitter: https://twitter.com/kasam_sharif94 Github: https://github.com/kasamsharif", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kasam Sharif (~kasamsharif)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-microservices~dyA6d/", - "title": "Python Microservices" - }, - { - "Content URLs": " I'll be sharing the slides after my talk as a Github repository", - "Description": "RabbitMQ is a powerful messaging broker based on the Advanced Message Queueing Protocol (AMQP). Microservices do what they say on the tin. They\u2019re small, isolated services that represent an equally small portion of your business domain. Recently there's a trend to build an application using Microservices which place an emphasis on small processes. As an increase in Microservices, we need to a mechanism where we could use some channel(Pub-Sub) to talk between these Services. Contents 1) Introduction to RabbitMQ and Its Terminology 2) Microservices using Pub-Sub 3) Sample Execution At the end of this session, participants will be able to use the rabbitMQ for there application(Could be ETL's/ MicroServices etc", - "Last Updated": "22 May, 2018", - "Prerequisites": "1) Basic Pytho", - "Section": "Others", - "Speaker Info": "My name is Jigar Shah. I have completed my BTech from Walchand College of Engg Sangli. I am currently working as a Software Developer @Browserstack. Interests: Building Backend Architecture, System Design, Data Structures, Algorithms More Inf", - "Speaker Links": "Github Linkedl", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Jigar Shah (~jigarshahindia)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rabbitmq-in-python-for-event-based-communication-between-microservices~az4qd/", - "title": "RabbitMQ in Python for event-based communication between MicroServices" - }, - { - "Content URLs": " The main sunpy website - SunPy.org The code repository - sunpy My Experience with working on the SunPy project - Blog SunPy Gallery - Examples My Contributions to the SunPy Project - Code + Examples Contribution", - "Description": "The Problem The Sun releases huge amount of magnetic energy in the form of X-rays, EUV (Extreme ultraviolet) and high energy particles. This kind of radiation bursts can cause damage to space and ground based technological infrastructure. \nHence monitoring such solar activity is crucial. Research Work There has been considerable research in the field of solar activity monitoring as done by NASA Space Stations. Primary research includes locating sunspot regions or potential regions of high solar density along with detecting solar flares from the solar data. Solar Physics in Python In the field of solar physics, IDL is regarded as the primary programming language for solar data analysis purpose. But due to its less popularity and complexity there has been transition to using a much simpler yet robust language Python. The SunPy Project is such a community developed open source project for solar data analysis purpose based in Python. So how using python we can benefit the astrophysics and helio-physics community to query solar data and analyze them much more efficiently and produce much more insightful results ? In this talk we will be discussing how we can analyze sunspots and solar flares through image-processing tools using a python package called sunpy . A small example Locating Solar Spikes in the solar Map Original observed AIA image After locating such regions Extras More examples - SunPy Gallery Machine Learning with Solar Data", - "Last Updated": "22 May, 2018", - "Prerequisites": " Knowledge of Python (Beginner/ Intermediate) Little bit knowledge about the sunpy package (not mandatory) Python modules like scipy and matplotlib since there is heavy use of this two modules. A lot of excitement and passion for open science", - "Section": "Data science", - "Speaker Info": "Prateek has been an open source enthusiast for the past 2 years with a deep love in the field of astronomy and helio-physics . He is currently an undergraduate in computer science also a GitHub Campus Expert working directly with GitHub Education to build open source communities and support them on campus. He is a core contributor to the SunPy project for around more than a year which is lead by researchers from different universities along with scientists at the NASA Goddard Space Flight Center", - "Speaker Links": " GitHub Profile - prateekiiest Twitter - prateekiiest Website - prateekiiest,github.io GitHub Campus Expert - prateekiiest @campus_expert Blog - Medium", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Prateek Chanda (~prateekiiest)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/predicting-sunspots-and-solar-flares-with-a-tinge-of-python~dBXQa/", - "title": "Predicting Sunspots and Solar Flares with a tinge of Python" - }, - { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Malware is a serious threat to all kind of Cyberinfrastructure. Since the first known malware (formerly or generally known as Virus) there have been malware detection techniques. There is the arms race between new incoming of Malware and defense against it. Traditionally, anti-virus software uses signature-based techniques to detect malware and protect the underlying system. Due to some critical limitations of signature-based techniques, anti-virus, and security agency looking for alternative techniques and investing in machine learning based techniques for malware detection.\nThis workshop aimed to train the participants through various steps involved in building malware classifier based on machine learning algorithms. Python is very suitable for the task due to its large number of useful modules suitable for each and every step. During this workshop, following topics will be explained with proper hands-on using Python. Explanation of the topic and draw out the various required steps. Data collection: How to collect Malware and Benign samples for the experiment. Pre-processing: How to carry out various pre-processing tasks\n (duplicate removal, file type identification etc.) to prepare the suitable dataset for the experiment. Labeling: How to label the sample i.e. malware v/s benign. (Required\n for supervised learning.) Feature extraction: How to extract features from the sample and\n build the proper representation of features to be used with various\n Machine learning algorithms. (We will restrict to static features\n for this workshop). Model training and Testing: How to train various machine learning\n algorithms and test their performance to select the best model. Making model persistence: How to make the selected model persistence\n to further use. ", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general. Required module/library:\n1. pefile\n2. androguard\n3. scikit-learn\n4. CS", - "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-malware-classifier-from-sample-collection-to-persistance-model-using-python~eEXWd/", - "title": "Building Malware Classifier: From Sample Collection to Persistance Model using Python" - }, - { - "Content URLs": "All the contents (code, slides and other supporting resources) will available after the workshop but I will keep updating the resources here in due time. Githu", - "Description": "Python is a versatile, powerful, and general purpose language, its easy and clear syntax makes it very popular for the beginner as well as the advanced programmer. Malware is one of the top threats to today's digital society. Due to heavy financial loss along with other infrastructure losses, the software industry is investing hue money for malware research and at the same time due to the wide need of effective and efficient anti-malware solution, the anti-virus industry is emphasizing on malware research.\nThis talk will focus on the array of python resources (script, modules, library, frameworks etc.) available for various dimensions of malware research. During the talk, I will share my experience with various tasks or problems related to malware research and how with the use of Python, those were solved. This talk will try to draw a parallel connection with various tasks related to malware research and suitable Python resources available for achieving those tasks. The talk will be supplemented with the brief explanation of concepts and python snippets for the same. \nSome of the modules and topics that I will touch upon are: yara Accessing VirusTotal API with Python Cuckoo-sandbox Androguard pefile pyew file type filtration ClamAV and pyClamd etc.", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of Python Syntax and Programming in general", - "Section": "Networking and Security", - "Speaker Info": "Dr. Ajit Kumar has completed his Ph.D. from Department of Computer Science, Pondicherry University in 2018. His Ph.D. thesis titled \"A Framework for Malware Detection with Static Features using Machine Learning Algorithms\" focused on Malware detection using machine learning. He is working with Python since 2012 for his research work and other development work. He is also interested in web development, Information security, and Data science. Python is his language of choice for all the programming related tasks. He has been motivating and training students to adopt Python as his programming language. He loves to write and share the article about Python and its applications. He has received his Bachelor of Computer Application (BCA) from IGNOU in the year 2009 and Master of Computer Science in the year 2011, from Pondicherry University. With his formal education, he has received Post Graduate Diploma in Statistical and Research Methods from Pondicherry University in 2015 and Post Graduate Diploma in Information Security from IGNOU in 2016", - "Speaker Links": "LinkedIn Twitter Quora ResearchGate Google Scholar Mediu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "urwithajit9", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-arsenal-for-malware-research~dGXKe/", - "title": "Python Arsenal for Malware Research" - }, - { - "Description": "The Talk will focus on the importance of satellite image processing with main focus on the utilisation of GDAL library to conduct various operations on satellite data. Datasets will include Optical imagery and Synthetic Aperture Radar Imagery. The power of GDAL library alongwith numpy and matplotlib will be demonstrated. Brief analysis of satellite images using python will be given", - "Last Updated": "23 May, 2018", - "Prerequisites": "Basic Knowledge of numpy and matplotlib libraries", - "Section": "Data science", - "Speaker Info": "Shubham Sharma is a Junior Research fellow currently working on a collaborative project with Calibration and Validation Division of Space Applications Centre, ISRO, Ahmedabad. He has a rich experience in handling and processing of Synthetic Aperture Radar Images. Also, he has experience in building software tools in python for satellite Image analysis", - "Speaker Links": "https://in.linkedin.com/in/shubham-sharma-5468578", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "shubham_thb", - "created_on": "23 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/satellite-image-processing-with-python~dJKKe/", - "title": "Satellite Image Processing with Python" - }, - { - "Description": "Many at times, we need to encapsulate our core logic in order to protect it from being reverse engineered and being exploited. Having a strong IP may not be the only protection. Once the code is open for the analysts, they can easily implement a modified version to achieve their goals. Some areas where the code obfuscation plays an important role are financial domain, security, web/mobile. Many times developers / teams fail to achieve the right level of code obfuscation which in turn fails to provide the level of protection to their code. We will be walking through the existing code obfuscation techniques in python and the level of protection they offer. I will be sharing my experiments and learnings during the journey to achieve a better obfuscation mechanism for python code", - "Last Updated": "22 May, 2018", - "Prerequisites": "Required : None. As we will be covering the required basic for code obfuscation in the talk it self. Good to have : Understanding the python run time process and how the code gets converted to executable binaries can be helpful", - "Section": "Core python and Standard library", - "Speaker Info": "I am Kailash, currently working as a Senior Software Engineer in Visa. I have been into python programming for the past 6 years now. I had worked on multiple levels of python projects ranging from scripting and automation, DevOps, Machine Learning, Computer Vision, Algorithmic Trading, Website Backends", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Venkata Naga Kailash Anantha (~avnkailash)", - "created_on": "22 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/effective-code-obfuscation-protecting-your-python-code-from-being-copied-reverse-engineered~axzld/", - "title": "Effective Code Obfuscation : Protecting your python code from being copied / reverse-engineered" - }, - { - "Content URLs": "I'll share my slides after my talk as a GitHub repository", - "Description": "This talk is for Python enthusiasts who are interested in building test automation framework and test suites for REST API functional testing. It would throw a light on how to write useful, business-oriented and maintainable functional API test suites in Python on top of existing test frameworks like lemoncheesecake . Contents: About myself REST API and it's testing - A quick introduction Choosing a test framework to write your tests on Making API requests from Python Writing suite configuration and teardown code Introduction to the \"component-tests\" model for structuring the test code JSON parsing, use of matchers, asserts for writing test case validation criteria Importance of logging and reporting - How logs and readable reports can ease the job of debugging bugs found using tests Bringing everything together", - "Last Updated": "24 May, 2018", - "Prerequisites": " Python basics REST API basics Basics of test frameworks like pytest Passion for test automation", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm currently working as a SDET Lead with AgroStar, India's largest agri-tech platform for the Indian farmer. I'm passionate about technology and automation, I'm willing to contribute in building robust software test frameworks accompanied with some of the best industry practices like CI/CD that would help ensuring the best possible software quality from time-to-time. The \u201calways exploring and learning\u201d attitude is something that keeps me going", - "Speaker Links": " LinkedIn Facebook Twitter", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Akshay Maldhure (~akshay61)", - "created_on": "24 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/rest-api-functional-testing-with-python~aK7Ga/", - "title": "REST API functional testing with Python" - }, - { - "Content URLs": "will be sharing the slides after my talk as a Github repositor", - "Description": "AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment. CloudFormation allows you to use a simple JSON or YAML file to model and provision, in an automated and secure manner, all the resources needed for your applications across all regions and accounts. This file serves as the single source of truth for your cloud environment. In this talk, I will be using Python to generate the JSON and YAML files with which AWS CloudFormation can be done. During this talk I will be covering the below points What is AWS CloudFormation? Library in Python for AWS CloudFormation. What are S3 and EC2 AWS services. Creating basic S3(Simple Storage Service) and EC2(Elastic Compute Cloud) instance using Python. Installing MySQL in the EC2 instance. Code pipeline (Automatic Deployment from Github to production server)", - "Last Updated": "25 May, 2018", - "Prerequisites": "Basic Understanding of Python and how to use Libraries", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Mohan currently working as a Software Engineer at Amzur InfoTech Visakhapatnam.I have been in to Python Programming for the past 1 year. I have 2 years of experience as a Developer. I had worked on Data Migration. I am currently working on Data Science,MicroGrids Automation and AWS", - "Speaker Links": "www.linkedin.com/in/mohan-pavan-kumar-bailapudi-5628a296 https://github.com/MohanBailapud", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Mohan Bailapudi (~mohan57)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-cloudformation-with-python~dL1De/", - "title": "AWS CloudFormation with Python" - }, - { - "Content URLs": "Fo now, I just have a gist: But I will create a proper package before the event: https://gist.github.com/dhilipsiva/3d7586e7bb941919f28afa70ccc39dd", - "Description": "Microservices are fun. But what would make them even more fun to work with, is if we can avoid duplicating the data layer across your micro-services. Django ORM is amazing. Let's share the joy of Django ORM with other languages. I have written a tool to automatically expose Django ORM to other languages and which can also generate respective client libraries in other languages. I heavily rely on Protobuf and gRPC and a lot of AST parsing", - "Last Updated": "25 May, 2018", - "Prerequisites": "You will need to know basics of: Django ORM Protobuf gRPC (or cap'n proto or any other RPC framework) Microservices", - "Section": "Developer tools and Automation", - "Speaker Info": "Wannabe Astrophysicist. Full Stack + DevOps. I code for fun and profit. Mostly in Python. FOSS. Dad of 2. Environmentalist. Atheist. Story Teller", - "Speaker Links": " http://dhilipsiva.com/ https://twitter.com/dhilipsiva https://github.com/dhilipsiva/", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "dhilipsiva Dhilip (~dhilipsiva)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automagically-exposing-djagno-orm-over-grpc-for-microservices-written-in-other-languages~aMKmd/", - "title": "Automagically Exposing Djagno ORM over gRPC for microservices written in other languages" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "The era of Artificial Intelligence is moving quite rapidly across the globe. It's being used in almost every application we know , from medical diagnosis to self driving cars and it's use is still growing exponentially. But should we blindly trust AI ? Is this technology robust enough? Are we capable enough to handle it's power? In this talk we will step back for a moment and look forward about the security issues and robustness of this technology. I'll be discussing the problems we can face , the precautions we have to take, etc. with the help of a famous problem, known as One Pixel Attack ", - "Last Updated": "25 May, 2018", - "Prerequisites": " A bit of Python Some knowledge of Machine Learning And a broader perspective ", - "Section": "Data science", - "Speaker Info": "The speaker, Srajan Kant Jha, is a final year B.E. student who has been working on Machine Learning and Data Science from quite a while now. Nonetheless, he pivoted from C/C++ to Python and during the transition, has also developed some projects on the same. He used to blog at his leisure time and is still on a venture to provide the knowledge of ML and Data Science to enthusiasts through a project site. Srajan is also the City Ambassador (and one of the speakers) of AI-Saturdays, which is a community of over 5000+ students(over 100+ cities) that helps people try their hands on Deep Learning and Artificial Intelligence, free of cost. Inspite of this, he still has a lot to discover in this growing industry. (Follow him on social media to know more", - "Speaker Links": " LinkedIn : https://www.linkedin.com/in/srajan-jha Github : http://github.com/srajan23 (not much updated) Facebook : https://www.facebook.com/srajan23", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Srajan Jha (~srajan)", - "created_on": "25 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-robust-is-artificial-intelligence-ai-using-python~dNK2e/", - "title": "How ROBUST is Artificial Intelligence ? ~ AI using Python" - }, - { - "Content URLs": " Github reposistories: Keras_aud Audio-Vision Drive links: Content link : (Slides to be uploaded soon)", - "Description": "In this workshop, we will try to teach how to understand Deep Learning, various paths to follow, Domains to explore and the most important part- how to start with the paper selection and implementation. We will also learn how to deploy a simple model into production. This workshop aims at providing the attendees of all level a foundation of research and further prospectives in deep learning. Contents Paths and prospects in Industry and Academia (10 minutes) Difference between AI, ML, and DL. (5 minutes) Introduction to Deep Learning frameworks (Hands-on) (5 minutes) Paper selection (10 minutes) Implementation (Hands-on) (60 minutes) Understanding the dataset Feature Extraction Model Selection Data Formatting Comparison Demonstration of our work (General Overview) Audio Tagging Acoustic scene classification Visual Question Answering Publish/Deploy (Hands-on) (30 minutes) Stay Motivated Opportunites to explore The participants should have interest in Research. Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first-time learner\u2019s of AI to comprehend", - "Last Updated": "27 May, 2018", - "Prerequisites": "Preferred Basic Python concepts Basic knowledge about Machine Learning Algorithms. Preferred (but not necessary) Interest in working on Research problems Installed libraries: Keras Theano or Tensorflow", - "Section": "Data science", - "Speaker Info": "Aditya Arora and Akshita Gupta are currently final year semester exchange students at Indian Institute of Technology, Roorkee. They have been working on research problems using deep learning specifically in Audio processing and visual Q&A. Aditya is a member of various open source societies such as rust-community while Akshita has experience in Academia research and is a selected as an Outreachy intern at Mozilla 2018. They have been working in python for the past 4 years and have been moving forward working on Computer Vision and Audio processing problems", - "Speaker Links": " Twitter : https://twitter.com/imaarora Twitter : https://twitter.com/akshitac8 Linkeldn: https://linkedin.com/in/aditya-arora145/ Linkeldn: https://www.linkedin.com/in/akshita-gupta152/ Github : https://github.com/channelcs Blog : http://channelcs.github.io/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Akshita Gupta (~akshitac8)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-into-the-world-of-deep-learning~aOXRb/", - "title": "Deep Dive into the world of Deep Learning" - }, - { - "Content URLs": "The repository where I have implemented concepts related to this talk https://github.com/tanayseven/http_quiz Contents for the presentation for the talk https://github.com/tanayseven/pycon_2018_python_web_app_tes", - "Description": "Abstract One of the first projects that I worked in the industry was in Flask . This talk is based on my experiences in the project with respect to the test suite and different things that I learnt in that. On the bases of those learnings, I started my own open source project on Github and enhanced on those ideas on how all the things necessary for testing are done. This is based on Flask as the web framework and all the ideas are implemented in it. The topics it covers are those things that you can do to achieve a robust set of tests in your code. Outline of the talk Pushing for 100% code coverage Making your test execution fast! The evil of \u2018over mocking\u2019 The necessity of using dependency injection Test Pyramid or Test Cone? TDDing while making changes Layers that make the web app architecture How does this map to UI testing", - "Last Updated": "27 May, 2018", - "Prerequisites": "Although most of the things are implemented in Flask, it is not necessary to know it, although it is very much recommended to know some web framework or having some knowledge of web app programming", - "Section": "Web development", - "Speaker Info": "A passionate developer with Python as his primary language. Have worked with Flask in the industry in the past. Passionate about testing and writing the code in a way that is very clean and maintainable. A strong believer in TDD and massive test coverage", - "Speaker Links": "https://tanayseven.com https://github.com/tanayseven https://www.linkedin.com/in/tanay-prabhudesai/ https://twitter.com/tanayseve", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanay PrabhuDesai (~tanay)", - "created_on": "27 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/having-a-robust-test-suite-for-your-python-web-app~dPKAb/", - "title": "Having a robust test suite for your Python web app" - }, - { - "Content URLs": "https://tools.ietf.org/html/rfc7047\nhttps://github.com/openstack/ovsdbapp\nhttp://www.openvswitch.org/support/dist-docs/ovsdb-server.1.htm", - "Description": "OpenvSwitch is an OpenFlow virtual switch implementation. It has its own database implementation based on JSON-RPC (https://tools.ietf.org/html/rfc7047) to store its internal state and data.\nThis session gives an overview of this database implementation and how it used in OVN, an SDN controller from the OpenvSwitch community and in OpenStack networking. This session will look\ninto how it is different from other traditional SQL databases and the python clients available to interact with the OVSDB server and the APIs it provides to carryout the CRUD operations with the OVSDB server", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of databases", - "Section": "Core python and Standard library", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": " https://numans.blog/about http://stackalytics.com/?metric=commits&release=all&user_id=numansiddique https://github.com/openvswitch/ovs/commits?author=numansiddique", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/openvswitch-database-based-on-json-rpc~dRKVe/", - "title": "OpenvSwitch Database based on JSON-RPC" - }, - { - "Content URLs": "https://en.wikipedia.org/wiki/OpenFlow\nhttps://www.openvswitch.org/\nhttps://3vf60mmveq1g8vzn48q2o71a-wpengine.netdna-ssl.com/wp-content/uploads/2014/10/openflow-switch-v1.5.1.pd", - "Description": "Networking is a key aspect of any cloud infrastructure solution. All the VMs and containers\nspawned in a cloud deployment should have seemless layer 2 and layer 3 connectivity. All this is\npossible because of virtual switching and virtual routing. This session talks about what is OpenFlow specification, OpenvSwitch (which implements OpenFlow)\nand how it is used as an important SDN layer in cloud infrastructure solutions (taking OpenStack and OVN as an example)", - "Last Updated": "28 May, 2018", - "Prerequisites": "A basic understanding of networking", - "Section": "Networking and Security", - "Speaker Info": "I am Principle Software Engineer at Red Hat, Bangalore. I contribute primarily to OVN (part of OpenvSwitch) and OpenStack Neutron. Before contributing to OVN, I have contributed to OpenContrail SDN solution", - "Speaker Links": "https://numans.blog/about/\nhttp://stackalytics.com/?metric=commits&release=all&user_id=numansiddique\nhttps://github.com/openvswitch/ovs/commits?author=numansiddiqu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Numan Siddique (~numan)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-introduction-to-openflow-and-openvswitch~aQKGd/", - "title": "An introduction to OpenFlow and OpenvSwitch" - }, - { - "Content URLs": "https://speakerdeck.com/aravindputrevu/introduction-to-application-performance-monitorin", - "Description": "Often late, the time to debug that particular bug/issue occurring in production with respect to your application is increasing. It might also cause business disruption and affect your organization financially. In this talk, I'd explain how you could use Application Performance Monitoring to understand your application. Application Performance Monitoring (APM) is a solution built on Elastic Stack. APM helps you to build/store data points in Elasticsearch and visualize. It automatically collects information from your python application/service. This talk mainly targets at introducing the solution, why it is needed and what you can do with data. It ends with once data is stored within Elasticsearch, what else you can use the same data for (ex. Infrastructure Monitoring, Machine Learning)? Agenda What is APM?\nWhy APM?\nWhat it can do to your Application?\nDem", - "Last Updated": "28 May, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "Aravind is a loquacious person, who has something to talk about everything. He is passionate about evangelising technology, meeting developers and helping in solving their problems. He is a backend developer and has six years of development experience. Currently, he works as a Developer Advocate At Elastic and interact with developer community in South East Asia and India. He has deep interest in Machine Learning, Security Incident Analysis and IoT tech. In his free time, he plays around Raspi or a Arduino", - "Speaker Links": "https://aravindputrevu.in will have links to all my social accounts. I have been doing community work for last 3 years. Presenting the same talk at PyCon Bangkok on June 16-17. https://th.pycon.org/talks/#monitoring-your-python-applicatio", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aravind Putrevu (~aravind34)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-your-python-application~eV2ze/", - "title": "Monitoring your Python Application" - }, - { - "Content URLs": "I will share the slides on my github repo for the evaluation by the team in some days.\nOther content will be shared on github after the talk", - "Description": "Training a machine learning / deep learning model is one thing and deploying it to a production is completely different beast. Not only you have to deploy it to a production, but you will have to retrain the model every now and then and redeploy the updates. With many machine learning / deep learning projects / POCs running in parallel with multiple environments such as dev, test prod, managing model life cycle from training to deployment can quickly become overwhelming.\nIn this talk, I will discuss an approach to handle this complexity using Docker and Python.\nRough outline of the talk is, Introduction to the topic Problem statement Quick introduction to Docker Discussing the proposed architecture Alternative architecture using AWS infrastructure Demo", - "Last Updated": "28 May, 2018", - "Prerequisites": " Basic Python Basic Docker", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company.\nI have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures.\nSince past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "saurabh1deshpande", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-devops-and-ab-testing-using-docker-and-python~bWKEb/", - "title": "Machine Learning DevOps and A/B testing using docker and python" - }, - { - "Content URLs": "https://docs.microsoft.com/en-us/python/api/overview/azure/?view=azure-pytho", - "Description": "Python SDK for Azure is natively available. We would explore how this SDK can be used for automation and management of Azure. Python makes it easier for IT Pros and Developers to build a rock solid DevOps pipeline with simple script", - "Last Updated": "28 May, 2018", - "Prerequisites": "Basic understanding of Azure or any cloud\nBasic Python knowledg", - "Section": "Developer tools and Automation", - "Speaker Info": "Wriju works for Microsoft as Cloud Solution Architect. He is with Microsoft for more than 13 years and total of 17 years of industry experience. He is one of the first to play with Azure in its very early stage back in 2008. His day to day job is to help a big Oil and Gas Enterprise to adopt cloud as the strategic platform. His key area of focus is to help customer migrate their line of business applications to Microsoft Azure. Application modernization is another aspect. This involves designing and implementing Serverless workflow and Microservices. He helps Architects to design and implement the solutions which are cloud scale", - "Speaker Links": "Twitter handle: @wrijugh\nBlog: https://blogs.technet.microsoft.com/wriju\nLinkedIn: https://www.linkedin.com/in/wrijughosh", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Wriju Ghosh (~wriju)", - "created_on": "28 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-and-automating-azure-with-python~eXXve/", - "title": "Managing and Automating Azure with Python" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of my Github Repository", - "Description": "Artificial Intelligence is spreading in the modern world and it has changed the face of technologies in past several years, especially Information technology. Today we are much engaged with using and developing so-called intelligent computing systems and devices. This paradigm has evolved in many sub-areas likewise Machine Learning, Deep Learning & Neural Networks. These sub-areas of AI have a greater role in solving Vision problems( e.g. image recognition, object & activity detection etc.), Speech problems( e.g. ASR, trigger word detection, language translation etc.) and many more complex problem domains with help of robust algorithms & models. this talk will be focused on Sequence Neural Models used for solving the Speech and text problems and we will be introduced to real-world applications. topics covered during the talk Introduction Recurrent Neural Networks Word embeddings Attention Models(Trigger word detection) Real World Applications", - "Last Updated": "29 May, 2018", - "Prerequisites": "Machine Learning\nBasics of Neural Networks\nPython Programming Machine Learning( Basics) Basics of Neural Networks Python", - "Section": "Data science", - "Speaker Info": "The speaker, Prashant Kumar Rai, is a final year M.C.A. student at Department of Computer Science (Pondicherry University, Puducherry) who has been working on Machine Learning and data science for quite a while. he pivoted from C to Python in his first year of Master's and currently using this for his projects. He used to blog at his leisure time. Prashant is also a course mentor for 'Sequence Models' part of Prof. Andrew Ng' s Deep Learning Specialization on Coursera, where he helps learners who need in-course assistance and feedback to successfully complete a course", - "Speaker Links": "Github Twitter Quora LinkedIn Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "PRASHANT KUMAR RAI (~pkraison)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/follow-the-sequence-in-deep-way-introducing-sequence-models~bYYAb/", - "title": "Follow the Sequence in Deep way - Introducing Sequence Models" - }, - { - "Content URLs": "Slides Repositor", - "Description": "I'll be sharing how Python has been of help in my transformation from a hobby developer to a researcher.\nCoding and in particular, simulations are used extensively in the field of research to verify results and sometimes serve as experiments when it is physically not feasible. I'll describe step by step, how to design a real-time simulator using the example of an aerial swarm of drones in a survivor rescue scenario with the help of common Python libraries", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic understanding of Python classes and objects Enthusiasm to learn something new Love for Python", - "Section": "Core python and Standard library", - "Speaker Info": "Aniq Ur Rahman, Final year undergraduate student from NIT Durgapur. Summer '18 Research Intern at CERN GSoC '17 Intern at RoboComp Summer '17 Research Intern at SWAN Labs, IIT Kharagpur", - "Speaker Links": "Linked In Blo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aniq Ur Rahman (~Aniq55)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-research~eZGQa/", - "title": "Python and Research" - }, - { - "Content URLs": "https://github.com/hasura/gitkub", - "Description": "Gitkube is an open-source project that brings the developer experience of Heroku, on your own kubernetes vendor within 60 seconds . This means that you can take your python app, deploy it with a git push & scale it massively all on infrastructure you own at a fraction of the cost on Heroku. After a brief introduction, this talk will be a live-coding demo + tutorial. \nAudience members are encouraged to bring their own laptops with python apps and follow along in the talk to deploy their app. Permitting time, the talk will cover how gitkube works and how developers can contribute", - "Last Updated": "29 May, 2018", - "Prerequisites": "Python\nGi", - "Section": "Developer tools and Automation", - "Speaker Info": "Tanmai runs a startup, Hasura, where they're building tools to make it easier for developers to move to GraphQL and Kubernetes. \nThey were early adopters in the container ecosystem (pre-1.0 adopters for both Docker and Kubernetes) and have grown and contributed to the ecosystem as a company especially in India. Before this, Tanmai ran a consulting firm where their work included everything from MVPs for startups to helping one of the largest banks in the world migrate from legacy monoliths to containerised microservices. Tanmai has been building applications for over 8 years with a variety of frameworks. He is a firm advocate of democratising the power to develop applications and is the proud teacher of one of the largest tech MOOCs in India, imad.tech", - "Speaker Links": "Kubecon talk on gitkube: https://www.youtube.com/watch?v=gDGT4Gf_4JM Hasura: https://hasura.io LinkedIn: https://www.linkedin.com/in/tanmaig/ Twitter: https://twitter.com/tanmaig", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Tanmai Gopal (~tanmai)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demo-tutorial-git-push-to-deploy-your-python-app-to-kubernetes-heroku-style~e1pZd/", - "title": "Demo + tutorial: Git push to deploy your python app to kubernetes - heroku style!" - }, - { - "Content URLs": "Content will be shared on github after the workshop. I will share detailed plan for the workshop in a while for the review", - "Description": "Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero ( https://deepmind.com/blog/alphago-zero-learning-scratch/ ). \nOpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms. In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding. Content Introduction to Reinforcement Learning (~ 15 mins) Introduction to Reinforcement Learning algorithms (~ 15 mins) Setting up OpenAI Gym and other dependencies Implementing simple algorithm using one of the atari games from OpenAI Gym (~ 1 Hr 15 mins) Quick overview of deep reinforcement learning and important papers in the area (~ 15 mins)", - "Last Updated": "29 May, 2018", - "Prerequisites": "Participants must be well versed with python. Some exposure to analytics libraries in python such as numpy, pandas, keras, tensorflow, pytorch would help", - "Section": "Data science", - "Speaker Info": "My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company. I have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures. Since past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow", - "Speaker Links": "https://www.linkedin.com/in/saurabh1deshpande", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "saurabh1deshpande", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-reinforcement-learning-using-openai-gym~b2qMa/", - "title": "Introduction to reinforcement learning using OpenAI Gym" - }, - { - "Content URLs": "I'll be sharing the slides after my talk as a Github repository. Soon will be sharing a gist", - "Description": "Abstract One of the feature people love about Python is how it\u2019s dynamically typed. A lot of people are very reluctant on hearing this idea of static typing, they will come back bashing on what's the use of Python then when we introduce static typing in it. With the torch bearers of Python in the industry like Google, Quora, Instagram, and a lot of others retaining their stack on Python and introducing static checking there have to be some non-superficial benefits, which are worth discussing. This is Python class Employee(NamedTuple):\n name: str\n id: int = 3\n\ndef fib(n: int) -> Iterator[int]:\n a, b = 0, 1\n while a < n:\n yield a\n a, b = b, a+b Contents of the talk What's static typing Need of static typing Static typing in Python 3.6 Type checkers Demo mypy vs pytype Pros and Cons QnA and discussion", - "Last Updated": "29 May, 2018", - "Prerequisites": "Basic Python knowledge and a little overview of what is dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Harshil Rastogi is working as a backend software engineer @Innovaccer, previously he has worked as an NLP Scientist @Evalueserve", - "Speaker Links": "Find me on github , ohh you like QnA forums stackoverflow . Oops were you looking for a professional platform? Okay, LinkedIn it's", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harshil Rastogi (~harshil9968)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/static-typing-with-python-what-why-and-why-not-to~e3rAd/", - "title": "Static typing with Python. What? Why? and Why not to." - }, - { - "Content URLs": " https://fasttext.cc/ https://github.com/PacktPublishing/Learn-fastText https://github.com/facebookresearch/fastText/tree/master/python", - "Description": "FastText has been open-sourced by Facebook in 2016 and with its release, it became the fastest and most cutting edge library in Python for text classification and word representation. It is to be seen as a substitute for gensim package's word2vec. It includes the implementation of two extremely important methodologies in NLP i.e Continuous Bag of Words and Skip-gram model. Fasttext performs exceptionally well with supervised as well as unsupervised learning. The tutorial will be divided in following four segments : 0-10 minutes: The talk will begin with explaining common paradigms that are present right now. Are deep learning really necessary? 10-15 mins: what are word representations 15-25 minutes: The code will be shown and explained line by line for both the models (CBOW and Skip-gram) on a standard textual labelled dataset. Showing how you can do fast prototyping with minimal code. 25-30: How to use the pre-trained word embeddings released by FastText on various languages and where to use them. Why python3 is the best language for multi-language support and a note on general deep learning using fasttext. 30-40 minutes: For QA session. ", - "Last Updated": "29 May, 2018", - "Prerequisites": " Basic python knowledge. Some Knowledge on common NLP techniques.", - "Section": "Data science", - "Speaker Info": "Joydeep is a machine learning engineer/python developer and is a Principal Engineer at Nineleaps. 5 years back he saw the Zen of Python, fell in love with Python and has been in love with it since then. Apart from his day to day work is involved in blogging and podcasting on medium and flawcode. Teaching is another passion of his and he is a python/ML trainer at tecmax", - "Speaker Links": " Medium: https://medium.com/@joydeepubuntu/latest Github : https://github.com/infinite-Joy LinkedIn : https://www.linkedin.com/in/joydeep-bhattacharjee-934a1157/ Machine Learning Podcast: https://flawcode.com/episode/show/12 twitter: https://flawcode.com/episode/show/12", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Joydeep Bhattacharjee (~infinite-Joy)", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cutting-edge-nlp-classifiers-in-one-hour-with-python-and-fasttext~b4v7e/", - "title": "Cutting edge NLP classifiers in one hour with Python and fastText" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1PZ56AYSH6GZ8s-V8rfxHuZ16UCmDg03Y1L2EiTCBiUs/edit#slide=id.p \n(Subjected to changes, not final one)", - "Description": "Talk is about how python is useful in web development, what are the most powerful and popular python frameworks used i.e., Django, Pyramid, Flask and how they are used in making web applications. My talk covers : What a web framework means Why to choose python frameworks over the normal other frameworks Explanation on Django, Pyramid, Flask. Which framework should be chosen based on dependencies. Starting Web development with python. Django, Pyramid, Flask will be explained in short with the help of small code snippets. Examples of organizations using these frameworks will be given. Uses of one framework over the other will be told in detail", - "Last Updated": "29 May, 2018", - "Prerequisites": "No prerequisite is required. Desire to learn is enough to attend this talk", - "Section": "Web development", - "Speaker Info": "About Me I am Jameer, a third year Computer Science and Engineering undergrad at Amrita Vishwa Vidyapeetham, Kerala, India. I love to code in Python. So, I started my open source career by contributing to Coala organisation. Due to my open source enthusiasm, I started learning how python is useful in Web development and using Django, Flask etc., I am also an OSFY author and published an article related to how Hadoop is being used in Big Data Analysis. I am also a ACM-ICPC Regional participant at Amritapuri. I also have a keen interest in Chatbots", - "Speaker Links": "https://github.com/JameerBabu https://www.linkedin.com/in/jameer-babu-0199a2137", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Jameer", - "created_on": "29 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-web-development~e5wYb/", - "title": "Python - Web Development" - }, - { - "Content URLs": "I will share the slides after my talk as a Github repository", - "Description": "If you are working in the field of research than you might be wondering about symbolic solutions which must be needed while working in such arduous fields like Mechanical Engineering or Computer Science or Quantum Mechanics. Sympy is the solution for that. Sympy deals with the computation of mathematical objects symbolically. This means that the mathematical objects are represented exactly, not approximately, and mathematical expressions with unevaluated variables are left in symbolic form. This talk will cover Introduction and Uses of Sympy Library", - "Last Updated": "30 May, 2018", - "Prerequisites": "Basics of Python is good. \nDon't know Python? It's still okay. You will definitely find something new", - "Section": "Core python and Standard library", - "Speaker Info": "Nikunj Parmar is a Sophomore year student at Nirma University. His major field is Flexible Robotics. He has been working with Python for last 2 Years as a Researcher. As a Junior Undergraduate student, He has worked on many projects focused on Robotics, Machine Learning, and Core OS Programming. His interests lie in the fields of Robotics, Design and Control Engineering, Computational Engineering, and its applications in a broad range of circumstances", - "Speaker Links": "https://www.linkedin.com/in/nikunj-parmar-b87739138/ https://github.com/nikunjparmar82", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Nikunj Parmar (~nikunjparmar828)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sympy-symbolic-computation-with-python~b6xOe/", - "title": "Sympy : Symbolic Computation with Python" - }, - { - "Content URLs": "https://github.com/aj-jeste", - "Description": "Google Cloud Platform Deployment Manager (GCP DM) allows you to codify your infrastructure with minimal setup, just need to download the gcloud library and you're off to the races. While its simple to get started with GCP DM, its a whole 'nother ball game to write extensible and reusable DM code. In this talk I will show you how to scaffold your code into two distinct groups: configs and templates. By separating these out you can reuse the same templates across multiple deployments with different configs and make your codebase a little bit smaller. How to write a basic DM deployment. Convert the basic DM deployment into a template. Launch multiple deployments with different configs but same template. Create custom helper functions in DM Best practices when using DM", - "Last Updated": "30 May, 2018", - "Prerequisites": "Understanding of Google Cloud Platfor", - "Section": "Developer tools and Automation", - "Speaker Info": "As a freelance Site Reliability Engineer and Cloud Architect, AJ has traveled all over the world helping startups setup and manage Cloud infrastructure. He has also architected and deployed large Hybrid on-prem/cloud infrastructure for existing well established companies that wanted a taste of the cloud but needed to keep their physical data-centers as well. This is his 11th year as a SRE/CA and has automated, scaled and monitored infrastructure anywhere from 150 to 3500+ nodes, both physical and virtual. Currently he is looking for his next challenge, perhaps its this pycon talk. Brought up and currently lives in New York City but travels all over the world in search of the best train journeys and awesome foods which seems to bring him back to India again and again", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "aj", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-cloud-platform-deployment-manager-scaffolding~b8zje/", - "title": "Google Cloud Platform Deployment Manager Scaffolding" - }, - { - "Content URLs": " https://github.com/errbotio/errbot http://errbot.io/en/latest/", - "Description": "The wikipedia definition of ChatOps is, a collaborative, conversation-centric way of working that brings people, discussions, bots, tools and files together in one central location: the workplace messaging app. That's it! That's what exactly I am gonna talk about. I am gonna talk about Chatops bot, Errbot which is written in python and can be used across various messaging apps like Hipchat, Slack, telegram, skype, etc. Using chatops one can automate the tedious, boring tasks and let the bot do the work for you. It also enables various engineering teams to collaborate and exchange information easily at one place: their official messaging app. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce chatops - culture, uses, possibilities. I will talk about the possible scenarios where we could use chatops in our daily tasks. I will then introduce Errbot and its plugin architecture. Tell audience about various features of errbot and its builtin plugins. Demonstrate errbot to audience by creating a command and using it in Slack. How to set up a alternate storage for errbot. I will conclude the talk explaining the ACLs(Access control List) in errbot.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic Python Passion for automation Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatops-using-python-bringing-developers-and-operations-together-making-tasks-easier~e9AJe/", - "title": "Chatops using Python - Bringing developers and operations together, making tasks easier!" - }, - { - "Content URLs": " https://www.djangoproject.com/ http://www.celeryproject.org/ https://sensu.io/", - "Description": "Monitoring is a key aspect for any business. It enables us to find and be notified about the problem way ahead our customer notices it, which enables us to keep our businesses running and making customers happy. I will be talking about how we SREs at Opentable Inc, tries to solve the good old monitoring problem, sensu with puppet, using Django, Sensu and Celery. If you are fed up with the limitations of what current monitoring tools offer, this is the talk you wanna look out. At the end of talk, audience would have an alternative approach for monitoring using python. Contents of the talk: I will start the talk with a brief introduction of myself and my journey with python. Introduce monitoring and how we use currently at Opentable Inc. Describe limitations we have with our previous monitoring stack. Alternate new generation monitoring architecture using python tools Django and Celery, keeping sensu intact. How we developed a site using Django, which help us to maintain the checks and add new check definition. How we used Celery distribution system to run checks on multiple worker nodes and send results to sensu. I will talk about how we scaled celery worker nodes by setting up different queues, and prioritising the tasks and by using Flower.", - "Last Updated": "30 May, 2018", - "Prerequisites": " Basic knowledge of Sensu. Basic knowledge of Django and Celery. Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "My name is Hari Kishore Sirivella. I have good experience with different verticals like testing, developing, devops and SRE in my 4 years of IT profession. I like to explore technology and reinvent myself, started as a manual tester in TCS, to selenium automation tester, to devops engineer, to my current role Site Reliability Engineer at Opentable. Passion towards development and will to learn operations, made me travel across various verticals and eventually land as SRE, where I get to work on both worlds - develop products and maintain them. As a selenium automation tester, I used to work on core Java and was introduced to python just 8 months back, with a task to introduce chatops in my organisation. I have developed and led a team, Voice based web browser as my final year project in my engineering, where you get to browse the internet , bookmark a page, navigate previous and next pages using your voice commands. The browser also reads out text enabling differently challenged persons to use it seamlessly. I work on lot of open source projects. I'm also a Machine Learning and Data Science enthusiast", - "Speaker Links": "https://www.linkedin.com/in/hari95kishore", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "hari95kishore", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/monitoring-infrastructure-and-application-using-django-sensu-and-celery~e0o5d/", - "title": "Monitoring infrastructure and application using Django, Sensu and Celery." - }, - { - "Content URLs": "The Magenta Project Music Composition using Recurrent Neural Network", - "Description": "Music is mainly an artistic act of inspired creation and is unlike some of the traditional math problems. But, a sequence of specific chords and notes can be observed when we listen to music. With the recent advancements of the AI tech, sequence models are used invariably in innumerous fields, one such sequence model, LSTM( Long Short Term Memory Networks) can be used to generate melodies and beats. So, this talk is about how deep learning models, specifically LSTMs were used to produce music - catering particularly to the Electronic Dance Music Industry. CONTENTS AND ORDER OF THE TALK Learning how LSTMs help in generating music, and the concepts behind it. Preprocessing the MIDI data for the melodies and beats using MIDI packages created by the Python community. Building the LSTM network using Keras with Tensorflow as backend and understanding it. Train the network with the melodical data to create the LSTM network for melodies and same thing for beats. Generating melodies and beats(using pretrained model) and combining the two to create different type of genres of music. I am including a piece of music generated by an MIT alumnus, but I will be explaining the steps from scratch . Generated Techno Beat", - "Last Updated": "30 May, 2018", - "Prerequisites": "Tensorflow, Keras, Recurrent Networks and a Good taste in music ;", - "Section": "Others", - "Speaker Info": "I am Kumar Abhijeet, a sophomore from RV College of Engineering, Bengaluru and an AI enthusiast. I am a budding EDM producer and a python programmer as well(no doubt in that). I have worked with small AI startups in building their frameworks. I am an open source contributor and a GSOC aspirant. I have always loved the idea of mixing technology with regular phenomena, which I will be doing with music. I love going to meetups and meet different kinds of communities to learn from them", - "Speaker Links": "LinkedIn ID Github Lin", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kumar Abhijeet (~kumar80)", - "created_on": "30 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-beats-and-melodies-with-lstms-using-python-and-tensorflow~ejgya/", - "title": "Generating beats and melodies with LSTMs using Python and Tensorflow" - }, - { - "Content URLs": "To get a feel of Numba see - first step", - "Description": "Thinking parallel is an art, applying it is another. While applying it, the first hurdle for us is to move to another language like C or C++ to get performance gains. \nWhat if we write simple python code and someone magically helps us gain C like performance? Sounds like a dream, it ain't ! . Enter Numba :) In this workshop you will - Witness how Numba help you get insane performance gains to your code without changing a line of it. Learn to harness the power of your GPU/CPU for performing math intensive computations. See how it compares to other libraries like Numpy , etc. and how they can complement it. Use Numba to parallelize the very famous Particle Swarm Optimization Algorithm Flow of the workshop - Where to use Numba in your code - (time profiling, small examples) The wow of Numba in my life, a small example of how it helped in my research Introduction to jit complier, internals of Numba Introduction to the Particle Swarm Optimization (this is where the fun starts :) ) Code up basic PSO Profile PSO to find pain areas Try to speed up the pain areas using Numba Kick up a hierarchical swarm (just for fun, if time permits) QA Session", - "Last Updated": "31 May, 2018", - "Prerequisites": "numpy, matplotlib, jupyter, ipython, numba, line_profiler , llvmlite. A more specific description is available her", - "Section": "Others", - "Speaker Info": "Hi, I am Shubham Bhardwaj. I am currently a Research Intern at Jio CoE for AI/ML and a final year undergrad at VIT University, Vellore. I am a die-hard pythonista. \nMy daily work involves developing and implementing algorithms for interesting problems in AI. Apart from this I am also an organizer at GDGVIT, I love dev :) and contribute to various open source organisations, organise workshops, promote python whenever I can", - "Speaker Links": " LinkedIn Github", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Shubham Bhardwaj (~shubham0704)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/leveraging-the-power-of-your-gpucpu-for-math-intensive-computations-with-python~bkjJa/", - "title": "Leveraging the power of your GPU/CPU for math intensive computations with python" - }, - { - "Content URLs": "https://github.com/radhikascs/cryptography-pytho", - "Description": "This talk is meant for the end users who aspire to learn basics of cryptography and its implementation in real world projects. \nThis tutorial is also useful for networking professionals as well as hackers who want to implement new frameworks instead of following traditional approach", - "Last Updated": "31 May, 2018", - "Prerequisites": "It is expected that the end user should know basics of cryptography and algorithms. The knowledge of cryptography algorithms becomes a cakewalk for a user who reads this tutorial", - "Section": "Core python and Standard library", - "Speaker Info": "A pinch of optimism with a blend of hard work and focus defines Radhika Subramanian. She works as an Academic Writer and Tutor with various organizations. She has completed MSc(CA) from Symbiosis International University. She also includes a passion for research work in Artificial Neural networks and it's technologies. She is currently working as an Author with BPB Publications and Apress Media LLC", - "Speaker Links": "https://www.linkedin.com/in/radhika-subramanian-486a771a/ https://www.unanth.com/tutor/radhika-subramanian-14135", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Radhika Subramanian (~radhika14)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cryptography-and-python~elkjd/", - "title": "Cryptography and Python" - }, - { - "Content URLs": " Postman Jmeter Burp", - "Description": "API testing is fun! For a small team of 7 (Dev + QA), having dedicated resources to do functional, Security and Performance of the APIs is close to impossible.\nHence, We came up with a framework which automates the process of API testing covering the basic functionality, Security, and Performance so that we don't miss out testing any of these layers. I would cover up the basics of Postman, Burp and JMeter components used for the framework", - "Last Updated": "31 May, 2018", - "Prerequisites": " Interest in automating the Webservices testing :)", - "Section": "Developer tools and Automation", - "Speaker Info": "A tech enthusiast who has 7+ years of experience in the Software Testing in Startups. I love to explore new technologies and automate mostly everything which takes more time. A strong believer in processes. Love testing Webservices. Would love to share the experience we had in building the framework for API testing", - "Speaker Links": "https://www.linkedin.com/in/sarala-v-620b0b1a/ https://twitter.com/saralaVeerann", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sarala V (~sarala)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-rest-api-testing-for-functional-security-and-performance-testing~bmkRe/", - "title": "Automating REST API testing for functional, security and performance testing" - }, - { - "Content URLs": "Slides: https://docs.google.com/presentation/d/1z-pWhSOERi-vl_wPLVsdCNpl54G3IA0D8K7ve13HFZI/htmlpresent Source code for the examples: https://github.com/minhajuddin/collaborative-canvas-demo", - "Description": "Outline/structure of the Session\n1. An introduction to Elixir\n2. An introduction to Phoenix\n3. Outline and design overview of our canvas app\n4. Implementing our app\n5. Deploying it to a server\n6. Q&A Learning Outcome\nLearn how easy it is to use Elixir and Phoenix to create real time applications at a massive scale", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic understanding of the web applications", - "Section": "Web development", - "Speaker Info": "I am a very passionate programmer. I am also the CEO of a Micro ISV, Cosmicvent Software. I have been in the software industry for 10 years.I love writing code and have worked with Elixir, Golang, Ruby, .NET and Javascript among other technologies", - "Speaker Links": "Follow me on twitter https://twitter.com/minhajuddin Follow me on GitHub https://github.com/minhajuddin/ My Blog: https://minhajuddin.com/ Previous presentation: https://www.youtube.com/watch?v=WabGxSZhPE", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Khaja Minhajuddin (~minhajuddin)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-collaborative-canvas-using-elixir-and-phoenix~enl5b/", - "title": "Building a collaborative canvas using Elixir and Phoenix" - }, - { - "Content URLs": "https://www.py4e.com/\nhttps://www.coursera.org/specializations/pytho", - "Description": "This session will take a look at the \u201cPython for Everybody\u201d series of courses on the Coursera platform. This course has impacted over 1.3 million students over the last five years. We will look a the history and goals of the course and how the course works to create a learning community. We will show how the free open educational resources (OERs) and book associated with the course have been used by teachers, students, and courses around the world to form a network of educational activities centered around Python. We will also cover briefly the Tsugi (www.tsugi.org) software that is used to build the learning assessments and distribute the OER materials in a way that enables maximum reusability of the materials for other teachers", - "Last Updated": "31 May, 2018", - "Prerequisites": "No pre-requisite", - "Section": "Core python and Standard library", - "Speaker Info": "http://www.dr-chuck.com/\nhttps://www.si.umich.edu/people/charles-severance\nhttps://twitter.com/drchuck/\nhttps://github.com/csev\nhttps://www.sakaiproject.org\nhttps://www.tsugi.org\nhttps://www.slideshare.net/cse", - "Speaker Links": "http://www.dr-chuck.com/dr-chuck/resume/index.htm Charles is a Clinical Professor and teaches in the School of Information at the University of Michigan. He is the Chair of the Sakai Project Magament Committee (PMC). Previously he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project and worked with the IMS Global Learning Consortium promoting and developing standards for teaching and learning technology. Charles teaches ten popular MOOCs and two specializations to students worldwide on the Coursera platform: Internet History, Technology, and Security, Web Applications for Everybody, and Python for Everybody and is a long-time advocate of open educational resources to empower teachers. Charles was the editor of the Computing Conversations column in IEEE Computer magazine from 2011-2017 that features a monthly article and video interview of a computing pioneer. Charles is the author of several books including: Python for Everybody, Sakai: Building an Open Source Community\", \"Using Google App Engine\", from O'Reilly and Associates and the O'Reilly book titled, \"High Performance Computing\". Charles has a background in standards including serving as the vice-chair for the IEEE Posix P1003 standards effort and edited the Standards Column in IEEE Computer Magazine from 1995-1999. Charles is active in media as a hobby, he has co-hosted several television shows including \"Nothin but Net\" produced by MediaOne and a nationally televised program about the Internet called \"Internet:TCI\". Charles appeared for over 10 years as an expert on Internet and Technology as a co-host of a live call-in radio program on the local Public Radio affiliate (www.wkar.org). Chuck's hobbies include off-road motorcycle riding, karaoke and playing hockey. Charles has a B.S., M.S., and Ph.D. in Computer Science from Michigan State University", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Charles Severance (~charles)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/inside-the-worlds-largest-python-course-on-coursera~bomYe/", - "title": "Inside the World's Largest Python Course on Coursera" - }, - { - "Content URLs": "---In progress, will be ready to share by July last week can make it to July first week if urgent--", - "Description": "Signal processing is a fundamental part of ECE and is also used in many other fields. Students for years have been using expensive Matlab for learning this skill. The talk/workshop/interactive session can be used by students to get a better understanding of signal processing and implementing it with python. The use of python language in signal processing is preferred as it is portable, easily available and fast to deploy Topics covered include but are not limited to Sound and Signals Noise Fourier Transform Filtering Modulation Sampling LTI Systems The talk will be at a simple level so that even a high school student can understand signal processing and implement it. If time allows another session on using python to solve electrical networks and visualizing them can also be implemented", - "Last Updated": "31 May, 2018", - "Prerequisites": "Basic knowledge of python and Signals and systems (WikiPedia knowledge is enough.) NumPy (Used for array manipulation ) SciPy (For computation) matplotlib (For plotting various signals etc.)", - "Section": "Others", - "Speaker Info": " Speaker is a 3rd year ECE student with experience in python for numerical computations, web development and most importantly signal processing , and electrical networks Interested in using python in modern electronics like the pyboard and raspberry pi and advocates the use of python over expensive software. An avid python user, always tries to find a way to implement given task in python and believes that where there is a task to be done there is a suitable python library.", - "Speaker Links": "LinkedIn Faceboo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Abel Joseph John (~abel91)", - "created_on": "31 May, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/digital-signal-processing-with-python-and-applications-in-audio~epnQb/", - "title": "Digital Signal Processing with Python and Applications in Audio" - }, - { - "Content URLs": "Kubernetes Docker Azure Kubernetes Service aka AK", - "Description": "Kubernetes is considered as the new Kernel of the Cloud. It's a distributed computing platform letting users not have to care about infra and helping them concentrate mainly on business logic. By having your web app deployed on a kubernetes cluster you can make sure your app is highly available, and can fail-over when there's a problem. One of the main goals of the Kubernetes project is to democratize distributed computing. With Kubernetes being open source, Companies do not have to redo the mundane task of writing a distributed computing platform to achieve high availability, automated deployment, scaling and management of your applications. Kuberentes will take care of that for you. Kubernetes is also considered as a container orchestrator, as it manages containers to achieve the above said goals. In this talk: We will first write a basic python web app. Next, We will go through what a container is Containers are becoming the de-facto way of deploying applications as they remove the complexities of dependency management,etc. Running apps on Individual Containers provide the isolation almost to that of a Virtual Machine without having the overhead of having individual Kernels as they all share the host kernel. Isolation is provided by using kernel level features like cgroups and namespaces. We will containerize the application using docker and push it to a Container Registry. Once we have the image deployed to a registry, this image will be used to create instances i.e containers of the web app. We will next create a kubernetes cluster on Azure, all along going through what a Kubernetes cluster is, and its components. We will then deploy our python web app onto the cluster. Now As we have our python web app up and running, We can then do some experiments on how Kubernetes self-heals the application when a node goes down,etc. After that I will run down some points on where Kubernetes is being\n used, its impact. To Finally answer the question, Is Containers and Kubernetes worth all the Hype ? This talk will be demo focused, But before going to a demo we will have some slides explaining the overview of the components and how they work. By the end of the talk, Audience will have a brief overview of what containers and kubernetes are, and how to deploy a web app on Kubernetes. From this overview, Audience can start digging deeper online and know more", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Understanding of Python. Basic Understanding of Deployment of a web app. It's good if you already have some basic understanding on what containers and kubernetes are", - "Section": "Developer tools and Automation", - "Speaker Info": "Tarun Pothulapati is currently pursuing his B.Tech in Computer Science and Engineering in Hyderabad.\nHe is a Tech Enthusiast and codes mostly in Python and C#. He is very much interested in distributed computing platforms like Kubernetes and Microsoft's Service Fabric which are trying to democratize \nthe technology which was before only a privilege of the Big-Tech firms.\nHe spends most of the time learning about it and trying to contribute to their repositories. He is also very enthusiastic about sharing the knowledge about these cutting edge technologies.\nTarun has also worked on many projects on chatbots, Web apps etc and have won some\nhackathons held by IEEE, IBM & Amazon and he was one of India's 40 finalists of AICTE's \nStartup Contest 2017", - "Speaker Links": "Twitter Github Linkedin Websit", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Tarun Pothulapati (~Pothulapati)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deploying-a-python-web-app-onto-a-kubernetes-cluster~bqo7e/", - "title": "Deploying a Python web app onto a Kubernetes Cluster" - }, - { - "Content URLs": "https://github.com/vivekaris/firebase-io", - "Description": "Now Days Internet of Things are Trending technology for every makers. Lets Build Python based Automation controller for any Hardware (tested on Raspberry Pi and Node MCU).\nWe will use firebase as a data storage and Action handling.\nWith the help of Firebase Realtime Database ,we can control hardware from any geographical location", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Keen to learn Basic of Python Knowledge of PIP Knowledge JSON Basic Knowledge of C for Arduino(Node MCU Programming) Laptop with Linux/Mac/Win 7 onwards. Node MCU v3 2 LED with 4 Jumper Wire Internet Connectivity Google Account enter code her", - "Section": "Web development", - "Speaker Info": "I am opensource tech lover", - "Speaker Links": " https://github.com/vivekaris https://twitter.com/vivdroid http://makerspacekanpur.com/blog/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-and-firebase-build-amazing-iot-application~erp2b/", - "title": "\"Python and Firebase\" Build Amazing IoT Application" - }, - { - "Content URLs": "share here soon", - "Description": "Flutter is Google\u2019s mobile app SDK for crafting high-quality native interfaces on iOS and Android in record time. So lets create web services for Flutter app using python/Flask framework", - "Last Updated": "01 Jun, 2018", - "Prerequisites": " Basic of Python Knowledge of Webservices REST and JSON Hello world Knowledge of Mobile App. Familiar with Android Studio and Pycharm", - "Section": "Web development", - "Speaker Info": "I am opensource lover. I love to explore opensource technologies for mankind. I am organiser of \"Arduino and IoT ,Kanpur\" . I teach kids under coderdojo program", - "Speaker Links": " https://twitter.com/vivdroid https://github.com/vivekaris", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "VIVEK KUMAR KANAUJIA (~vivek_kumar)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/write-python-web-services-for-flutter-app~avw8b/", - "title": "Write Python Web services for Flutter App" - }, - { - "Content URLs": "Programs in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=", - "Description": "Mention of \u201cCancer\u201d evokes words like tumor, chemotherapy, hair loss, vomiting and pain. Interestingly our knowledge and thereby cancer treatment has changed radically in the past few years and is changing rapidly every passing day. In 2003, human genome was sequenced and for the first time we could read entire human DNA from end to end. Interestingly DNA and cancer are deeply connected. Scientists deciphered that always a change in DNA (mutation) led to cancer (oncogenic mutation). Cigarette smoking, alcohol, pollution etc only led to such DNA change (oncogenic mutations). This led to numerous diagnostic companies starting to extract and sequence tumor DNA, to detect the root cause of each patient tumor. While drug companies formulated new drugs that targeted specific DNA change (mutation). These were called targeted therapies which were very different from chemotherapy in being very precise, less toxic, less side effects and they could be taken orally just like any regular pill. Thus, an oncologist (cancer doctor) could treat a cancer tumor effectively if s/he knew the precise location of mutation in the entire patient tumor DNA and the drug that targeted it. Suddenly oncologists in India and elsewhere, found themselves struggling to comprehend tumor DNA and the technology around it. Already burdened with tomes of ever changing patient treatment guidelines, now they were needed to integrate tumor DNA information to make accurate treatment decisions. For eg. NCCN (National Comprehensive Cancer Network, USA) which publishes treatment guidelines for all cancer for oncologists across the world, published lung cancer guidelines that is 271 pages long. To this, add the complex data of patient\u2019s tumor DNA, various mutation databases, clinical trials and research papers. Modern day oncologist are often overwhelmed. They need tools to simplify and hasten their decision making. I am a molecular biologist who understands the tumor DNA and the technologies around it. As Chief Scientist (molecular oncology) of Neuberg diagnostic lab, I also write patient DNA reports that guide oncologists to take treatment decisions. While meeting various oncologists and marketing them different DNA tests for different type of cancers, I got acutely aware of the problems oncologists faced. To simplify their decision making, I created algorithms that combined patient\u2019s clinical history, histo-pathology data, molecular test decisions, mutational databases and NCCN guidelines. Subsequently I coded these integrated and complex decision algorithms as Python programs that can be executed from a browser. They are available for free and oncologists are/can use it.\nPrograms in Python for lung cancer and colorectal cancers: https://sites.google.com/view/molecularpathology/programming?authuser=0 \nMy article on need of Python programing for cancer treatment: https://sites.google.com/view/molecularpathology/programming/is-it-time-for-precision-medicine-app?authuser=", - "Last Updated": "01 Jun, 2018", - "Prerequisites": "Interest in using programing to resolve healthcare problems in India", - "Section": "Others", - "Speaker Info": "I am a PhD in Biochemistry with significant research experience at the University of North Carolina at Chapel Hill, in the areas of molecular oncology, cardiovascular biology and biology of infectious diseases. Currently, I prepare molecular diagnostic reports for cancer patients as Chief Scientist (Molecular Oncology), Neuberg Center of Genomic Medicine, Ahmedabad", - "Speaker Links": " Molecular pathology of cancer: https://sites.google.com/view/molecularpathology/home?authuser=0 The DNA Labs: https://sites.google.com/site/thednalab/ , https://www.facebook.com/TheDNALab , https://www.youtube.com/channel/UCf2HKt1vgjhe8MXbvMSwELg/feed", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "siddharth srivastava (~siddharth40)", - "created_on": "01 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/helping-oncologists-to-take-complex-decisions-in-treating-cancer~axylb/", - "title": "Helping oncologists to take complex decisions in treating cancer." - }, - { - "Content URLs": " Initial version of slides (will update regularly and mark it complete once done)", - "Description": "Abstract Being one of the most used collaboration tools used by software engineers and data scientists, \"Jupyter Notebooks\" are transforming the way \"data science\" is happening in the industry. Started as a smart Python interpreter, the Jupyter project has grown into a common platform that supports the development of data science and scientific computing tools across multiple programming languages. This talk is aimed at understanding the technical internals of Jupyter project. Agenda A brief introduction to Jupyter How is it different from IPython Component architecture Kernel Frontend Communication protocol used between a frontend and kernel How does a kernel work Magic commands How to create one Let's create a Jupyter frontend Wait! What if you can use Slack as a Jupyter notebook? Jupyter, Interactive computing, and possibilities What will you learn Process that powers an interactive Jupyter session Do you know how does the tab-completion work? Extending the capabilities offered by Jupyter ecosystem for a custom use-case We will learn how to create magic commands and frontend Black magic", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Basic understanding of Python, comfortable with functions/classes Experience working with Jupyter/IPython notebooks (Optional) Interested in knowing how stuff works", - "Section": "Data science", - "Speaker Info": " Tech & Product at Vernacular.ai Data-driven journalism practitioner Featured in Tech in Asia and Global Investigative Journalism Network Contributor to Go programming language", - "Speaker Links": " Website GitHub Twitter", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pravendra Singh (~pravj)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyter-notebooks-internals-and-extension~dyz6e/", - "title": "Jupyter Notebooks: Internals and Extension" - }, - { - "Description": "The goal of this talk is to explain this quote : \u201cYou shall know a \u2018word\u2019 by the company it keeps!\u201d In this talk, we will go through as to how to build a model for text summarisation (from scratch) and its possible applications in the real world scenario. An intuitive explanation will be provided (the talk would not be all mathematical!) as to how to do the data preprocessing for a large dataset and provide a reasoning as to why we choose a specific model for training. We will also talk about how certain Python libraries make it easier to structure a machine learning pipeline. We will also walk through the best practices and various caveats while building these kinds of complex models and how to circumvent these", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "The prospective audience should have a basic understanding of neural networks and natural language processing", - "Section": "Data science", - "Speaker Info": "Harshdeep is currently a student at the University of Manchester pursuing his Bachelors in Artificial Intelligence and is interested in Natural Language Processing. My experience with Python started at IBM Bristol where I worked for a year developing the compliance automation tool. After that, I worked on my final year research project using Python which was based on finding summaries and sentiment of news articles. I have previously spoken at PyCon APAC in Malaysia last year in August which was a talk about the basics of Neural Networks. After university, I will be working with some early stage startups in India related to AI and Aviation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Harshdeep Harshdeep (~harshdeep)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/text-summarisation-made-fun~azAqe/", - "title": "Text summarisation made fun!" - }, - { - "Content URLs": "Slides will be updated soon. Django2 release note", - "Description": "Django is one of the most used Python framework in the world of Python and is even used more than Tensorflow(Stack Overflow 2018 Developer Survey). Django is an excellent web-application framework to build scalable, extensible and high-performance web applications that can serve hundreds of thousands of requests per second -- while keeping the development cycle optimal and maintaining the sanity of developer mind-space. The latest version of Django 2.0 has been just released this year. The new Django 2.0 begins a new era without any backward incompatible changes except the removal of Python2.7 in the latest version and it aims to completely remove Python2 support for Django environment when LTS Django 1.11 expires in 2020 with Python2 . This release also starts the Django using the loose form of semantic versioning. Django 2 has introduced a lot of major changes like : SImplified URL routing syntax Performance optimisation and improvements Mobile Friendly Admin site Newer functions like Windows and more modified aggregate functions\n-Stricter schema Made Mysql isolation as read committed Talk Outlines What is Django and why use Django? Django design patterns - MTV kind of MVC How does Django work? Simplified URL routing syntax in Django2 Other new features in Django2 When should you move your old project to Django2 and Django release Cycle Tips on converting your legacy code to Django2 This talk aims to provide some general insights on Django and latest Django2 version. Apart from being a talk focussed exclusively on Django, the talk aims to give an introduction to what server-side programming is and in general to Web Development", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Python Django (preferable) After all, this is a Hitchhiker\u2019s guide, this talk will focus on a general introduction to Django and don\u2019t be afraid all the noobs in Python and Django will be welcomed and be accommodated in this tal", - "Section": "Web development", - "Speaker Info": "Kurian is currently in his sophomore year, pursuing an undergraduate degree in Computer Science from Govt. Model Engineering College, Kochi. He has interned in multiple startups like Entri.me, WiM as a product intern developing products using Python and web frameworks like Django. He is also a Open source Enthusiast and have contributed to multiple organisation like Zulip , FOSS Asia. He is an active member of FOSS club in his college(FOSSMEC) and of Kochi Python Club(Python Meetup Group of Kerala)", - "Speaker Links": "Github LinkedIn Medium Twitte", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kurian Benoy (~kurianbenoy)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-hitchhikers-guide-to-django-2~aAr9b/", - "title": "The Hitchhiker\u2019s Guide to Django 2" - }, - { - "Content URLs": "PyCon India 201", - "Description": "What's a good way to Set up many development version(s) ? Developers need consistent isolated development environment, running exact same container(s) as what runs in production , automated test tools, package, ship & deliver. Let's touch features of docker to make it run for Python programs/web apps. Outlines First 5 minutes, I'll be talking about current developers need and present solution. Next 5 minutes, what is docker and how it can solve these problems. Next 10 minutes, I'll be demonstrating, how I use docker for in my Python development tasks (Python library, Python web app). After 20 minutes I will have delivered the enough knowledge for the docker, and next 5 minutes I will let the audience know about the some advance features in docker that they can learn from various resources, to get the maximum power of docker. Q/A along with this. Detail description Basic terms of docker Docker Container Docker Image Dockerfile Docker Compose Docker Repository and Docker Hub Docker Daemon, Docker Client and Docker Engine Docker Swarm Docker Machine Docker for Developers Reproducibility and Developer teams Isolation Security Environment Management Continuous Integration Creating Custom Images and Containerizing Your Application Sample Dockerfile to build an image of an small python program. We will run the image and play with this container. Using Docker Compose in development adds an important constraint: your services are not on the same machine anymore. Container Logs Learn how you can see or capture the logs of the container(s) and services. Docker for Python developers In this section I will demonstrate, how you can setup a development version of real world software.\nI will setup the development version. After creating an image and running it in a container, I will show volume sharing techniques as well. Audience will understand how I have created an consistent isolated container, integrated CI which is easy and fast to ship. Docker for Python Web applications Django and Flask web app will be run under the docker container, different environments in one system. We will learn how to use microservices and advantages of making services using docker-compose. Advance and new features of docker Now audience have understood the docker and they can learn many more powerful features of docker. I will share some good resources and let them know about docker swarm, docker machine, Dealing with Logs, etc ", - "Last Updated": "02 Jun, 2018", - "Prerequisites": "Prior experience with docker is not a necessity but having some exposure to Python development, version control system, Unix System is recommended. At the starting talk basic developers need, basic docker features will be covered. So starting point, anyone (entry/intermediate) can understand the docker concepts. Slowly moving to docker for developers, expert Python developers will get ideas to use docker in their development system and how they can solve most of the development conflicts because of using having multiple environments", - "Section": "Developer tools and Automation", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/containerizing-your-application-is-the-solution~dBvQd/", - "title": "Containerizing Your Application is the solution" - }, - { - "Content URLs": "We will share the Github repository for the workshop here couple of weeks before the conference", - "Description": "\"Our Business Is Our Business None Of Your Business\u2026\" Yes, they wish, but we want to know everything about Bollywood! Who is more popular, Katrina Kaif or Deepika Padukone ? Do you think you look like a Bollywood celebrity? Does deep learning thinks the same? :) What movie is the most similar to PK based on the storyline? Which city in India is home of the most active actresses and actors? And lots of other questions. Do you want to know the answers? And even better, would you like to discover them yourself by using Python and popular libraries such as pandas, Gensim, scikit-learn and pytorch? And cutting-edge data science techniques? Join us for a workshop full of insights where you will be able to answer your own questions while learning the most advanced Python libraries and algorithms. The workshop is designed for Python programmers new to data science. Everybody is welcome, but data analysts and people experienced with pandas will find some parts basic. What will we cover? Loading, merging, cleaning and analysing your data with pandas Advanced data visualisation with Bokeh Embeddings and natural language processing with Gensim Basic machine learning with scikit-learn Deep learning building a face extractor and a classifier with pytorch All this while answering the questions above, and letting you answer your own questions", - "Last Updated": "02 Jun, 2018", - "Prerequisites": " Laptop with Anaconda3 installed Clone of the workshop repository Knowledge of Python Good knowledge of Bollywood desirable :)", - "Section": "Data science", - "Speaker Info": "Simmi Mourya is a researcher at IIIT Delhi in collaboration with All India Institute of Medical Sciences. Her work involves developing end to end deep learning pipelines for Multiple Myeloma detection from histopathology images. Simmi is a regular speaker at Python conferences, including PyCon India and Europython, and other conferences like Fossasia Open Technology Summit. She is also a regular open source contributor, including as a Google Summer of Code Student. She is a huge Irrfan Khan fan. Himanshu Awasthi is the organiser of Kanpur Python and PyData Kanpur. Free and open source software enthusiast, and passionate about Python and data analysis, He is currently working for KanpurFOSS organization which organize free technical workshops in India. Yai Workshop\u2026 Data Analysis Ke Workshop Hai\u2026 Kisi Ke Data Analysis sikha kar He Khatam Hoge... Marc Garcia is a pandas core developer. He has worked as software engineer and data scientist for companies like Bank of America, Tesco, Unilever or NTT Communications. He is a regular organiser of sprints, and speaker at PyCon and PyData conferences. His favourite actor is Aamir Khan, but wouldn't mind teaching Python to Asin", - "Speaker Links": "Simmi : https://twitter.com/simmimourya | https://github.com/simmimourya1 | https://www.linkedin.com/in/simmi-mourya-34406886/ Himanshu : https://twitter.com/IHackPY | https://www.slideshare.net/HimanshuAwasthi14/ | https://speakerdeck.com/johim9493 Marc : https://twitter.com/datapythonista | https://www.linkedin.com/in/datapythonista/ | http://datapythonista.github.io", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Marc Garcia (~marc)", - "created_on": "02 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decoding-bollywood-with-python-data-science-and-deep-learning~eEyWe/", - "title": "Decoding Bollywood with Python, data science and deep learning" - }, - { - "Description": "With the advent of Tableau and languages like Python and R, converting raw data into meaningful insights is much easier and convenient than before. Tableau is a tool used to visually represent data and is powerful enough to analyze the given data at any required level. At an industry perspective, the tool comes handy in finding the trends in marketing and sales with a click of a button. Introducing Python to Tableau using TabPy can help define calculated fields in Python, thereby giving it the power to leverage a large number of Machine-learning libraries right from the visualizations. This widens the scope of its applications to any field that deals with big data and its analytics. Optimisation and cross-sharing of data models facilitated by TabPy immensely enhance the efficiency and usability of the tool. With just a few lines of code, we can churn out predictive models and increase the accuracy of future predictions. The talk will primarily focus on: An introduction to data manipulation and visualization using Tableau. An overview of the steps to leverage TabPy in Tableau. The impact and advantages of Tableau-TabPy combination in the real world.", - "Last Updated": "03 Jun, 2018", - "Prerequisites": "A rudimentary understanding of Data Science and Python scripting", - "Section": "Data science", - "Speaker Info": "I am a sophomore undergrad in computer science from Amrita School of Engineering, India of which I am a part of an intra-college FOSS initiative called FOSS@Amrita. Developing small but useful things that improve lives of the common and affects the open-source community has always been my passion. I believe that with the right technology applied, it can do wonders for the lives of people. Furthermore, I have completed the Google Summer of Code\u201917 with The Wikimedia Foundation and was also a Google Code-In mentor for the same community. Worked on the project that aimed at the improvement and enhancement of the ProofreadPage Extension and Wikisource , through important bug fixes that are left as backlog and implementation of significant features that would make it more user-friendly. This was done so that the extension and Wikisource become easier to use and are raised to the contemporary Mediawiki standards. Apart from this, I'd love to \u200bexpress\u200b \u200bviews\u200b on\u200b \u200bcontemporary\u200b \u200bworld issues,\u200b \u200bget\u200b to know\u200b \u200bthe\u200b \u200bdifferent dimensions\u200b of\u200b \u200bit and analyze the\u200b \u200bmultiple\u200b\u200b ways\u200b \u200bin\u200b\u200b which\u200b \u200bthe\u200b \u200bproblems\u200b \u200bcould be rectified", - "Speaker Links": "Linkedin Blog Gerrit GitHu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Amrit Sreekumar (~amrit95)", - "created_on": "03 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-leveraging-python-in-tableau~dGAKa/", - "title": "Data Analysis: Leveraging Python in Tableau" - }, - { - "Description": "The Jupyter ecosystem of tools lets you interleave code and stories for a literate computing experience, where you can visualize your data as html, plain text, svg and images. You could also view the same rich displays in multiple environments - on the web, on your desktop, in your shell or even your IDE . But how is this possible without duplicating logic, re-inventing the wheel multiple times? How do visualization libraries like Bokeh, Plotly work across frontends - like jupyter notebook, jupyterlab and nteract? This talk explores Jupyter's display system and how it handles multiple display formats in multiple environments. We will see how this idea is applied in some open visualization libraries. After this talk, you will know how to integrate your python objects better with the notebook. You will also get an idea of how to create a visualization library that works across the Jupyter ecosystem of tools. Duration 45 mins (Content can be modified to fit into 30-minute slot too) Outline - Setting some terminology for the rest of the talk (what is a frontend, kernel, displayhooks) (5 mins) - How to use Jupyter's display hooks for your python objects with the notebook (10 mins) - The Jupyter messaging protocol - specifically, the display_data and update_data messages (5 mins) - Custom mime-types (and this is the secret to Jupyter's display system!) - separating what to display from how to display it (10 mins) - Examples of custom mime-types in the wild (a look at altair , vdom , plotly and more) (10 mins) Additional notes This proposal might seem to overlap with another - Jupyter Notebooks: Internals and Extension - which explores how jupyter works under the hood and how to create alternative frontends. My talk's focus will be different, and will dive into a very specific part of Jupyter - the display system - in depth", - "Last Updated": "04 Jun, 2018", - "Prerequisites": "Some experience using either the jupyter notebook or jupyterlab ", - "Section": "Others", - "Speaker Info": "I am a software developer at D.E.Shaw, Hyderabad. I've occasionally contributed to projects in the jupyter ecosystem - the notebook, ipywidgets, hydrogen, nteract", - "Speaker Links": "Github Twitte", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Madhumitha psg (~madhumitha)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jupyters-rich-display-system~dJ1Kb/", - "title": "Jupyter's Rich Display System" - }, - { - "Content URLs": "Brief content is here: https://github.com/yashug/Pandas Actual workshop will cover more inf", - "Description": "The Goal of this workshop is to make you more fluent at pandas to answer data science questions. Python has long been great for data munging and preparation, but less so for data analysis and modelling. pandas help fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R", - "Last Updated": "04 Jun, 2018", - "Prerequisites": " Laptop with Anaconda installed Basics of Python", - "Section": "Data science", - "Speaker Info": "Yaswanth is a Senior Software Engineer, currently working in ZeMoSo Technologies and Graduated from IIT Guwahati. Free and open source software enthusiast, and passionate about Python and Machine Learning", - "Speaker Links": "Linkedin | Githu", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Gosula Yaswanth (~yashug)", - "created_on": "04 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-pandas-for-better-data-science~aKGGa/", - "title": "Using Pandas for Better Data Science" - }, - { - "Content URLs": "Will share the code, slides, and resources as a GitHub repository after the talk", - "Description": "Automatic Visual Speech Recognition comes very handily in scenarios that have noisy audio signals. A video image of a person talking is analyzed and shapes made by the lips are examined which are then turned into sounds by comparing to a dictionary to create matches to the words being spoken. In this talk, we will use a VGG+GRU network which is based on CNN+LSTM layers to predict the text spoken by the speaker and classify it into 20 classes from audio-less videos, consisting of 10 words and 10 phrases. This will be done on the audiovisual MIRACL-VC1 dataset. The talk will cover how a CNN+LSTM can be used to recognize a sequence of shapes formed by the mouth and then match it to a specific word or sequence of words spoken from Visual Feed. It will include data-preprocessing, creation of CNN and LSTM layers using Python and applying them on the dataset", - "Last Updated": "06 Jun, 2018", - "Prerequisites": "Basics of Python Syntax, Tensorflow, Keras, Neural Network", - "Section": "Data science", - "Speaker Info": "Kanika Modi holds a Bachelor's in Computer Engineering from Netaji Subhas Institute of Technology, University of Delhi. Having finished her coursework, she will join Amazon as a Software Development Engineer(SDE). She is an open source enthusiast and has contributed to organizations such as Systers, Fossasia, etc. She is also a Google Summer of Code'18 mentor at Systers, a GirlScript Summer of Code'18 mentor and mentor at RightApprise. Her interests also extend to the fields of artificial intelligence and machine learning. She prefers Python as her weapon of choice", - "Speaker Links": "Link to LinkedIn Link to GitHub Link to Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "kanika_96", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-a-lip-reading-system-to-recognise-visual-speech-using-python~dNG2e/", - "title": "Building A Lip Reading System To Recognise Visual Speech Using Python" - }, - { - "Description": "Considering the fact that businesses these days make a lot of money by recommending customers the things that match their likes, knowing how to build a Recommendation System would be of great use to many aspiring Deep Learning enthusiasts. This workshop is all about understanding and implementing Auto-Encoders. Auto-Encoders are the Unsupervised Deep Learning Models which are widely used for Dimensionality Reduction and Feature Discovery. New types of Auto-Encoders have enabled us to build very nice Recommendation Systems. The talk will focus on understanding Auto-Encoders, their types, and building a Recommender System that Predicts Rating (1 - 5) using PyTorch. The flow of the workshop will be as follows: Self Introduction Introduction to Unsupervised Deep Learning Diving DEEP into Auto-Encoders (Theory, Architecture, and Working) Introduction to Sparse Auto-Encoders Introduction to Denoising Auto-Encoders Introduction to Contractive Auto-Encoders Introduction to Stacked Auto-Encoders Understanding the Deep Auto-Encoders Training Auto-Encoders Building a Recommender System that Predicts Ratings (1 - 5) Understanding the Problem of Overcomplete Hidden Layers End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras, TensorFlow, or PyTorch will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-auto-encoders-using-python~aOGRa/", - "title": "Understanding and Implementing Auto-Encoders Using Python" - }, - { - "Content URLs": "I delivered a talk on Recurrent Neural Networks at GeoPython 2018, Switzerland. The proposed talk will be enhanced version of my previous talk. This time, I will be covering more topics to make it a more detailed talk.\nLink to my previous talk: https://github.com/greatdevaks/GeoPython_Basel_201", - "Description": "Recurrent Neural Networks (RNNs) have become famous over time due to their property of retaining internal memory. These neural nets are widely used in recognizing patterns in sequences of data, like numerical timer series data, images, handwritten text, spoken words, genome sequences, and much more. Since these nets possess memory, there is a certain analogy that we can make to the human brain in order to learn how RNNs work. RNNs can be thought of as a network of neurons with feedback connections, unlike feedforward connections which exist in other types of Artificial Neural Networks. The flow of the talk will be as follows: Self Introduction Introduction to Deep Learning Artificial Neural Networks (ANNs) Diving DEEP into Recurrent Neural Networks (RNNs) Comparing Feedforward Networks with Feedback Networks Quick walkthrough: Implementing RNNs using Python (Keras) Understanding Backpropagation Through Time (BPTT) and Vanishing Gradient Problem Towards more sophisticated RNNs: Gated Recurrent Units (GRUs)/Long Short-Term Memory (LSTMs) End of talk Questions and Answers Session", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Familiarity with programming in Python. Basic knowledge of Linear Algebra, Probability Theory, and Statistics. A basic idea of how Artificial Neural Networks work. Some experience with Keras or TensorFlow will be good but not necessary.", - "Section": "Data science", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience and hence understand the nitty-gritty of the subject. Deep Learning is a Black Art and I want to impart knowledge of this Black Art to people who are willing to learn. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-and-implementing-recurrent-neural-networks-using-python~dPGAb/", - "title": "Understanding and Implementing Recurrent Neural Networks using Python" - }, - { - "Description": "Data Wrangling involves detection, correction, removal, or otherwise dealing with inaccurate and corrupted data. The most common file formats in which data can be stored are CSV, JSON, and XML. However, many times, the data is not available in the desired format and rather is available in some unconventional file formats like PDF or PPT. Parsing PDFs may seem like a daunting task to many as it is quite an unpredictable format. Simply stated, PDF is a hard-to-parse format. This workshop will help you understand the concept of Wrangling PDFs in an easy and fun way. Following will be the flow of this workshop: Self Introduction Brief Introduction to Data Wrangling Why prefer CSV, JSON, or XML? Why avoid using PDFs? Basics of RegEx based Pattern Matching Parsing PDFs Programmatically using \"slate\" and \"pdfminer\": Getting hands-on Inefficient Parsing? Consider Data Cleaning Exploring PDF Wrangling with \"pdftables\" Where to go from here? Question and Answers Session The End :) Key Takeaways: Gain confidence in Data Wrangling using Python. Get familiar with the daunting PDF Parsing task. Get hands-on with popular PDF Wrangling libraries in Python: \"slate\", \"pdfminer\", and \"pdftables\". Understand the concept and importance of Data Cleaning.", - "Last Updated": "06 Jun, 2018", - "Prerequisites": " Basic knowledge of programming in Python language. Familiarity with wrangling CSV, JSON, or XML files will be good but is not necessary.", - "Section": "Core python and Standard library", - "Speaker Info": "Highlights: Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing. Represented India at International Hackathons like Hack Junction\u201916, Finland and Hack the North\u201916, Canada. Got invited for more than a \u2018dozen\u2019 of prestigious International Hackathons (PennApps\u201917, HackNY\u201917, Hack Princeton\u201917 and many more) and Conferences. Recently talked about \"Understanding and Implementing Recurrent Neural Networks using Python\" at GeoPython, Basel, Switzerland'18. Will be speaking about Artificial Neural Networks at EuroPython 2018, Edinburgh, Scotland. A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer. Has 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.] Received 6 Honours and Awards (International and National level). My compact Biography: My name is Anmol Krishan Sachdeva. I am currently pursuing MSc Advanced Computing from University of Bristol, United Kingdom. My specialization is in AI, ML, Applied Data Science, Computer Vision, and Computational Neuroscience. I am also doing research work on Neural Networks and Computational Neuroscience. This conference is the right place to deliver the knowledge. Looking forward to speaking at the conference", - "Speaker Links": " GitHub: https://www.github.com/greatdevaks Linkedin: https://www.linkedin.com/in/greatdevaks Twitter: https://www.twitter.com/greatdevaks", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "greatdevaks", - "created_on": "06 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/wrangling-unconventional-file-formats-with-python-playing-with-pdfs~aQXGe/", - "title": "Wrangling Unconventional File Formats with Python: Playing with PDFs" - }, - { - "Content URLs": "A few topics I will be covering, I would not be covering everything in detail, but hope to highlight important aspects from these links over the talk session: http://openmusictheory.com/ https://in-thread.sonic-pi.net/ https://github.com/gkvoelkl/python-sonic http://www.daveconservatoire.org/course/introduction-to-sonic-pi By the end of this talk, I aim to instil a much better idea about Live Coding and Programming Musi", - "Description": "Sonic Pi: An open-source live coding platform developed by Dr Sam Aaron aims to explore and teach programming concepts based primarily on the process of creating new sound.\nWe will venture deeper into the live coding platform and produced different genres/styles on music while coding live and dwell further into performing algorithmic music on a wider scale. I have tinkered with different styles of tones and sounds in sonic-pi and Python and re-created a rendition of popular 21st century music, only through algorithmic-generation, and seek to promote appreciation about open-source software such as sonic-pi and aim to demonstrate it's applications, along with the use of Python over the course of a thirty minute-talk and demo, in the rendition of producing Algorithmic-Music Live , during the course of the talk. By the end of the session, I aim to establish a better understanding of Live-coding, Programming Music and Intelligent-dance music Artists such as Aphex Twin. The flow of the talk will be as follows: Self Introduction Introduction to Music-theory and Sound Generation Introduction to Live Coding and Python-sonic Understanding the algorithmic workflow Diving beyond: Guitars, drums and Piano Produce an algorithmic-track! End of talk Q&A Session We shall also fiddle with a physical midi-controller if we find time, and demonstrate various interesting forms and styles of music; \nWe will also be producing a popular 21st century track from scratch ", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " A curiosity for algorithmically-produced music, Python and open-source software. Basic Music theory knowledge is appreciated, but anything relevant will be covered during the talk.", - "Section": "Others", - "Speaker Info": "My name is Sushen Kumar. I am a currently pursuing a Bachelor of Engineering in Computer Science at Sir M Visvesvaraya Institute Of Technology, Bangalore. Over the course of my academia I have dabbled into a few open-source projects, as well as contributed to open-source organisations on GitHub: Attended several hackathons around India: (Winner-ValuePitch Hack, Runners' up- IESA Makeathon) Given talks and held beginner sessions on Creative Coding in Python and sonic-pi. Completed three grades in hindustani-classical music-theory, with 8+ years of experience in playing the Guitar and Harmonium. Received 3 Honours and Awards (National level). I absolutely love Music and Coding, and aim to merge this passion and demonstrate the applications of Python and open-source frameworks in Music Production by means of this talk :)", - "Speaker Links": " https://github.com/nehsus https://www.linkedin.com/in/sushenk/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Nehsus (~nehsus)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/generating-algorithmic-music-and-melodies-with-python-sonic~dRXVa/", - "title": "Generating Algorithmic Music and Melodies with Python-sonic" - }, - { - "Description": "In Data Science, Garbage In = Garbage Out. Feature engineering is one of most of the important yet most neglected step in life cycle of Machine learning projects. Kaggle competitions have showed us that top Kagglers spend more than half of their time in feature engineering. Through various experiments, its also proved again & again that better features with simple model triumphs even advance models. In this talk I am planning to discuss basic as well advance feature engineering techniques which can be used by everyone in their projects Outline What is Feature Engineering ? Techniques for Numerical Variables Techniques for Categorical Variables Techniques for Textual data Advance techniques Feature Selection & Dimensionality reduction QA", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic knowledge of Python & Machine learning", - "Section": "Data science", - "Speaker Info": " Sudarshan Gadhave is a Data Science ,Data Engineering & Data\n Integration professional with over 8 years of experience working on\n Machine Learning , Data Engineering , Data Visualization and Data\n Warehousing Projects. Currently he is working as a Specialist Data Scientist in Analytics R&D team of\n Nice Actimize ( Nice Systems) working on developing Anomaly & Fraud detection models. Earlier experience of working in Advance Analytics & Data Warehousing\n teams of NEC, Japan & John Deere (Deere & Company). Pythonista & expert in Python Machine learning stack (Numpy,Pandas,\n Scikit-Learn, Matplotlib) Active & Core member of Python Pune meetup group.Presented several\n talks on Python & machine learning in meetups, conferences and\n colleges all over Pune.", - "Speaker Links": " Github:- https://github.com/sudarshan1413 Linkedin:- https://www.linkedin.com/in/sudarshan-gadhave-73567b23/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "sudarshan1413", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/art-of-feature-engineering-for-machine-learning~eVWza/", - "title": "Art of Feature Engineering for Machine Learning" - }, - { - "Content URLs": "Slides : https://docs.google.com/presentation/d/1zNFGNy2BMBYQvZypkH8Iql-WRx--6Ddg8Ft33intWjM/edit?usp=sharin", - "Description": "Large Python codebases can be hard to maintain. If we make it easier to understand our code bases, we make everyone more productive and help each other write fewer bugs. Static typing is one of remedies that can improve readability and maintainability of the code. That's why Python now features optional static typing as described in PEP-484 , implemented as Mypy . Mypy is an experimental variant of Python that let's you add optional type annotations to type check your Python code. And it works great on both Python 2.7 and 3.3+. Adopting static typing is easier that you think, you can start on a small set of code and move on to bigger pieces. In this talk I'll share about, PEP-484 and Introduction of type annotations in Python 3.5 Use cases of Mypy and how to use it with Python 2 and 3 Project typeshed and how to leverage it Lessons I learned by type hinting the project Twine We\u2019ll also discuss how to make it a seamless part of your project; what order to approach things in; and some powerful new packages that make it even easier today to add static types to your Python codebase than ever before", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of Python Difference between dynamic and statically typed languages", - "Section": "Core python and Standard library", - "Speaker Info": "Wasim is a Senior Software Engineer at Zemoso Labs, Hyderabad. He's an open source fanatic who loves to create meaningful software and contribute to open source projects. Some of his contributions are included in projects like Sendgrid, Warehouse, Twine and Hazelcast. Apart from programming he also tweets . You can find him interesting on his GitHub profile ", - "Speaker Links": "Article on Medium about Mypy Stub file for the project Texttable Open source contributions can be found at my GitHub profile ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Wasim Thabraze (~waseem18)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mypy-optional-static-typing-for-python~bW1Ee/", - "title": "Mypy: Optional Static Typing for Python" - }, - { - "Content URLs": "https://www.artima.com/weblogs/viewpost.jsp?thread=214235 http://www.dabeaz.com/python/GIL.pdf -slides tb", - "Description": "Python is an amazing language, known for its vast standard library and use in rapid prototyping. When we were trying to build a robotics system that is primarily modular and upgradeable, we ended up using Python to power the brain of the project. In this talk, we'll discuss how we designed the event loop, responsible for controlling the mechanical actions and state of a robot snake. Animating multiple motors concurrently at different speeds to different positions. Foreground and background tasks. Interrupting ongoing tasks. We will discuss best practices when performing asynchronous actions in Python, and how to ensure actions are completed within a bounded time.\nFinally we touch one of the lesser known 'features' of Python, the Global Interpreter Lock. GIL is a mutex that protects access to Python objects, preventing multiple threads from executing at once. Two threads calling a function may take twice as much time as a single thread calling the function twice. We'll discuss some of the real world implications of the GIL, along with some considerations that must be taken while writing highly synchronous Python code", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Knowledge of common Python syntax would be great", - "Section": "Core python and Standard library", - "Speaker Info": "Hi, I'm Pranith, a final year undergrad student at NMIT, Bangalore. I'm a robotics enthusiast with a passion for cypherpunk, virtual reality, and generally, the future. Apart from the usual frameworks, I've used Python across the field, ranging from web technologies implemented on raw CGI to microPython on the ESP8266. I try to apply Python in odd ways to bridge various layers of the stack, and as a result have a fair amount of experience breaking it", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pranith Hengavalli (~prnthh)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/robot-snakes-and-the-global-interpreter-lock~eXPve/", - "title": "Robot Snakes and the Global Interpreter Lock" - }, - { - "Content URLs": "Shall be updated soon", - "Description": "Here, We will talk about how you can make a bot to help you automate your life and make your very personal Assistant, and maybe you will end up making something better than Google Assistant or Siri. We will be using modules to perform a task, so you can keep making them as you go and your assistance will keep becoming more powerful and yes all this will be done in python. In this talk: - We will start with setting up project creating simple python GUI. - Making some modules to perform a simple task. ~ Composing email with speach ~ Some other cool modules - Explaining what else we can achieve with this. ~ Let's make, its personality using tensorflow for talking stuff - Showing my work and explaining how it works Here, Is in early development phase Then we will end with some questions and how they can continue with this project", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic Understanding of Python", - "Section": "Developer tools and Automation", - "Speaker Info": "He is a student, a self-taught programmer loves to dig deep and know more about the computers. Fell in love with python and now loves to Automated things with python. He is GSoC aspirant. He is an active volunteer at PyDelhi and ALiAS . When he is not automating things he loves to contribute to open-source and closing issues", - "Speaker Links": "Website: omkar.site Github: @omi1085", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "omkar yadav (~omkar10)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/superpybot-your-personal-assistant~bYZAd/", - "title": "SuperPyBot: Your Personal Assistant" - }, - { - "Content URLs": "This one is the essence of it but closed source and in java: https://lifehacker.com/how-to-build-your-own-amazon-echo-with-a-raspberry-pi-1787726931", - "Description": "Voice is the new touch. It's not going to be too long before the likes of Alexa or Google Home take over our day to day life like the Internet and the mobile phones have. There are countless tutorials on how to hook up a home automation system using a Raspberry Pi like here and here . Pair that up with voice capabilities and you can basically tell your lights to turn themselves off or the TV to change the channel. In this talk I'll cover the following: Hook up a microphone to a raspberry pi and be able to capture wav files on python. Use an online API like Google's Speech API to convert the wav to text. Give a background on what intents and entities (slots) are. Installing open source software like Snips Encoding our intents and example sentences and training the open sources software Calling a functions to do particular activities At the end there'll be a cool demo", - "Last Updated": "07 Jun, 2018", - "Prerequisites": " Knowledge of what a Raspberry Pi and Python is. And maybe played with an Alexa, Siri or Google Home. Yup, low barrier of entry", - "Section": "Embedded python", - "Speaker Info": "I am Ved. I have a masters in Computer Science/Data Science from IIIT-Bangalore and I work on NLP/Linguistics at Slang Labs. My goal in life is to sit down and have a conversation with a computer at a bar coffee shop. Maybe we won't get there soon, but at least maybe I can make it reserve my seat for me", - "Speaker Links": " vedmathai.com https://github.com/vedmathai/ https://www.linkedin.com/in/vedmathai/", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ved Mathai (~ved47)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/create-a-voice-conversational-agent-for-your-raspberry-pi-home-automation-system~eZgQa/", - "title": "Create a voice conversational agent for your raspberry pi home automation system" - }, - { - "Content URLs": "https://github.com/Laneone/askfm-pytho", - "Description": "Hey everybody! Ever tried to webscrape? Ever faced a \"No robots allowed! No web scraping allowed!\" message from a favorite site? This talk is for meant for you. Usually when you're done building a fancy web scraper and begin running the homebrew'd tool on your favorite site there's chances you'll face a block on your IP address preventing your computer from accessing more resources and therefore downloading the contents of the website. Your tool maybe fast, it might be scalable, it might be the best written scraper out there, but with just one IP address under your belt, it's easy for giants to block your ip address and prevent you from getting that precious data, especially if you've built a threadsafe and multi-node webscraper. Enter The Onion Router, The ToR project, allows you to use the the internet vis-a-vis a proxy and visit the same website under a different endpoint ip address, but that's just for one instance of ToR. What if you ran, say 200? at once? 200 ip addresses > 1 ip address. With 200 endpoints and the latest update to the requests library, you can now use your multi-threaded and resource hungry webscraper and it can(not) be stopped! Whatever your rate of data collection, you can 200x it! The stack is simple, you open a SOCKS5 proxy per ToR endpoint, connect it to a request with it's own port number and you're good for that one request, same for multiple requests. You can build a task scheduler to orchestrate the url to scrape and the port number the tor endpoint is on and have the entire application running on a cloud service provider to ensure you face no bandwidth issues. The demo centered around the talk will attempt to rapidly and quickly scrape users from the famous social network Ask.fm which is known to restrict users from retreiving from their site if you attempt to download more than 4 users in under a second, but with the hack in place, you'll be retrieving close to maximum efficiency on a DigitalOcean droplet , but this can be applied to virtually any website and any cloud provider. Never pay for webscraping again! Thanks and see you at PyCon! \n-Lokesh Poovaraga", - "Last Updated": "07 Jun, 2018", - "Prerequisites": "Basic concepts of web scraping, Regex, Task scheduler, ports and proxies", - "Section": "Developer tools and Automation", - "Speaker Info": "Hi I'm Loki! (Lokesh Poovaragan) A full-stack developer from Dayananda Sagar, Bangalore, and I love to code in python! In my free time I love to web scrape and gather good amounts of public data and encompass them into json format for data(sentiment) analysis. I also build prototypes of interesting combinations of technology to solve unique problem statements. I love exploring new and interesting areas of work and I love to play with code", - "Speaker Links": "Blog: http://laneoneblog.blogspot.in GitHub: http://github.com/Laneon", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Laneone (~Laneone)", - "created_on": "07 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-intermediates-guide-to-theoretically-unlimited-webscraping-with-python-using-requests-lxml-tor~e1MZe/", - "title": "A Intermediate's Guide to (theoretically unlimited) WebScraping with Python using Requests & lxml & ToR" - }, - { - "Content URLs": "Would update soon after feedback", - "Description": "Most machine learning algorithms require feature vectors as inputs. In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object (image, text, sound). Feature engineering, the practice of extraction of features from objects is a combination of art and science; it requires the experimentation of multiple possibilities and automated techniques with the intuition and knowledge of the domain expert. Automating this process is called \"feature learning,\" where a machine learns the features itself. One way to obtain features is to use the 'Bag-of-Features' model, the idea behind which is to simplify object representation as a collection of its subparts. Originally used for representing text data, the \"Bag-of-Words\" methodology can be extended to different types of objects resulting in models such as \"Bag-of-Visual-Words,\" \"Bag-of-Audio-Words.\" The significance of these models in the age of self-learning deep networks still holds because of their ability to work with limited data. The contents of the talk are: Introduction to Feature Engineering Working with Text Data Understanding 'Bag-of-Words' Example: Text Classification Working with Image Data Introduction to 'Bag-of-Visual-Words' Example: Image Classification Comparing the performance to CNN Overview of 'Bag-of-Audio-Words' Generalizing 'Bag-of-Features' This talk primarily discusses Bag-of-Words, Bag-of-Visual-Words through an example of text classification and image classification respectively. It also covers the concepts that generalize to models other than Bag-of-Features. The goal is to acquaint the audience who have previously worked on numeric data with some ideas to get started with text and multimedia data", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Intermediate knowledge of Python Familiarity with classification problems Familiarity with basic NLP/CV is helpful (but not necessary)", - "Section": "Data science", - "Speaker Info": "I'm a fresh graduate in Computer Science & Engineering. I am passionate about Data Science, and I spent most of my time learning about skills required to excel in the domain. Outside of my professional interests, I am fond of rock music and reading", - "Speaker Links": " Blog: https://pranavsuri.com GitHub: https://github.com/pranavsuri LinkedIn: https://linkedin.com/in/suripranav Twitter: https://twitter.com/pranav_suri", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pranav Suri (~pranavsuri)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bag-of-features-representing-text-image-data-as-numerical-vectors~b2XMe/", - "title": "Bag-of-Features: Representing Text & Image Data as Numerical Vectors" - }, - { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "In today's Era, the IT sector is moving more and more towards automation. Now every company is trying to provide its users with the facility to perform their task without the need for any human intervention.\nIn this talk, we are addressing a similar problem of automating the vehicle parking systems. Problem description: Automated license plate recognition(ALPR) is a well-known problem where we try to extract the license number from a cars number plate using machine learning algorithms. The scope of its real-world application ranges from highway toll plaza to automated parking and charging of future electric cars.\nThis problem has been targeted with a variety of algorithms like traditional template matching to advance deep learning algorithms like YOLO . Here we will be presenting a combination of little template matching clubbed with some deep learning to solve this problem in the most simplistic way", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations", - "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Siddhant Khandelwal", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saqhas", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-license-number-recognition-in-python~e33Ae/", - "title": "Automated License number recognition in python" - }, - { - "Content URLs": "http://click.pocoo.org (Cool power-point and Github repo coming up", - "Description": "Who hasn't used Git in the terminal? An absolute beast of a tool. But did you ever have an idea to build your own cool Command Line tool for something you believed could simplify life for other devs but you didn't because you were too lazy to research? Worry not! I present to you Click! Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It\u2019s the \u201cCommand Line Interface Creation Kit\u201d . It\u2019s highly configurable but comes with sensible defaults out of the box. In this talk, I'll go through the process of designing a simple (or complex) Command Line Interface called thanos which tells you whether you survived the SNAP or not. I'll be taking you through the process of designing, building and publishing our thanos package. We'll then upload it to the Python Package index so that you can do pip install thanos from any system worldwide and find out if you perished or not. Outline What is a CLI ? Building our own CLI called Thanos , to find out whether you survived the snap or not. >>thanos snap\n You didn't make the snap. Creating complex commands using beautifully decorated code. Exploring arguments, flags and options within the CLI. What's PyPI, and why do we need it? Uploading your new Thanos package to Python Package Index. QA", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Should have seen or used a terminal before. (Mandatory) Basic Python knowledge preferred.", - "Section": "Developer tools and Automation", - "Speaker Info": " Adarsh is a visionary who strives to build amazing tools for people. He is currently pursuing bachelors in CSE. Currently he is Google Summer of Code Intern at CloudCV , an organisation which works on making reproducible AI research, where he is building a versatile CLI for EvalAI project. He was one of the youngest speakers at FOSSASIA International Summit 2018 in Singapore for his work on Python based NLP POSTagger. Worships Open Source software and have contributed to multiple organisations like FOSSASIA, Zulip where he was also a mentor for Google Code-In 2016 .", - "Speaker Links": "https://www.youtube.com/watch?v=TzIr9THCUJg https://2018.fossasia.org/event/schedule.html#s-4267 https://github.com/isht3/ https://www.linkedin.com/in/guyandtheworld", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "isht3", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-your-own-command-line-application-and-upload-it-to-pypi~b427e/", - "title": "Build your own Command Line Application and upload it to PyPI!" - }, - { - "Content URLs": "Part 1 Part 2 Github Rep", - "Description": "Websites and blogs have become a common trend amongst professionals to display not just their resumes but also their daily work items. Static blog generators have gained popularity over the last few years . People who have been using Wordpress, Blogspot or Blogger are now shifting to Pelican , Jekyll etc. One major annoyance was that Wordpress had a huge attack surface. Everytime someone found out a Wordpress exploit, your site was at risk. When comparing Blogger vs Pelican, the Slant community recommends Pelican for most people. In the question \u201cWhat are the best solutions for a personal blog?\u201d Pelican is ranked 10th while Blogger is ranked 14th. Python is becoming more and more popular amongst programmers and so is Pelican . \nPelican is a static blog generator and supports several formats like Markdown , ASCII etc . It turns Markdown and some Jinja templates into the Full Stack Python site. Its beauty lies in its simplicity and even a non programmer can get started with Pelican in just a few lines of code and plain text . Over the past few years people have shifted from Wordpress to Pelican .This is because a static site has basically no attack surface, and can be hosted on free or inexpensive hosts like Github Pages .\nThis talk is focused on introducing a simple static site generator to beginners and even avid bloggers who aren't coders . This talk will cover:- Basic installation of Pelican Writing a blog post with Pelican Changing themes of a blog/site Comparison between Jekyll and Pelican The main aim of this talk is to familiarize people with the concept of edifice . I have met a lot of non coders who have asked me about creating a basic website for personal use . This talk is also targeted to all those you are interested in blogging and everyone out there has something to say and something to blog ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": "Absolutely nothing ", - "Section": "Web development", - "Speaker Info": "Anumeha Agrawal is a Pythonista and an open source enthusiast . She is in her third year of undergraduate program in Information Technology at NITK Surathkal . She is also a Google Summer of Code 2018 student at Systers . In her project at Systers , she has used python to write scripts to retrieve data from GitHub API and use it in her MEAN stack project . She uses python scripts to simplify most of her work like API data collection and web scraping . Python was the first language she was introduced to when she began programming and it is her weapon of choice . Owing to the simplicity of python syntax, she also used python to code her algorithms for her talks and workshops at college . Apart from being a full stack developer ,she is also a Data science enthusiast and employs python for designing most of her Deep Learning models and algorithms ", - "Speaker Links": "Link to Github Link to Linkedin Profile Link to Medium Blog Link to GSoC projec", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anumeha Agrawal (~anumeha)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pelican-magic-for-beginner-bloggers~e5MYe/", - "title": "Pelican - Magic for beginner bloggers" - }, - { - "Content URLs": "Will be sharing soon", - "Description": "Your introduction to concurrent programming in python. This talk is dedicated to a developer to enable him/her get started in asynchronous programming. The contents that will be covered in the discussion are as follows. What is asyncio? Why should we bother? Multi Threading vs Multiprocessing vs asyncio understanding the differences. All about what an event loop is with examples Futures Tasks and coroutines Streams Multiple Coroutines. Scheduling Calls Synchronization primitives Queues Working Example with a few notes on sockets and summary. The talk provides preliminary insight and a simple explanation to programmers who wish to explore asyncio and/or concurrent programming. ", - "Last Updated": "08 Jun, 2018", - "Prerequisites": " Basic understanding of python syntax. Some OS concepts like differences b/w multiprocessing and multithreading. Understanding UNIX (not mandatory).", - "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "08 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-asyncio~b6MOa/", - "title": "Introduction to Asyncio" - }, - { - "Description": "This workshop is dedicated to discuss and extrapolate on the core of Object Oriented Programming its finer details and nuances. The objective of the talk is to introduce concepts that will ensure OOP becomes second nature to a programmer. What you will gain after this session Detailed overview of Object Oriented Programming Intuition on the finer nuances of Object Oriented Programming. Tips on keeping the OOP code clean and readable. Expanding your horizon by understanding some lesser known concepts in Python. The session will focus on the following aspects with examples Inheritance and everything about it. Method Resolution Order Method Types Custom Base Object, Collections, and Dict Objects Extending Built-in Types Data Models Meta Classes and where they help Decorator and Class Decorators. Factory Design pattern Singleton Things to remember while writing code Conclusion", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic Python syntax Some understanding of Object Oriented Programming", - "Section": "Core python and Standard library", - "Speaker Info": "I am a Software Engineer/Data scientist at NextOrbit, Technical Architect at Code Matrix. I am a startup guy who loves the idea of building teams and working with them from the ground up. I have been part of and lead teams that have built medium and large scale software. I am glued to the computer a lot, although that must be obvious. But when I am not peeled to a laptop I play badminton, chess, teach students software and find creative reasons to skip a session in the gym on a daily basis", - "Speaker Links": "https://www.linkedin.com/in/vishnu-kiran-k-v/ https://www.linkedin.com/pulse/redis-vs-rabbitmq-message-broker-vishnu-kiran-k-v/ Have not had a lot of bandwidth for open source contribution. Something I hope to change soon", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Vishnu Kiran (~vishnu25)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-object-oriented-programming~e7MQb/", - "title": "Advanced Object Oriented Programming" - }, - { - "Content URLs": "I will upload slides soon", - "Description": "Object-Relational Mapper (ORM) is one of the powerful feature of Django. It allows us to interact with database without writing long complex SQL queries. The contents that will be covered in the discussion are as follows. Introduction to ORM, How it works ? What is queryset ? how it works ? Explaining use of values, values_list, only and defer to run ORM query efficiently How to use select_related and prefetch_related to optimize queries Some examples to show, how to query very complex data using only ORM What not to do while using ORM to avoid slow performance", - "Last Updated": "09 Jun, 2018", - "Prerequisites": " Basic knowledge of Python and Python web framework (Django) Some experience in quering relational databases", - "Section": "Web development", - "Speaker Info": "My name is Hiren Patel. I am working at Aubergine solutions pvt ltd and I have been doing full stack web development there from last 2.5 years. While working on some web projects, I have always focused on learning django in more detail and try to optimize APIs to return response faster", - "Speaker Links": " Github: https://github.com/hirenalken LinkedIn: https://www.linkedin.com/in/hiren-patel-046672ab/ StackOverFlow: https://stackoverflow.com/users/3553279/hiren-patel?tab=profile Medium: https://medium.com/@hirenpatel_38103 I had presented a talk on this same topic in meetup organised by Ahmedabad based meetup group. here is the link to meetup: lin", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Hiren Patel (~hirenalken)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/efficient-use-of-django-orm~b8gja/", - "title": "Efficient use of Django ORM" - }, - { - "Content URLs": "Slides TBD Code repository TB", - "Description": "Abstract Today, massive systems are running on microservices communicating with each other using REST APIs. REST is easy to get started, loosely structured and does good job in exchanging messages. But it's convenience comes with a performance trade-off, which takes us back to other optimal alternative: gRPC Description In this talk we will see what gRPC is and how it is different from REST. We will get started with GRPC by generating stubs for python and \nbuild a simple gRPC API server. We will try to find out the advantages of gRPC over REST by doing a side by side comparison of our APIs. We then deploy our server in Kubernetes and discuss how we could scale our microservices. Outline Introduction to gRPC (3 min) gRPC concepts (5 min) Designing the APIs REST-fully (3 min) Going the gRPC way (5 min) Generating python stubs Duel: gRPC vs REST python servers (4 min) Demo (4 min) Deploying our gRPC apis in kubernetes Summary (3 min) Q & A (3 min) Key take aways to audience Audience will get a practical introduction to gRPC and protocol buffers. Now the audience will know an alternative to HTTP/REST. This allows them to design better microservices\nbased on their use cases. Bonus: Deploying and scaling python microservices in Kubernetes. Links Companies using gRPC in production Protocol buffers ", - "Last Updated": "09 Jun, 2018", - "Prerequisites": "This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners", - "Section": "Web development", - "Speaker Info": "Naren is a Product Engineer with specific focus on building robust backend systems. Past 5 years, he has built dozens of microservices and scalable systems using Python, Go and AWS cloud. He is an open source enthusiast who loves speaking at tech conferences and currently works as Senior Software Consultant at Tarka Labs. In his industry experience he\u2019s worn plenty of hats- like the one of a Trainer, Embedded Engineer, Product Engineer and Consultant and sometimes even helmets- while he\u2019s out cycling.\nWhen he\u2019s not stirring up code, you can find him whipping up a delicious gluten-free treat or training for cycling races.\nHe also blogs about software, productivity and goes by the handle DudeWhoCode across the internet", - "Speaker Links": "Past 5 years I have been architecting and building scalable backend systems using Python. I have built a dozen of microservices at scale. Recently I built a production infrastructure in Python that handles 20+ millions of API calls per day. At one point of time, I realised I should know some alternatives other than REST to communicate between the microservices. Out of curiosity I explored and used gRPC in few of my microservices. Since then, I wanted to share the knowledge so that developers will get to know other options while architecting their infrastructure. This talk targets intermediate audiences. As it involves microservices, a little bit of knowledge in REST API is nice to have to realise how gRPC is different from REST. But nevertheless, it will also be useful to curious beginners. I have spoken in various conferences, my recent one was PyCon Singapore 2018. Below are some of my previous talks and speaker portfolio: Speaker Portfolio Featured talk 1 Featured talk 2 Featured talk 3 portfolio blog Github", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Narendran R (~narendran)", - "created_on": "09 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-better-python-microservices-using-grpc~e9jJa/", - "title": "Building better Python microservices using GRPC" - }, - { - "Content URLs": "Any related material will be shared soo", - "Description": "Natural language processing(NLP) is a branch of artificial intelligence concerned with automated interpretation and generation of human language. From keyword search to Virtual Assistants, from spell checkers to language translators and from sentiment analysers to Chat bots, NLP finds its applications in most of our day to day applications.\nThis workshop aims at delivering a basic Hands on tutorial to get started with NLP in Python. It commences with an introduction to NLP, discussion on various applications and a linguistic breakdown of Language (English). By the end of this workshop you will be able to : Install relevant packages such as nltk, gensim and pattern . Applying text processing techniques such as Tokenization, Stemming, Lemmatization and Chunking . Forming a Document Term Matrix using Bag of Words Model . Building a simple Spam/Ham classifier using Bag of Words Model . Generating Word Vectors using Gensim Word2Vec module. Building a Sentiment Analyzer . This workshop provides preliminary insight and a simple explanation to enthusiasts who wish to explore the field of Natural Language Processing.\nIt enables you to talk to your computer!", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of Python. Any knowledge of Python modules such as Numpy, Pandas etc. is and add on.", - "Section": "Data science", - "Speaker Info": "Hello, I am Osheen Nayak, working as a Software Engineer at Texas Instruments Bangalore. I belong to Delhi Technological University batch of 2017.\nI am a Machine learning and Data Science enthusiast and I have been actively driving various Machine Learning activities. I have delivered few talks on Machine Learning in the past one of them including \"A primer on Machine Learning and Artificial Intelligence\" in the IEEE forum to and audience of 50 people. I am an avid football fan and also an amateur player.Also, I like to play video games, cricket and chess", - "Speaker Links": "Connect on LinkedIn : https://www.linkedin.com/in/osheen-nayak-31022a10b", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "osheen nayak (~osheen)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-talk-to-your-computer-a-101-on-natural-language-processing-with-python~e0M5a/", - "title": "How to talk to your computer - A 101 on Natural Language Processing with Python" - }, - { - "Content URLs": " http://github.com/vaideesg/omsdk http://github.com/dell/omsdk", - "Description": "Abstract Ever wonder creating your own super-type-manager leveraging the python's own type constructs? Ever explored alternatives to APIs for integration? In this talk, we will cover our experience in building a new type manager (as part of developing open source OpenManage(tm) Software Development Kit) leveraging pythons own type constructs and explore how this new type manager provides a credible alternative to APIs, especially in those information-heavy environments like Device Management. Description Devices (like Servers, Switches, Telecom Switches) are data-intensive systems. Their information model is so intensive, that practically all operations (health, inventory, metrics, configuration) on the device ends up in primarily as CRUD operations on the information model they expose. Only a paltry few operations are exposed as APIs. When building an API for managing these devices, we realized that providing classic function-style APIs only degraded the user experience. What we realized was there was significant information available on the Servers, and providing an API for exposing traditional CRUD (Create, Retrieve, Update and Delete) for all information nuggets was just exploding the API sets. It was not necessarily covering all the scenarios that could be possible for management and did not seem to scale. Our approach was to take this information model within the devices and expose them as a huge navigable data structure representing the entire spectrum of the device and provide a language native experience. We created a new type manager leveraging the python class special operators ( getattr (), setattr (), le () etc.) to create a whole new type manager that provides additional controls and safeguards. Some of the safeguards include: Not allowing edits to read-only components Allowing only applicable changes only (ranges, enumerations) Providing native python experience for special types (IP Address Types etc.) Providing mechanisms to validate cross-attribute validations Providing custom indices for arrays (like Virtual Disks, Users) Providing mechanism for tracking changes to configuration Apply changes to the device optimally Provide mechanisms for identifying configuration drifts Outline : Outline of the presentation: Introduction Device Configuration - Aspects & Peculiarities Pitfalls of API approach for Device Configuration Type Manager - introduction Super Types - Enumerations, Fields, Classes and Arrays Bringing in Native Type Experience Data as API - Enriched user experience Demo Q&A Key takeways to audience Audience will get an exposure: How to create your own type manager by overloading python type constructs Exposure to alternative approach to creating APIs for data-heavy systems & explore benefits Learn how type manager simplifies your life as well as the life of your consumers. Secrets of the python inbuilt __ operators - and how you can leverage them to provide native type experience even for your own custom classes How you can create a better user experience for customers in a simple way How you can incorporate Object Oriented SOLID principles", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " General familiarity with type concepts (fields, arrays, classes, enums) is needed Exposure to in-built operators like ( getattr etc. will help) Exposure to Systems Management would be useful.", - "Section": "Core python and Standard library", - "Speaker Info": "Vaideeswaran Ganesan, Senior Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and data center products. His passion is compiler design, analytics, systems management, networking protocols and automation. Ajaya Senapati, Principal Technologist @ Dell EMC, has special focus in building systems management products for servers, networking and storage products", - "Speaker Links": "Vaideeswaran Ganesan\n 1. My Github Repository 2. My Linkedin Article which I wrote while implementing this Fun with Python Code Generation Ajaya Senapati\n1. Lin", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Vaideeswaran Ganesan (~vaideeswaran)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-as-api-building-a-type-manager-with-python~egyrb/", - "title": "Data as API: Building a Type Manager with Python" - }, - { - "Description": "Fog and haze (referred to as the atmospheric light) are the main cause of distortions, degradation in the quality of images clicked during foggy situations. But with the advancement in technology, thanks to Python and OpenCV libraries and brilliant minds of people out here in this small world, recovering almost a fog-free image has been made possible in recent times. And now we are moving towards making this algorithm more optimized so that it can work in real time for videos and live camera feed. Different mathematical models have been presented over the time for this algorithm but there are very few real-life implementations in any particular programming language, so here the Python implementation of this algorithm will be discussed. Basic steps and the ideas implemented will be discussed in a brief and different implementation will also be shown in the session", - "Last Updated": "10 Jun, 2018", - "Prerequisites": " Basic knowledge of the numpy functions. An idea about the OpenCV computer vision libraries and the different filters implemented there. Love for Python", - "Section": "Developer tools and Automation", - "Speaker Info": "Speaker: Vivek Modi Final Year undergrad at NIT Durgapur Tech Head at GNU/LINUX USERS' GROUP NIT Durgapur Summer Intern at DRDO (Integrated Test Range) Contributor in the project: Soumam Banerjee Final Year undergrad at NIT Durgapur", - "Speaker Links": "modiher", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vivek Modi (~modihere)", - "created_on": "10 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-and-opencv-for-removing-fog-and-haze-from-an-image~ejBye/", - "title": "Using Python and OpenCV for removing Fog and Haze from an Image" - }, - { - "Content URLs": " Will have own slides. Link will be shared with all This GitHub Repo contains some of the content that will be delivered during the course of the talk. A lot of other websites from where I pick a point or 2", - "Description": "Everyday we listen to this word \"DATA\".\nBut after listening to that word, some questions might pop up in your mind. WHAT IS DATA? WHY DOES ANYONE NEED TO WORK WITH DATA? HOW TO UTILISE AND WORK WITH THIS DATA? Data is now one of the most important things for any business to run. From small startups to large companies, everyone looks at data to improve their business.\nEveryone looks at data to increase their profits. Everyone looks at data to understand why they failed and where they failed. Everyone looks at data to understand how a product gained success in the market. Basically Data is everything today for companies. Data is available everywhere now and it's become more important than ever to actually work with data and luckily we have great modules to work with data in Python. I'll be focusing on these modules and the power that data possesses. My primary focus here would be about the power of data. I surely will be talking about how to use this data in Python to make the most out of it, but before that I'd like the entire crowd to know what the power of data is. This would be a good talk for beginners honestly. Even if you have no idea about how data could be used or what is data, after this talk, you'll get a decent idea about it. Through this talk the 3 questions mentioned above in bold will be answered. The talk would progress in the following manner : Self introduction (3 minutes) Introduction about the topic (2 minutes) What is data? (3 minutes) Where is this data? (2 minutes) How to make the most out of data? (3 minutes) How Python helps in this process? (2 mins) Name and explain about different Python modules like Pandas, Numpy, Matplotlib and Seaborn in brief (10 mins)", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "No prerequisites required. This talk will deal about everything from scratch and will give you a basic understanding of what modules could be used in Python. So you could research on those modules after the talk, but for the talk, no prerequisites required", - "Section": "Data science", - "Speaker Info": "Hey everyone, I'm Rahul Arulkumaran, a B.Tech 3rd year Student pursuing my major in Computer Science Engineering from Mahindra \u00c9cole Centrale, Hyderabad. I'm an open source and data science enthusiast. Coding is one thing I love doing all day and all night. Never feel like quitting.\nPython is my go to language. Anything I think of developing comes to life using Python. I have a very strong connection with Python as it was the first programming language I learnt. I'm also a full stack developer and perform data science on various datasets. I'm a Contributing and Managing Member in the PSF. I also am the President of the Computer Science Club in my college. Apart from that, I head the website development team for TEDxMahindra\u00c9coleCentrale and the Marketing and Promotions team for Aether (the techno cultural fest of MEC). I'm the Co-Founder and CEO of a startup which goes by the name FreeFlo. It is a product based company that looks at developing products related to Machine Learning, Blockchain and other related fields. I'm also currently interning in IIIT-Hyderabad in the Machine Translations and NLP Lab in the field of sentiment analysis. It might seem although I'm not interested in the non tech aspects of businesses, but I actually love working in teams related to business development and marketing. So that's mostly about it. Looking forward to interact with all of you out there ", - "Speaker Links": " GitHub My Blog Facebook LinkedIn Twitter Telegram Gmail ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Rahul Arulkumaran (~rahulkumaran)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/power-of-data-and-working-with-it-using-python~bkgJb/", - "title": "Power of Data and Working with it using Python" - }, - { - "Content URLs": "-> How does a web framework work -> WSGI basics -> Getting hands dirty with coding More information will be uploaded soo", - "Description": "Build your own web framework using python .\nLets unleash the power of python by building a web framework from scratch . \nIt will help you understand what actually happens under the hood in most famous web framework", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Web development basics\nCuriosity\nTrust in python :", - "Section": "Web development", - "Speaker Info": "Not so useful BTech ( biotechnology ) from Thapar University\n2 years of experience working in pytho", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-our-own-web-framework-like-flask-in-python-from-scratch~el0je/", - "title": "Building our own web framework like flask in python from scratch" - }, - { - "Content URLs": "Will be uploading soon !", - "Description": "My philosophy has been : If you haven't build it you don't know it. So lets build a hadoop clone and see how it works . This workshop is basically about building your distributed processing system . It will take you through some basics of distributed system and we will try and build our very own distributed system in python ", - "Last Updated": "11 Jun, 2018", - "Prerequisites": "Google \"what is hadoop\" Google \"what is a distributed system", - "Section": "Networking and Security", - "Speaker Info": "class Pankesh (human)", - "Speaker Links": "class Pankesh (Human): def __init__ ( python=\"Python3\" ) :\n\n super.name = \"Pankesh gupta\"\n\n super.age = 25\n\n curiosity = True\n\n experience = 2\n\n education = \"Thapar University , Patiala", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lets-build-a-hadoop-clone-in-python~bm6Rd/", - "title": "Lets Build a Hadoop clone in python !!" - }, - { - "Content URLs": "Any related material will be shared soo", - "Description": "Financial data is difficult. It is sensitive to many unknown factors. So we need a good strategy for trading with deep learning. That's where reinforcement leaning comes in. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over.\nBy the end of the talk, you will learn:- What trading is? Why it's hard? How Can Deep Learning solve the trading problem? Why is reinforcement learning an effective solution?", - "Last Updated": "11 Jun, 2018", - "Prerequisites": " Willingness to learn Basic python", - "Section": "Data science", - "Speaker Info": "I have always been amazed by computers and how much you can do with soo little. Curiosity lead to passion. Passion lead me to work on some amazing things. AI is the buzzword around and I have been working on AI for quite some time and it's been a really great journey, challenging but rewarding. Recently, I started working with some startups. Currently, I'm working for a Silicon Valley startup, who has been working on making serious predictions on small data. I have also been interested in Fintech data. I started with simple fraud detection models and now I'm working on solving the trading problem with reinforcement learning", - "Speaker Links": "Connect on Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Himanshu Singh (~himanshu61)", - "created_on": "11 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-trade-with-reinforcement-learning~enX5b/", - "title": "Learning to Trade with Reinforcement Learning" - }, - { - "Content URLs": "https://www.tensorflow.org/ https://github.com/aymericdamien/TensorFlow-Example", - "Description": "Hey everybody!\nIf you have ever heard of this thing called as neural network , than this workshop is definitely for you .Neural networks are not new they been there for a long time . but they have become quite famous recently\ntensorflow is consisdered one of the best frameworks for getting started with neural networks and deep learning . About TensorFlow TensorFlow\u2122 is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google\u2019s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. We will also try and build an image recognition model using deep learning from scratch . Tensorlfow helps getting started with deep leaning and building neural networks ", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basics of python and an open mind to learn new things ", - "Section": "Data science", - "Speaker Info": "Python lover . Machine learning enthusiast . Currently working on BIG ML ( training machine learning models on big data ) and efficient deployment of machine learning models on production ", - "Speaker Links": "Contributor at https://github.com/polyaxon/polyaxo", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Pankesh (~PankeshGupta)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learning-to-build-neural-networks-from-scratch-using-tensorflow~boKYb/", - "title": "Learning to build Neural networks from scratch using tensorflow" - }, - { - "Content URLs": "Will be updated on github before the conference", - "Description": " It is always essential to understand the genesis of evolution or the roots of revolution. Keeping in mind the above saying, in this workshop, I will provide a hands-on understanding of Blockchain technology using Python. There are multiple resources to get a firm understanding about this domain, but the best way to understand it is by using the concept of \"Learning-By-Doing\" . Following are few reasons why I want to willingly contribute to this domain: Blockchain is the underlying technology behind most of the\n cryptocurrencies and it has a potential of changing the way we work\n and communicate, making it more secure, efficient, and trustworthy. There is a immense amount of speculation going around in this domain\n with the rise of Bitcoin. What\u2019s happening with blockchain\n technology, I would say, is similar to the great American gold rush\n that happened in the mid 1800s. Innovators, investors, entrepreneurs, technologists all are hovering\n over the same underlying idea on how these cryptocurrencies work and\n how could blockchain be leveraged to create use-cases beyond\n crypto-systems. Also, I would love to mention few quotes to support the escalating phenomenon of Blockchain : The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping\neverything along its way by the force of its progression. -- William\nMougayar Over the next decade, there will be disruption as significant as the Internet was for publishing, where blockchain is going to disrupt\ndozens of industries, one being capital markets and Wall Street. -- Patrick M. Byrne I will help people in understanding the bits and bytes of this domain, including the basic cryptography concepts, algorithms and how to utilize the power of Python language to build their own blockchain. As we progress, we would engage into more advanced concepts pertaining to scalability and deployment once we build a minimalist prototype of aforementioned. Using on-the-go learning while developing will serve as a pivotal entry point for all the people who are willing to enter into this space and planning to build smart-contracts or invest in cryptocurrencies. Agenda for workshop : Introduction to Blockchain: Existing problems, what is Blockchain, why it matters, gist of few use-cases, related concepts. Python revisited: Functions, libraries, object-oriented programming terminologies, basic data structures, basics of zen of python. Blockchain under the hood: Cryptography 101, underlying data structure and algorithms, conceptual terminologies. Python and Blockchain amalgamated: Create blockchain using python. User-friendly front-end: Integrating the scripts in previous section with a basic front-end. Discussion regarding scalability methods and resources. Generating self-help focused Pypi library called pymyblockchain . (optional) Q&A session. Note: The above agenda is subject to change. It is tentative for now. Any changes will be updated here itself", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "Basic python: Functions , Classes and Objects , Use of Libraries *No prerequisites apart from aforementioned. Even a person who is new to python will be able to grasp everything in workshop", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchain-by-implementing-it-from-scratch-in-python~bq57b/", - "title": "Understanding blockchain by implementing it from scratch in Python" - }, - { - "Content URLs": "My python script", - "Description": "Information is being generated at an exponential rate everyday. There are multiple sources generating information. It becomes really tedious for a person to go and visit all the sources to obtain information. It could be of great help to the person if there can be a single source which cumulatively providing all the links of news generated by different newspapers. This is where web scraping and automation comes into picture. In this talk I want to explain how to scrape webpages hassle free , gather information and represent the gathered content in a easy to visualize format. By executing just a single Python file we can get all the data what we want from the web. Its not just about collecting the data, it is to reduce the repetitive work which a person does again and again to achieve the same goal. We can put repetitive work into a module and leave it upon the computer to do the same. This in turn will help us channelize our time more on the information rather than gathering that information. Agenda of Talk: Introduction: Web scraping, automation tools, parsing and scraping python libraries. How it helps in learning python extensively: My experience with web scraping and various use-cases on which I utilized. Q&A session.", - "Last Updated": "12 Jun, 2018", - "Prerequisites": "None", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "12 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping-and-automation-for-novice-users~er52d/", - "title": "Webscraping and automation for novice users." - }, - { - "Content URLs": "https://www.slideshare.net/mobile/karx01/micro-python-pycon-india-2018-proposal-kartik-aror", - "Description": "This session will aim to achieve 2 objectives Introduce you to (in a fun and practical way), what is microPython. equip you to be up and running to build your own systems!", - "Last Updated": "13 Jun, 2018", - "Prerequisites": "Must know a guy who owns a raspberry Pi", - "Section": "Embedded python", - "Speaker Info": "Hello World. I am Kartik Arora, founder at Akriya Technologies . Before starting my journey in the wild, I worked for Rivigo for a few months, and in Bing Team during my 2 years at Microsoft", - "Speaker Links": "https://twitter.com/karx_brb https://www.facebook.com/karx01 https://www.linkedin.com/in/karx01 https://github.com/kar", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kartik Arora (~kartik53)", - "created_on": "13 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/micropython-time-to-get-building~av58e/", - "title": "MicroPython : time to get building" - }, - { - "Content URLs": "GitHub More content will be updated soon", - "Description": "What is Transfer Learning? Transfer Learning is the method of reusing our existing knowledge developed for one task to solve a similar task. Say, you want to detect cars on night-time images and instead of learning from scratch we could reuse our existing knowledge from a model which has been trained on day-time images. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. I believe Transfer Learning is a major achievement in our quest for Artificial General Intelligence (AGI) as Transfer Learning allows us to generalize our knowledge which is something we humans excel at. Andrew Ng, ex-chief scientist at Baidu, co-founder of Coursera and professor at Stanford, said during his widely popular NIPS 2016 tutorial, \u201cTransfer Learning will be the next driver of ML success.\u201d Training Deep Neural Networks from scratch is an expensive process. Not only does it require a lot of compute resources and time, deep Learning models require a huge amount of data and it is a major bottleneck when it comes to start-ups and niche areas of research like health care. What you will learn :- How to build an image classifier in a few minutes using Transfer Learning When and how to fine-tune pretrained models Freezing layers of a pretrained model depending upon the scenario Using ConvNet as a feature extractor Using differential learning rates Constraints of using pretrained models Transfer Learning : Beyond Computer Vision Cross-Lingual Domain Adaptation : Using the knowledge we have learnt from one language and applying our knowledge to another language is another application of transfer learning with huge potential. Cross-lingual adaptation methods would allow us to leverage the vast amounts of labeled data we have in English and apply them to any language, particularly languages with very less labeled data such as Indian languages. Reinforcement Learning and Learning from Simulations : Training an agent (in Reinforcement Learning) to achieve general artificial intelligence directly in the real world is too costly and hinders learning initially through unnecessary complexity. It is better to train an agent in a simulated environment such as the OpenAI Gym before deploying it in the real world. Eg: Self-driving cars Agenda 1.Introduction to Computer Vision (3 min) 2.Introduction to Transfer Learning (3 min) 3.Why should you use Transfer Learning? (2 min) 4.When to use Transfer Learning? (2 min) 5.Build an image classifier in minutes using Transfer Learning (2 min) 6.Effective Transfer Learning techniques (6 min) 7.Feature Extraction using pretrained models (3 min) 8.Constraints of using pretrained models (1 min) 9.Transfer Learning beyond Computer Vision (3 min) 10.Transfer Learning : A right step towards Artificial General Intelligence (AGI) (2 min) 11.Q&A session (3 min", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of deep learning Love for Pytho", - "Section": "Data science", - "Speaker Info": "Hi! I\u2019m fascinated by AI and it\u2019s applications particularly in art and culture - generating art, fashion styles, music, literature, etc. I\u2019m a 3rd year student at SRM Institute of Science and Technology, Chennai studying Computer Science Engineering. I\u2019m also part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in AI, Blockchain, Computational Biology, Electrical Systems, Internet of Things, and Mixed Reality. I'm also a part of a club which organizes PyData KTR . I will be talking about \"Abstract Art using Compositional Pattern Producing Networks\" in the next meet-up which is scheduled on 14th July, 2018. I\u2019m currently working as a Computer Vision intern at Cogknit Semantics, Bangalore. I'm working on a fashion recommender system which analyses images of clothes and suggests matching clothes to go along with it. Eg: Suggests matching pants and shoes if the input image is a shirt. I love Python because of it\u2019s simplistic philosophy and lucid coding style which allows me to think more about model architectures rather than fixing bugs in my code", - "Speaker Links": "Connect with me on LinkedIn Find me on GitHub Follow me on Twitter E-mail me at : niladrishekhardutt@gmail.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "niladri99", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-subtle-art-of-effective-transfer-learning~dw5ra/", - "title": "The Subtle Art of Effective Transfer Learning" - }, - { - "Content URLs": "The GitHub repository and the talk slide are: Slides : Will be updated soon. Github repo : Will be updated soon.", - "Description": "Problem description : Deep learning algorithms have shown great results in speech recognition domain, So here we have used deep learning techniques to enable the machines to read the lips from a video without sound better than humans. By analysing the movement of lips of a person we are trying to predict what that person is trying to speak.\nAutomated Lip reading can be helpful in many ways. Some of them are: Silent dictation in public spaces. Covert conversation. Helping the people with speaking ade in talking to other people. Improved hearing aids. Speech recognition in a noisy environment. The talk will be focused on : How the problem should be tackled. Discussion of different phases Algorithms and python libraries used for implementation.", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. \nBeginner's knowledge of the following items would be helpful. Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack Basic understanding of OpenCV: A good resource for the same is: Udemy OpenCV Basics . This much is enough, we would also be covering the important content in the talk. Basic Knowledge of Convolutional Neural Networks : An excellent resource to understand this is CNN by Datacamp . The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working. Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is: Metrics for Evaluations Basic understanding of Recurrent Neural Networks : An excellent resource to understand this is Understanding LSTM Networks . Similar to CNN the motive should be to understand the basic working of Recurrent Neural Networks. The coding part will be discussed in the talk.", - "Section": "Developer tools and Automation", - "Speaker Info": "The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn", - "Speaker Links": "The LinkedIn Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal The Github Profile are: Saquib Hashmi Kaushtubh Kumar Dhruv Mittal", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saqhas", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-lip-reading-using-convolutional-neural-networks-in-python~ejMvd/", - "title": "Automated Lip reading using convolutional Neural Networks in python" - }, - { - "Content URLs": " Research Paper Github repository of project with over 100 stars: pyCAIR Beta release on PyPI: pyCAIR Docs: pycair.readthedocs.io", - "Description": "In this talk, I will speak about a simple yet very powerful image manipulation mechanism. The naive user utilizes the services of any standard toolkit, be it a web service or a remote application for image manipulation. The black box approach to this process is: A user provides an image and other parameters as input to the toolkit which in turn produces the results and returns it back to the user. Often these results are not up to the mark. The image sometimes gets distorted, misaligned or blurred. Deviating from the standard mechanisms, I would like to talk about a technique called as Content aware image resizing . The primary factor in this technique is the content . It is the content which drives the entire technique. The image is cropped, enlarged or modified keeping in mind the primary factor. I will talk about an algorithm called as Seam Carving which is used under the hood to achieve the aforementioned technique. It is this algorithm and the power of Python libraries , that makes this technique perform better than the standard mechanisms. Agenda of Talk: Introduction: Basics of seam carving, how the algorithm works Understanding energy concepts, basics of computer vision and dynamic programming Walk over the pseudo-code and dry run of algorithm Comparative analysis of this technique with standard mechanisms Q&A Session Conclusion", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Developer tools and Automation", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my\n goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pycair-understanding-content-aware-image-resizing-using-python~bkK6b/", - "title": "pyCAIR: Understanding Content-Aware Image Resizing using Python" - }, - { - "Content URLs": "Will be provided soo", - "Description": "Everyone need not to know everything to build something great. If you are a student and wants to build a major/minor or a professional level project without worrying about the DevOps/Servers and its cost. If you are a Data Scientist and works with files/data and want to make your analytical tool public but you don't want to get in Server handling and learning some web framework . If you are a Frontend developer or work in a fast paced organisation where shipping out fast, better, robust and always running services are required. If you want to prepare a POC or a working model API fast without the requirement of server engineer. Then, this Talk is the place which your are looking for. This talk will be focused on How one can build really scalable and robust web APIs without learning any web framework that too in a very very easy manner. We will be talking about a python package I have made called Lamlight which makes the process of building web APIs as simple as a Git push . This package provides a CLI tool and answers the limitations imposed by the services like AWS lambdas . Lamlight enables Developer to: Make web APIs without learning any web framework or DevOps. Just focus on the core business logic because everything else it will provide you. (Eg: full python boilerplate, CLI automation tool ) Live code Changes. Put large dependencies on your Serverless web api like Numpy, Scipy, Pandas. Save 80% of time by making the process as simple as Git push. Objective of the Talk: Problems faced in a Servered Architecture. Introduction to Serverless Web APIs. Why Shift to Serverless Web Architecture. Platforms providing these Services and their limitations. Get Faster and beat these Limitations. Problems solved by Lamlight. Explanation of its working. Live demo. Q & A The talk would be extremely beneficial for students, Algorithm developer, Frontend Developer, Data scientists and others who are not familiar with server side development and server technologies or want to save time of server handling but still want their work to be done", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Love for Python Linux AWS(Optional)", - "Section": "Developer tools and Automation", - "Speaker Info": "Hello I am Rohit Negi. I am a developer with 1 year of professional experience and +2 years of freelancing experience. I have a Bachelor's degree and I am currently working as a developer in Elucidata Corporation, where I work on making technical architectures for the system to get connected and work robustly , designing Server APIs, Working with Frontend technologies like Angular to make the robust Frontend apps. I am very passionate about creating new and better stuff", - "Speaker Links": " https://www.linkedin.com/in/rohit25negi/ Email: rohit25.negi@gmail.com", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rohit Negi (~rohit17)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/lamlight-develop-webmobile-apps-without-learning-django-flask-and-any-other-web-framework~egKke/", - "title": "Lamlight: Develop web/mobile apps without learning Django, Flask and any other web framework" - }, - { - "Content URLs": "GitHub Repo: https://github.com/sleebapaul/gospel_of_rnn.git Google Colab Notebook: https://drive.google.com/file/d/1qh94MdQr9SeTLxGkMJc6kZGguRID8LqW/view?usp=sharing Blog: https://sleebapaul.github.io/rnn-tutorial", - "Description": "Language modeling was a complex task of previous days. But advancements in Deep Learning has solved this problem very effectively. Using Recurrent Neural Networks architecture, I've built a language model which can effectively generate the fifth gospel of bible by learning from four existing gospels. This model is also able to divide verses and chapters along with meaningful passages", - "Last Updated": "14 Jun, 2018", - "Prerequisites": " Recurrent Neural Networks basics Deep learning basics Language modeling basics Familiarization with PyTorch", - "Section": "Data science", - "Speaker Info": "Sleeba Paul is a Power System graduate and published researcher who loves intelligent machines. He currently works as a Machine Learning Engineer at Refly; an AI startup in India where he works on content enhancement and video analytics", - "Speaker Links": "Personal website: http://sleebapaul.github.io/ LinkedIn: https://www.linkedin.com/in/sleebapaul/ Github: https://github.com/sleebapau", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sleeba Paul (~sleeba)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gospel-of-lstm-how-i-wrote-5th-gospel-of-bible-using-lstms~elLMe/", - "title": "Gospel of LSTM : How I wrote 5th Gospel of Bible using LSTMs" - }, - { - "Content URLs": " Hello world of chatbots world - wordbot An Experiment with Opensource chatbot engine - RASA NLU ", - "Description": "Google Assistant and Siris\u2019 of the world have tickled our curiosity enough to deep dive and understand under the hood technologies that make a chatbot. Though we don\u2019t have Google level of data to create a generalized chatbot, we can use the existing NLP engines and create chatbots that produce valuable results in a specific domain. For eg., anything that goes in your FAQ page can be converted into content for a chatbot. In this talk, I\u2019ll share my 2-year journey with chatbots. Existing bot platforms and how to leverage it to build your own chatbots. I'll also share the internals of an opensource chatbot engine - Rasa NLU. Key Takeaways Chatbot\u2019s architecture (3 mins) Natural language Processing, Understanding, and Generation what and how it plays an important role in building chatbots(3 min) How to use existing chatbot engines to build a chatbot(6 min) Internals of a chatbot engine - Demystifying RasaNLU (15 mins)", - "Last Updated": "14 Jun, 2018", - "Prerequisites": "Basic knowledge of Pytho", - "Section": "Data science", - "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape - Tech Enthusiast - Django & Chatbot specialist - Mentor/Speaker Build2learn , Chennai Geeks. Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", - "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavan", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Bhavani Ravi (~bhavaniravi)", - "created_on": "14 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/chatbots-101-by-demistifying-rasanlu~bm6Gd/", - "title": "Chatbots 101 - By Demistifying RasaNLU" - }, - { - "Content URLs": "Source code available on Github: https://github.com/Cheukting/Style-mimicking-text-generator Example slides: https://slides.com/cheukting_ho/pylondinium1", - "Description": "Computers are getting closer to speak like humans. But can we even make them speak in particular ways, like as Trump or Shakespeare? In this hands on talk we will see how this is possible with the latest deep learning techniques combined with word embeddings and other advanced NLP technique. In this talk, first we would introduce two neural network and machine learning mechanisms which in popular and widely used in NLP (natural language processing): Word Embeddings and Recurrent Neural Network. Word Embeddings is a way to extract the context of a word by \u201clearning\u201d its presence in a paragraph; while Recurrent Neural Network, including LSTM (long short-term-memory), enable us to \u201ctrain\u201d sequential data. After that, we will showcase how to implement these mechanisms in a neutral network. With that, we can \u201cbuild\u201d a machine to generate articles, plays or speeches in the style of the training corpus and have lots of fun. In the first half of the talk, concepts of how Word Embeddings and LSTM works will be explained. Audiences will understand why this is essential in the field of NLP and why we are using it. In the second half, a code demo will be used to showcase how to implement these mechanisms. Through an example, audiences will learn how Keras is used together with Tensorflow and Python to build a sequential neutral network. We will showcase generating a paragraph using Shakespeare\u2019s play and another one using Trump\u2019s speech. This talk is for people who have some experience with data science and understand the concept of how a neural network works, but would like to go deeper into the details of how does it applied to NLP to solve more complex AI problems. We used very simple code but did a complex task like text generation, that opens the door for a lot of people who wants to experiment with deep learning", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "Basic concepts of Neural Network like Stochastic Gradient Descent and back propagation, as it will not be covered in the talk due to time limit", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-keras-building-an-ai-that-talks-like-shakespeare-or-trump~enX7b/", - "title": "Deep Learning with Keras : Building an AI that Talks like Shakespeare or Trump" - }, - { - "Content URLs": "Project source code on Github: https://github.com/Cheukting/GCP-GPU-Jupyter Demo code: https://github.com/Cheukting/jupyter-cloud-demo Example slides: https://www.slideshare.net/CheukTingHo/pycon-israel-launch-jupyter-to-the-clou", - "Description": "There are lots of reasons using a cloud service is favorable, but how to make sure consistency between development and deployment? With Docker and Terraform, we can create the same environment on cloud easily. For example, we will deploy a Jupyter notebook on Google Cloud Platform using both tools. In this talk, we will use a task: hiring a GPU on Google Cloud Platform to train neural network, as an example to show how an application can be deployed on a cloud platform with Docker and Terraform. The goal is to have Jupyter Notebook running in an environment with Tensorflow (GPU version) and other libraries installed on a Google Compute Engine. First we will briefly explain what is Docker and what is Terraform for audiences who has no experience in either or both of them. Some basic concepts of both tools will also be covered. After that, we will walk-through each steps of the work flow, which includes designing and building a Docker image, setting up a pipeline on Github and Docker Hub, writing the Terrafrom code and the start up script, launching an instance. From that, audiences will have an idea of how both tools can be use together to deploy an app onto a cloud platform and what advantages each tool can bring in the process. This talk is for people with no experience in application deployment on cloud service but would benefit form computational reproducibility and cloud service, potentially data scientists/ analysts or tech practitioners who didn\u2019t have a software developing background. We will use an example that is simple but useful in data science to demonstrate basic usage of Docker and Terraform which would be beneficial to beginners who would like to simplify their work flow with those tools", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Developer tools and Automation", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/launch-jupyter-to-the-cloud-an-example-of-using-docker-and-terraform~boKXb/", - "title": "Launch Jupyter to the Cloud: an example of using Docker and Terraform" - }, - { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/seatgeek/fuzzywuzzy Source code available on Github: https://github.com/Cheukting/fuzzy-match-company-name Slides (not finalized): http://slides.com/cheukting_ho/fuzzy-matchin", - "Description": "Ever encounter a tricky situation of knowing there\u2019s names that are the same, but matching strings straight away leads you no where? All you need is FuzzyWuzzy, a simple but powerful open-source Python library and some wit. This talk will demonstrate how to efficiently fuzzy match company names. Matching strings should be one of the first natural language processing problem that human encounter since we start use computer to handle data. Unlike numerical value which has an exact logic to compare them, it is very hard to say how alike two strings are for a computer. One may compare them character by character and have an idea of how many characters in the pair of stings are the same. Unfortunately in most application we need computer to perceive strings like we do and therefore we have to use fuzzy matching. Fuzzy matching on names is never straight forward though, the definition of how \u201cdifference\u201d of two names are really depends case by case. For example with restaurant names, matching of words like \u201ccafe\u201d \u201cbar\u201d and \u201crestaurant\u201d are consider less valuable then matching of some other less common words. Also, do we consider company names that matches partly (like \u201cHappy Unicorn company\u201d and Happy Unicorn co.\u201d) are the same? In the first half of the talk Levenshtein Distance, a measure of the similarity between two strings, will be explained. Different functions in FuzzyWuzzy like \u201cpartial_ratio\u201d and \u201ctoken_sort_ratio\u201d will also be explored and compared for difference. It is very important to understand our tool and choose the right one for our task. Then in the second half, we will start tackling the example problem: matching company names, we will show that besides using FuzzyWuzzy, we have to also handle problem like finding and avoid matching of common words and speeding up the matching process by grouping the names. By combining all tricks and techniques that we demonstrate, we will also evaluate how efficient this method is and the advantage of using this method. This talk is for people in all level of Python experience who would like to learn a trick or two and would like to be able to solve similar problems in the future. Theory of how the library works will be explained and It is easy to be pick up even for beginners", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fuzzy-matching-smart-way-of-finding-similar-names-using-fuzzywuzzy~epKVd/", - "title": "Fuzzy Matching - Smart Way of Finding Similar Names Using FuzzyWuzzy" - }, - { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/networkx/networkx Slides (not finalized): https://docs.google.com/presentation/d/1y_Wmuv_hqs8OZTI8XLJ5ajvjEpllK7Xeifa52yTpw-k/edit?usp=sharin", - "Description": "When you make a search for a hotel room, do you know how many travel agents are searching for you at the same time? In this talk, we demonstrate how to use the millions of searches a sourcing company received to build a network of travel agents and finding the main hubs among them using NetworkX. Network analysis is getting more and more attention in Business Intelligence, people hope to get information out of the structure of an organization or a communication network. In this talk, we use the hotel room search requests from travel agents, including online public website, B2C, B2B and B2B2C, to build a relational network among them. By using this network as an example, we demonstrate how insights can be extract by studying network properties. In the first half of the talk, we will explain how the network is built using NetworkX, an open-source python library that is designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. When 2 agents are making the same search at the same time , a link ( or an \u201cedge\u201d in network analysts terms) is made pointing form the initial searcher to the subsequent searcher. Using a list of these searches, a directed graph is built. We will also demonstrate how to pick the biggest connected component out form the graph. In the second half, with the graphs created, we show how different functions of NetworkX can be used to study the graphs. By compare the graph properties of our graph to the other popular network graphs, we can get the insight of how the network was created. Also by studying the graphs, we can understand the behavior of the agents and can even figure out which agents are acting as main hubs in the network. This talk is for people who are interested in network analysis and would like to see how it can be used in a business case. Audiences with any level of python experience can learn some basic concept of network analysis work and how it can be applied to provide business insights", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-understanding-agent-connections-using-networkx~bq5pb/", - "title": "Case Study in Travel Business - Understanding agent connections using NetworkX" - }, - { - "Content URLs": "The library shown in the talk is an open source library which is available on Github: https://github.com/welch/seasonal Example Slides: https://www.slideshare.net/CheukTingHo/pydata-amsterdam-2018-time-series-analysis-with-seasonal-data-9909335", - "Description": "For time series analysis, everyone\u2019s talking about ARIMA or Holt-Winters. But there\u2019s other models which could also break down a seasonal series into trend, seasonality and noise. We will use an open source Python library called Seasonal to analyse B2B worldwide travel data. Times series analysis is an important part of data analysis for lots of businesses. It is very often for stakeholders to be interested in the performance of the business by analyzing measurements of profit, cost, number of sale, number of searches etc over time. In this talk, we will do a case study of showing how we estimate the impact public holidays made on the travel business. The method of analyzing the time series by seasonal breakdown will be explored and the work flow of solving the problem will be explained. In the first half of the talk, an introduction about time series and its characteristic will be explained for audiences who is new to analysis on time series. The data we use will be from a business to business travel company. It has seasonality thought out the year, a weekly cycle and also a growing trend in business. As the company have clients around the world, data from different countries will shows different behaviors as well. Therefore, before we show the analysis, the complexity of the data will be explored. In the second half, we will introduce a open source Python library called Seasonal. Using this package, we will demonstrate how to break down the travel data and extract the fluctuation of the sale in different countries. By comparing the fluctuation and Google calendar, public holidays in different countries can be spotted and their impact on the business can be estimated. This talk is for people who are interested in time series analysis and its application in business. Audiences with or without experience would also found this talk useful in giving them insights in how a business could benefit in making use of the data and doing a proper time series analysis", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "None, it's a beginner friendly talk", - "Section": "Data science", - "Speaker Info": "After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business. Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion", - "Speaker Links": "Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw GitHub: https://github.com/Cheukting Slide Share: https://www.slideshare.net/CheukTingHo/presentations Slides.com: https://slides.com/cheukting_ho Speaker Bio: https://www.papercall.io/speakers/26654/ Twitter: https://twitter.com/cheukting_ho LinkedIn: https://www.linkedin.com/in/cheukting-ho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Cheuk Ting Ho (~Cheukting)", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/case-study-in-travel-business-time-series-analysis-with-seasonal-data~er5pd/", - "title": "Case Study in Travel Business - Time Series Analysis with Seasonal Data" - }, - { - "Content URLs": " Code will be updated on github very soon.", - "Description": "There are many framework available in the market for free and with a lot\u2019s of feature like Django , Flask , Tornado . These framework help us to build web application and serving the files over the network without worrying about the low level details like how it works , how the files are being severed to the clients , web browser and how it handles the clients to be connected and serving the data to the lot\u2019s of clients with minimum amount of time with managed thread. So in this talk I\u2019ll share my knowledge how does the web server work and how we can build our own framework like other available framework and further enhance it , to make it big, and to handle the clients with multiple processes and threads. In this talk I will be talking about : What is a WebFramework and How does a web framework work? How we can make a simple web sever to serve the \u201chello world\u201d webpage to the browser How we can make the HTTP custom request header to tell the browser about the current status of request on the different situation like 200 , 404 , 500. how to server files like html, css to generate the advance webpages using socket to the browser. Getting the requested URL Params and serving the files over the network. Making a Download link and let the user to download the files over socket. Improvement of request and response time of the web server and optimising it so that the web server can handle more and more clients over the network. ", - "Last Updated": "15 Jun, 2018", - "Prerequisites": "1. Basic python understanding. 2. Python installed on your system. 3 .Socket library (you can install it using the pip installer", - "Section": "Core python and Standard library", - "Speaker Info": "I am Nawneet Kumar, CTO at Elezire Technologies Pvt. Ltd. I have worked in Different Projects and in Different Languages in my past year. I have worked in era like IOT Development , Android Application Development , IOS Development and Web Development", - "Speaker Links": "Linkedin : https://www.linkedin.com/in/nawneet-kumar-77b64814b/ github : https://github.com/navSharma4", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "nav.sharma47", - "created_on": "15 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-own-webframework-like-django-flask-tornado-to-serve-web-application-using-core-socket-programming~av55e/", - "title": "Building Own WebFramework like Django , Flask , Tornado to serve Web Application using Core Socket Programming" - }, - { - "Content URLs": "Apache_Build_Monitor Jenkins' REST API & Pytho", - "Description": "As a build and release engineer, have you felt how good it would be to know the status of scheduled nightly builds before you reached office ? As a developer, have you wondered, while you were away from the desk, what's the status of quality gate builds that should be passed before the changes can be integrated to the mainline ? Intent of this talk is to outline what's offered via Jenkins's REST API and showcase some of the possibilities by consuming the API using Python", - "Last Updated": "16 Jun, 2018", - "Prerequisites": " Read-up docs on Python libraries XML, JSON Capability to follow and assimilate code snippets", - "Section": "Developer tools and Automation", - "Speaker Info": " Speaker works for a CyberSecurity firm in Bengaluru, India Likes being outdoors and reading books.", - "Speaker Links": "Linkedi", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ramanathan Muthaiah (~ramanathan)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/consuming-jenkinss-rest-apis-in-python~dw58a/", - "title": "Consuming Jenkins's REST APIs in Python" - }, - { - "Content URLs": "http://github.com/gnsrikanth/simplelinuxbackdoor/ https://medium.com/@gnsrikanth/creating-a-tcp-backdoor-using-python-9edafc213f9", - "Description": "In this talk, we discuss how python scripts can be used in the world hacking. Python can be used to automate many tasks and we see network protocols using python. Programming isn't just codes, but it's a way of communication. This talk is more of an awareness about the possibilities of python can be used and hacking is one of them. We break down steps to hack a system and automate tasks using python. Topics covered: Sockets in python Using TCP, UDP protocols and creating a Server/Client A basic backdoor for windows Using HTTP protocol to steal users data Using encryption to obfuscate network traffic Subprocess module Pyinstaller to make binaries of malware Bypassing antivirus (we will test it by uploading .exe to virustotal) Using Sqlite3 to retrieve chrome passwords Emailing subprocess outputs with python Send data to google forms as POST Simple Ransomware code Other Python tools for hacking", - "Last Updated": "16 Jun, 2018", - "Prerequisites": "Basics in python, Operating system fundamentals, Networking basics", - "Section": "Networking and Security", - "Speaker Info": "I am Grandhi Srikanth, and truly passionate in cyber security. I hold C|EH, CCNA in Routing and Switching, Cyber Ops certification and interested in creating malware codes and as python makes it simple, I use python", - "Speaker Links": "Twitter: @gn_srikanth LinkedIn: https://www.linkedin.com/in/grandhi-naga-srikanth/ Github: https://github.com/gnsrikant", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Naga Srikanth Grandhi (~naga_srikanth)", - "created_on": "16 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/backdooring-windows-with-python~ax5Bb/", - "title": "Backdooring windows with python" - }, - { - "Description": "We have a word for it now - Domotics . The fun started a year back when I laid hands on this beautiful device from Amazon, which could not only manage your music, reminders, lists but also make calls and send messages. Basically, a smart phone in the cloud to be used without hands. But a developer sees endless possibilities with this powerful tool. Although speech recognition technology itself is nothing new, Amazon Echo has made its way to the homes of regular consumers. This talk is specially focused on giving a head start to the attendees about building and using powerful applications in python using an Alexa device. Being a python developer for the past 10 years and working on alexa skills for the past year, I intend to share my experience with the python community and enthusiasts. Broadly, this talk will be covering the following topics: How the echo framework and Alexa skills work An introduction to creating alexa skills in python with flask-ask Handling requests , responses , contexts and sessions . Testing applications with ngrok and deploying to the cloud. A sneek peek into other home automation possibilities like micropython embedding with popular microprocessors. The talk would be illustration and example driven and will include demos of cool app(s) I have been working on", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "This talk is intended for developers who have a decent grasp on the basics of the python framework and trends, although you do not need knowledge of any specific packages or libraries. Just an enthusiastic mind is enough! The primary takeaway of this talk would be learning how to get started ideating and building applications for an alexa enabled smart home device and discuss some cool developer tips", - "Section": "Developer tools and Automation", - "Speaker Info": "Sonal Raj ( @_sonalraj ) has been an avid pythonista for 10 years. He has been working as an integral part of the financial technology industry for the past 4 years. Sonal holds a masters in Information Technology and has been a research fellow at the Indian Institute of Science, Bangalore. His domains of interest include distributed systems and graph databases, and he loves to explore new gadgets and develop new technology. He is also the author of the best selling book 'Neo4j High Performance' ", - "Speaker Links": " Talk at PyCon India 2014 Talk at PyCon India 2013 Real Time Computation with Apache Storm - IISc Bangalore Human Computer Interaction Systems : Slides Website Github Reasearch Profile", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sonal Raj (~sonal)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/alexa-enabled-smart-home-programming-with-python~dy5nd/", - "title": "Alexa enabled smart home programming with Python" - }, - { - "Content URLs": "A library for ANTLR that is being built by me is available here: https://gitlab.com/virresh/coala-antlr ANTLR's official page: http://www.antlr.org/ My blogs related to ANTLR in Python: https://virresh.wordpress.com/tag/antlr/ An example calculator: https://github.com/virresh/ANTLR4-Exampl", - "Description": "This talk aims at introducing ANTLR for python 3, and talk about Abstract Syntax Trees. It will present an overview of the process, the intricacies and will end with a concrete example to show the utility. ANTLRv4 is a tool that can generate parse trees for any compatible grammar, and provide tools to walk through that tree, so I will illustrate how to use that rather than dwelling more on the theory aspect of the parse trees and boost up the development of language tools. There is a speciality with ANTLRv4, we can separate context from the grammar (so we can get very close to the expectation that grammars are context free). I expect the session to be beginner friendly so no pre-requisites save some basic python expected. Also I will cover some basic examples, and also a demo of an actual language grammar to create a meta-program if time permits. The session is expected to have the following things: What is a grammar ? What are Parse trees and how do they compare to ASTs ? What is ANTLR ? (The parser generator and the runtime provided) How do we use a parse tree ? (dwelling on setting up the environment for ANTLR based development and a short, basic calculator building example) Visitors and Listeners A short real world example on detecting technical constricts in actual programming languages (probably Python itself)", - "Last Updated": "17 Jun, 2018", - "Prerequisites": "A working knowledge of python basics and some familiarity with some sort of command line interface is ideal (best suited if you are familiar with any unix/linux based systems, simple script invocation etc", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm a student presently pursuing BTech in CSE at IIIT-Delhi, and am a GSoC student this year at coala.io and have been programming various stuff using python for around two years. I am developing a library to facilitate easy usage of ANTLR for building linting tools. I've worked on a large array of technologies in any area that I get to know about, ranging from Full stack development, to Systems programming to Language tools. I do my best to pick up and experiment with whatever technologies I can, and I love to learn ", - "Speaker Links": "GitHub: https://github.com/virresh Website: https://virresh.github.io/ Blogs: https://virresh.wordpress.com/ LinkedIn: https://www.linkedin.com/in/virresh", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viresh Gupta (~virresh)", - "created_on": "17 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-antlr-with-python~az5ye/", - "title": "Using ANTLR with python" - }, - { - "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. \nThe website for the workshop is here . \nYou can find the introduction slides here , the sphinx tutorial here and the exercises in form of IPython notebooks. Note: The notebooks are hosted statically, you can download from here and run locally to have an interactive session. See Also: Workshop content for PyCon conference in 2015 , SciPy conference in 2016 , 2014 and 2013 ", - "Description": "In this tutorial we will introduce attendees to SymPy, a computer algebra system (CAS) written in Python. We will show basics of constructing and manipulating mathematical expressions in SymPy, the most common issues and differences from other computer algebra systems, and how to deal with them. In the last part of this tutorial, we will show how to solve practical problems with SymPy. This will include showing how to interface SymPy with popular numeric libraries like NumPy. Attendees will take home an introductory level understanding of SymPy. This knowledge should be enough for attendees to start using SymPy for solving mathematical problems and hacking SymPy's internals (though hacking core modules may require additional expertise). SymPy is a pure Python library for symbolic computation. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. The tutorial will cover the following topics and more. Introduction What is Symbolic Computation? A More Interesting Example The Power of Symbolic Computation Why SymPy? Gotchas Symbols Equals signs Two Final Notes: ^ and / Basic Operations Substitution Converting Strings to SymPy Expressions evalf lambdify Printing Printers Setting up Pretty Printing Printing Functions Simplification simplify Polynomial/Rational Function Simplification Trigonometric Simplification Powers Exponentials and logarithms Special Functions Calculus Derivatives Integrals Limits Series Expansion Finite differences Solvers A Note about Equations Solving Equations Algebraically Solving Differential Equations Matrices Basic Operations Basic Methods Matrix Constructors Advanced Methods Advanced Expression Manipulation Understanding Expression Trees Recursing through an Expression Tree ", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "The tutorial will only assume a basic knowledge of Python. No prior knowledge of SymPy or other Python libraries is required, although it is suggested that attendees be familiar with the IPython notebook. A mathematical knowledge of calculus is recommended. We recommend that the attendees install the Anaconda Python distribution which includes SymPy, NumPy, and IPython. Once Anaconda is installed simply type the following in a terminal to install the necessary packages: $ conda install numpy ipython-notebook sympy Other alternative installation instructions can be found here: http://docs.sympy.org/dev/install.htm", - "Section": "Data science", - "Speaker Info": "SymPy India developers will be conducting the workshop: Shekhar Prasad Rajak : GSoC 2016 | Solvers Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers Module Ravicharan : IIIT Allahabad | Core Developer at SymPy, GSoC 2018 | Combinatorics module Jashanpreet Singh : TIET Patiala | Core Developer at SymPy, GSoC 2018 | Beam Bending module", - "Speaker Links": " Resource repository: https://git.io/sympy-pycon-india-18 SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://youtu.be/5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://youtu.be/nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://youtu.be/AqnpuGbM6-Q SymPy, SciPy 2014: https://youtu.be/Lgp442bibDM Symbolic Computing with SymPy, SciPy 2013: https://youtu.be/dAgShwIx72c", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Yathartha Joshi (~Yathartha22)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-python-using-sympy~aAold/", - "title": "Symbolic Computation with Python using SymPy" - }, - { - "Content URLs": " Hydra Draft Book of Hydrus Hydra Ecosystem Wiki Hydrus Hydra Flock Demo Hydra CG homepage I'll be sharing my slides after the talk", - "Description": "Introduction 3rd generation Web APIs enables creation of truly RESTful services with all its benefits in terms of scalability, maintainability, and evolvability. This allows to create Generic Consoles and loosely coupled clients. The main objective of this talk is to provide an overview of Hydra and Hydrus and how we can create such APIs using Hydrus. Hydra Building Web APIs seems still more an art than a science. How can we build APIs such that generic clients can easily use them? And how do we build those clients? Current APIs heavily rely on out-of-band information such as human-readable documentation and API-specific SDKs. However, this only allows for very simple and brittle clients that are hardcoded against specific APIs. Hydra, in contrast, is a set of technologies that allow us to design APIs in a different manner, in a way that enables smarter clients. Hydrus Hydrus is a Flask server meant to build and deploy Hydra-based Web APIs in a straightforward and effective way. Hydrus utilises the power of Linked Data to create a powerful REST APIs to serve data. Hydrus uses the Hydra draft standard for creation and documentation of it's APIs. The flow of the talk will be as follows: My Introduction What is Hydra Draft? A detailed introduction to Hydrus How can Hydrus be used to create Semantic Web APIs easily? Some Use Cases A short demo Q/A session", - "Last Updated": "18 Jun, 2018", - "Prerequisites": " Python Basic knowledge of Web APIs", - "Section": "Web development", - "Speaker Info": "My name is Akshay Dahiya. I'm a Mentor and Organization Admin for Python Hydra in Google Summer of Code 2018 and I love working on Semantic Web and Artificial Intelligence-related projects. I also mentor a couple of students across various Udacity Nanodegree programs (FullStack Nanodegree, React Nanodegree and Deep Learning Nanodegree) in my free time", - "Speaker Links": " http://www.xadahiya.me/ https://github.com/xadahiya/ https://www.linkedin.com/in/xadahiya/ http://www.typingeek.com/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Akshay Dahiya (~xadahiya)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3rd-generation-web-apis-using-hydra-and-hydrus~dBpYa/", - "title": "Creating 3rd generation Web APIs using Hydra and Hydrus" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1_hyRLHdITpIMzhAbpxuaTQkm6qop4ZWQt6ERGW4MFag/edit?usp=drivesdk&ouid=10471550379351873801", - "Description": "This is a simple talk about web scraping using python.In this lecture we going to have a clear picture of webscraping. \nBy the end of the lecture audience are going to have a clear picture of \nWhat is web scraping? \nWhat is the use of it? \nWhat are the useful libraries in python for web scraping? \nPros and cons of the libraries\nAnd mainly how to parse the Websites with practical examples", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "A little amount of python knowledge is useful but not mandatory. I'm going to explain right from the very beginnin", - "Section": "Others", - "Speaker Info": "I am a student of Vishnu Institute of technology, Bhimavaram. I am studying 2nd IT. I was fallen in love with coding when I listened to the 1st lecture of my academic about C programming. That day changed my life. I have been working on python from January 2018.\nI am a quick learner, self disciplined, self motivated guy. \nMy hobbies are coding and learning new thing", - "Speaker Links": "https://www.sololearn.com/Profile/495149", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Deepak Puppala (~deepak12)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/webscraping~bDrKe/", - "title": "WebScraping" - }, - { - "Content URLs": "Will share the Slides post my Talk through a proper channel", - "Description": "Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. Note: In this workshop all the implementation will be done using PYTHON Session Takeaways: How to use different features of AWS to create your Serverless Application. What is Serverless Computing and how \"Functions as a Service\" is a revolutionary way to develop applications. Understand AWS Lambda Functions, the FaaS offering on Amazon Web Services. Understanding of the AWS services - Lambda, S3, EC2, CloudWatch, API Gateway, RDS, IAM How to access the AWS services using Python libraries in the Lambda Function. Hands On Cloud Native Web Applications Development using AWS Lambda and other offering. Practical examples of how you can combine multiple services and events in AWS and develop applications rapidly using AWS Lambda Functions", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Python: Basic of Python Programming Basics of Python Libraries Usages (Imports) AWS Free Tier account - https://portal.aws.amazon.com/billing/signup?redirect_url=https%3A%2F%2Faws.amazon.com%2Fregistration-confirmation#/start", - "Section": "Web development", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ritu Mehra (~ritu86)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/serverless-application-development-using-aws-and-python~eEvga/", - "title": "Serverless Application Development using AWS and Python" - }, - { - "Content URLs": "SymPy team has developed and delivered many talks and tutorials at SciPy and other conferences. \nWe are constantly building on new content and improving the present at the same time. You can find the introduction slides here ", - "Description": "SymPy is a Python library for symbolic mathematics. It aims to be an alternative to systems such as Mathematica or Maple while keeping the code as simple as possible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.\nThe talk will highlight the following: SymPy, what it is and how it is different from others. What is symbolic computation and how SymPy achieves it. Power of SymPy: Symbolic manipulations Equation solving Calculus Linear Algebra ", - "Last Updated": "18 Jun, 2018", - "Prerequisites": "Basic mathematics, just enough to appreciate the manipulation done by the computer algebra system and Python. No prior knowledge of SymPy or other Python libraries is required", - "Section": "Data science", - "Speaker Info": "SymPy India developers will be conducting the talk: Sidhant Nagpal : NSIT Delhi | Core Developer at SymPy, GSoC 2018 | Discrete module Yathartha Joshi : BTKIT Dwarahat | Core Developer at SymPy, GSoC 2018 | Solvers module", - "Speaker Links": " Resource repository: https://git.io/sympy-pycon-india-18 SymPy website: http://www.sympy.org/en/index.html SymPy live: http://live.sympy.org/ GitHub repository: https://github.com/sympy/sympy Link to previous SymPy Tutorials/Talks Automatic Code Generation with SymPy, SciPy 2017: https://youtu.be/5jzIVp6bTy0 SymPy, EuroSciPy 2017: https://youtu.be/nfRyux3wEhw Symbolic Compution with Python using SymPy Beginner, SciPy 2016: https://youtu.be/AqnpuGbM6-Q SymPy, SciPy 2014: https://youtu.be/Lgp442bibDM Symbolic Computing with SymPy, SciPy 2013: https://youtu.be/dAgShwIx72c", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Yathartha Joshi (~Yathartha22)", - "created_on": "18 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/symbolic-computation-with-sympy~dGxJe/", - "title": "Symbolic Computation with SymPy" - }, - { - "Content URLs": "Coming Soo", - "Description": "It's really hard to escape the 3D buzzword. You find it used in all sorts of places, right from the movies you watch, Games you play, 3D printing , webgl graphics in the browser and VR , AR applications. In this workshop we are going to cover the basics of 3D and do a hands on session on creating 3D Art using a professional open source application called Blender . Of course, python is a major part of blender and we will put your python skills to some good use. What is this workshop NOT about : This is not one of your boring programming workshops. We are not going to try improve your python knowledge ten folds in a matter of 2 hours. What is this workshop about : Come to this workshop if you want to be a kid again and have fun creating art in 3D using Blender and Python !!! Who am I : Hello, Sreenivas here! I am a 3D artist turned programmer. I work in the animation and VFX Industry and battle production issues with the power of python. I love art, technology and excited about combining both. I support open source by evangelizing Blender and Krita . Who are you : You are a person with an open mind, bitten by the curiosity bug and intrigued by how 3D Art is made. You have at least basic knowledge of python and ready to use your super powers to create 3D Art. Takeaway : By the end of the session\u2026 You will know a broad overview of 3D Art . Have a working knowledge of the professional open source 3D application, Blender . Get a deeper understanding of the workflow for creating 3D art. Use your python skills in the process of creating 3D Art.", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Laptop with a decent GPU (any modern laptop) A mouse with a middle click button (scroll which is clickable) Download and install Blender from https://www.blender.org/download/", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-3d-art-using-blender-and-python~aKBxe/", - "title": "Creating 3D Art using Blender and Python" - }, - { - "Content URLs": "Coming soon", - "Description": "Do you know, your favorite superheroes in Avengers , cute characters of Kung Fu Panda and the epic wars of Baahubali were brought to screen with the help of python ? If you are into gaming , you need to thank python for the characters you have played and the world you have explored. Even the next generation technologies like AR and VR use python to deliver their magic to you in new formats. It won't be a overstatement if we say python is the backbone of the animation Industry In this talk we go behind the scenes and see how our favorite programming language is used in the animation industry, why it plays a huge role and the kind of applications built with it", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "A bit of curiosity and interest in learning about usage of python in various industries, usually less represented in the python community", - "Section": "Others", - "Speaker Info": "Sreenivas Alapati Developer / Artist Sreenivas started his career as an artist at Rhythm & Hues where he worked on Oscar award winning movies like Life Of Pi . During this time, he started self learning python for fun and got hooked on to it. Went on to developing tools, automate stuff and shifted to technology. Currently he works as a developer at The Cirqus where he takes care of the studio technology and has worked on projects like Baahubali and upcoming VR games & applications. He is a self-learner and open-sorcerer. Apart from Python he is interested in Nodejs and Rust. He is also a RHCA and cloud enthusiast", - "Speaker Links": "Art : http://artstation.com/sreenivas Code : http://github.com/cg-cnu/ Movies : https://www.imdb.com/name/nm5590765/ Events : https://www.meetup.com/BonfireVR/events", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "sreenivas alapati (~cg-cnu)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/amazing-world-of-animation-powered-by-python~dLDrd/", - "title": "Amazing world of animation - powered by python" - }, - { - "Content URLs": "https://docs.openstack.org/infra/jenkins-job-builder", - "Description": "Jenkins job builder is an openstack project used for automation and reusing of templates in yaml and json to make jobs and subscribe them to Jenkins. People who like to save time on tedious details can use this open source software and live there life a little better", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Jenkins( a little bit )\nPython\nPip\nRelated libraries like PyYAML, Jinja etc", - "Section": "Developer tools and Automation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Himanshu Chhabra (~himanshu87)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/jenkins-job-builder-automating-jobs~aMgGd/", - "title": "Jenkins job builder - automating jobs" - }, - { - "Description": "Abstract: Everyone will agree to the fact that - Serverless is the \"In Thing\" now a days . \nBe it AWS , GCP or Azure everyone is talking about it.\nAWS provides a series of services which can be used to create a full fledged application. Out of all \"Lambda functions\" is the backbone of Serverless Computing on AWS Cloud Computing. It is the \u201cFunctions As a Service\u201d (FaaS) offering and currently it is positioned against Google Cloud Functions and Microsoft Azure Functions. The Big Question: \"Is everything Perfect in AWS Lambda?\" .... Well it depends on how you use it and this is what I will cover in my Talk. Note: This Talk will have some code references using PYTHON Outline: What will you learn from this session/talk: What are Lambda Functions . What are the different features of Lambda Functions. The famous Lambda Timeout . The Deployment and Resource Limits . The Cold Start issue and its workarounds. The Cost Factor Why do you need to know this: Helps develop decision making in the project design architecture The Case Study: Case Study in which you should/should not use Lambda Functions. Real Life project experience: The hidden learning with an on job project on the limitations to Lambda Function. Q&A ", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Python: Basics of Serverless Computing Basic of Python Programming Basics of Python Libraries Usages (Imports)", - "Section": "Others", - "Speaker Info": " Ritu Chawla Mehra is a working professional with over 10 years of development experience on C++ and Python . She has application development experience in multiple domains - Mobile , ServerSide and Web Application. Currently working as a Technical Lead in Xoriant Solutions Pvt. Ltd. . She is passionate about exploring new technologies and spreading awareness about the same. Her current focus is on AWS and Python :) She was also a speaker at SciPy 2017 held at IIT Powai Mumbai.", - "Speaker Links": "Linkedin Profile : www.linkedin.com/in/ritu-chawla-mehra-21299615 Speaker at SciPy 2017 : https://drive.google.com/file/d/1lzcRbI7ut3wYiFUaUqm2DOa7ra-0pIqg/vie", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Ritu Mehra (~ritu86)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/aws-lambda-with-python-dos-and-donts~dNjvd/", - "title": "AWS Lambda with Python : Do's and Dont's" - }, - { - "Description": "With examples build the concept of creating a language model using text data", - "Last Updated": "19 Jun, 2018", - "Section": "Data science", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "divya chowdhary (~divya69)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~aOkra/", - "title": "Language Model (Text Analysis) using Python from scratch" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Note: This talk is co-presented by Koushik (me) and Shubham Rao Talk Summary: Bitcoin has become so mainstream these days. It unveiled the importance of decentralization. But how does Bitcoin work? It\u2019s because of its core technology called Blockchain. After the Internet, Blockchain technology is regarded as the next big revolution. This talk gives a hands-on demonstration of how Blockchain technology works by building a toy version from scratch. Outcomes: After this talk the audience should be able to understand the basic working principles of bitcoin. They will be able to leverage their knowledge as a starting point of open-source contributions to projects like Ethereum. This demonstration will consider three important features of Blockchain Technology. All these features are essential to blockchain technology and we will be building a minimal version in Python. Agenda: 0 - 5 mins:\n Blockchains are secure because they use SHA256 or SHA512 algorithm for cryptography. I will describe the logic behind these hashing algorithms and give some computational facts about them. 5 - 10 mins: \n I will use the Python library called \u2018hashlib\u2019 to implement the SHA256 algorithm in Python. This makes us to convert data into SHA256 hashes. 10 - 15 mins:\n The SHA256 algorithm is used to convert all the transactions and their details into a single hash. Once the everything is converted into a hash, this hash must be stored for future usage. After a new transaction is approved, this new transaction and its details are again converted into a new hash along with the previous hash. I will demonstrate the process of storing the hash and using it again for a new transaction. 15 - 20 mins:\n Here I will explain a basic working principle of blockchains and how linking the previous transactions with the new one helps in the their security. The hashes stored are called blocks and the process of liking the previous hash the new hash makes a chain like connection thus forming a Hyperledger. 20 - 25 mins:\n Later in the process of mining will be explained using the variable quantity called Nonce. This explains why bitcoin miners need high computation power to do Proof-of-Work. \nI will also cover a variety of essential terms and concepts through the course of the talk which haven\u2019t been detailed in the agenda. Also, I will use python module called 'TkInter' to build a basic GUI for our blockchain. Last 5 mins:\n Questions and further reading + code sharin", - "Last Updated": "19 Jun, 2018", - "Prerequisites": "Love for Python and acquaintance with its libraries", - "Section": "Core python and Standard library", - "Speaker Info": "Hi, we are Koushik and Shubham , two Computer Science sophomores with research interests in Decentralisation and Blockchains, also occasionally working in Artificial Intelligence and Machine Learning. As members of Next Tech Lab, QS Reimagine Award-winning, student-run lab from our University, we work in Satoshi Lab, which focuses on Blockchains. We regularly participate and give talks in paper-reading groups and meetups like PyData", - "Speaker Links": "Visit my profile on LinkedI", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "KOUSHIK BHARGAV M M Srinivas (~koushik_bhargav_m)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-blockchains-from-scratch~dPl4d/", - "title": "Understanding blockchains from scratch" - }, - { - "Content URLs": "Github repository links will be updated soon", - "Description": "In this talk, I am going to talk about advanced concepts of Python related to Caching. A cache can be easily understood as a saved answer to a question. Caching can speed up an application if a computationally complex question is asked frequently. Instead of the computing the answer over and over, we can use the previously cached answer. Caching is an important component while scaling applications which are to be used by many users. It solves various problems related to cost and latency. Usually it takes more time to retrieve data from DB rather than cache. Using a cache to avoid recomputing data or accessing a slow database provides us with a great performance boost. I will describe in depth the different methods of Caching, their pros and cons. This talk will help developers focus on their code before scaling their applications. It will provide immense performance improvements with this simple concept. Outcomes: The novice audience will be able to understand basic Caching Mechanisms. They will be able to utiilize their knowledge which will serve pivotal while scaling applications Contents to be covered in talk: Local Caching: What is it, how to do it, example, built-in Python libraries: (using cachetools ), advantages, dis-advantages Memoization: What is it, pseudo-code algorithm, implementation using example, built-in Python libraries: (using lru_cache ), advantages, dis-advantages Distributed Caching: What is it, techniques: (using memcached , using pymemcache ) Agenda: Initial 10 minutes: Introduction to Caching and its various techniques. 10 - 20 minutes: Examples and code walk through for various techniques. 20 - 25 minutes: Comparative analysis of how caching is better than non-scaled applications. 25 - 30 minutes: Q&A session", - "Last Updated": "19 Jun, 2018", - "Prerequisites": " Basics of Python", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. Software development is my long suit. AI, ML and Data Science are my \n goto subjects. Competitive programming is something I love to do\n in my spare time. I like tinkering with new technologies, creating new projects and\n implementing things by myself. I have been contributing on github since a while. I am an avid learner and I can quickly adopt to new frameworks. Also,\n I am a mediocre public speaker with modest interest in Fintech and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "19 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-caching-in-python~aQm9a/", - "title": "Understanding Caching in Python" - }, - { - "Content URLs": "Docker Docker Swarm https://docs.docker.com/engine/api/v1.37/ https://www.elastic.co/products/elasticsearch https://www.elastic.co/products/kibana https://www.elastic.co/products/beats https://jmeter.apache.org", - "Description": "Summary: Knowing how Enterprise Server perform under load (% CPU, % Memory, Network, % Disk time) is extremely valuable and critical. This may limit the server performance and lead to enhancements or fixing before you go for production. Now any Load testing tools available comes with below problems Preparing the environment / infrastructure (installing various software dependencies) on multiple host systems to perform load test at times very tedious task. It requires maintenance and manual interventions to scale up and scale down load test. You have to write your own test codes, need some development effort. Most of the stress tools comes with their own format of reporting, very difficult to customize if it\u2019s really needed. Also it\u2019s difficult to view, analyze and compare test results real time across systems. Here in today\u2019s talk we are going to demonstrate how JAAS (JMeter As A Service) can be a one stop solution for all these problems. And how python is playing a crucial role in Delivering JAAS Solution. Tech Stack: Tech Stack behind JAAS Python: Python is at the core of JAAS. It is responsible for communicating across all individual components using Rest API. Python is also responsible for slicing and dicing the data for processing. Docker: For auto deploying of JMeter Apps, we use Docker containers (pre-packaged with all dependencies). This reduces manual interventions for maintaining the Load test environment / infrastructure. ELKB Stack: ELKB is the backend for JAAS. We store all logs, beats, JMeter results in Elastic Search. Logstash for data processing pipeline and Kibana for visualization. JMeter : JMeter is the load test tool for generating load. It\u2019s an open source software, Ease of Use, Platform independent and Robust Reporting. JAAS comes with a single window User interface where user will provide the Load test details like: System details Load Generation type Number of concurrent users Number of threads Using RESTFul API implemented in Python this info (including dynamic Test plan .jmx file for JMeter) will be stored in ES Backend and a new Docker service will be created. We use Docker container (prepackaged with all dependencies as a single app) for generating load on System. Usually a Docker container ships JMeter software and Beats (Data shippers for Elasticsearch ). Every time for a new load test request, we deploy a new instance of our app on the Docker Swarm cluster (a new Docker container).We maintain Docker swarm cluster (group of machines that are running Docker) for scalability and load balancing while performing load test. Each of this machines in cluster (both manager and worker) will communicate with each other and execute Docker command using Python Rest call only. Swarm managers can use several strategies to run Docker containers, such as \u201cemptiest node\u201d -- which fills the least utilized machines with containers. Or \u201cglobal\u201d, which ensures that each machine gets exactly one instance of the specified container. Swarm managers authorize workers to execute\\run the Docker container. Each Docker service will have specific input from user (stored in ES backend) for generating particular type of load on specific host system. Similarly user can scale up or scale down the load (number of users or threads) using the same UI form on the fly. This is the biggest advantage of JAAS over any other Load test tool available. In normal scenario there is no option but stop and start the tool, if you want to scale up or down. \nEach Docker container with its JMeter instance will keep generating the Load on specific host system and Beats will be responsible for pushing back the data/results into Elasticsearch. This entire implementation of data reading and writing to Elasticsearch is happening through Python. Once the load test specific data pushed to Elasticsearch , kibana will prepare the Visualization for you. This is real time, aggregated (in case of concurrent users are generating the Load) and available in a single dashboard which makes it very easy to compare and analyze", - "Last Updated": "20 Jun, 2018", - "Prerequisites": "Familiarity to Python, Docker, JMeter and Elastic Stack.\nPython and Modules(XML, JSON and Request) experience", - "Section": "Developer tools and Automation", - "Speaker Info": "Vishnu Murty K A Senior Principal Engineer at DellEMC Infrastructure Solutions Group, is an MS (Software systems) with a total experience of 13 years in Leading Product Qualification and Automation Development efforts. The domains Vishnu has worked on include Storage and System Management Software. Responsible of Delivering Zeno - Continues Test Automation framework, JAAS, ICEMAN and Automation Tools. Presented automation papers in Pycon (Python developer forum)\u00a0and STeP-IN Forum. Dibyendu Dutta A professional with over 7 years of experience in Core Java, PHP, Node.js, Python.\nHe is currently working as a Senior Engineer in Dell R&D Bangalore. He has designed, developed web applications for various MNCs across multiple domains.\nHe loves to be keep updated with all latest tech trends , cutting edge technologies", - "Speaker Links": "Vishnu Murty K https://www.linkedin.com/in/vishnu-murty/ Dibyendu Dutta https://www.linkedin.com/in/dibyendu-dutta-3b65581b", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vishnu Murty (~vishnu79)", - "created_on": "20 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/distributed-load-testing-using-python-jmeter-and-docker~dRnEd/", - "title": "Distributed Load Testing using Python, Jmeter and Docker" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Talk Summary :- Recently, there is a boom in concept of face recognition system with the introduction of Face ID by Apple in their iPhone X mobile phones. This was also incorporated by OnePlus for their mobile phones too. The most notable use of this technology is at Baidu, an internet company, are using face recognition instead of ID cards to allow their employees to enter their offices. Another place where this technology is prominently seen is in auto photo and video tagging feature of Facebook. In this talk we will build a Facial Recognition program using python library \u201cface_recognition\u201d and then we will dive deep in the behind the scenes action of this library and will try to build a One Shot Learning face recognition model using PyTorch. We will be implementing a Siamese neural network on AT&T Laboratories Cambridge dataset. We will also cover the basics of this neural network, triple loss function and and will discuss the reason for choosing this architecture. I will explain how the network models a relation between two images and relates them. Outcome of this Talk :- Attendees will be able to possess the power to implement state of the art Facial Recognition program in a few minutes. They will also get to know how facial recognition works when we have very small dataset. They will be able to make a state of the art One Shot Learning face recognition based on Siamese Network (the working force of face_recognition and implementation of Google\u2019s FaceNet). Agenda :- Introduction to Face Recognition [2 mins] Introduction of python library \u201cface_recognition\u201d [1 min] Building a face recognition program using \u201cface_recognition\u201d library\n (possible live demo of the output) [6 min] How \u201cface_recognition\u201d encodes faces [2 min] Introduction of Triplet Loss and Siamese Network and reason to choose one shot learning (which is used to\n encode faces) [5 min] Implementation of Siamese Network using PyTorch on AT&T Laboratories\n Cambridge dataset and its results [10 min] Q&A Session [3 min]", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basic Knowledge of Machine Learning and Neural Networks Love for Pytho", - "Section": "Data science", - "Speaker Info": "Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", - "Speaker Links": "Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Saurabh Ghanekar (~saurabh29)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-state-of-the-art-facial-recognition~eVrXe/", - "title": "Understanding State of the Art Facial Recognition" - }, - { - "Description": "for students,\nunderstanding data analysis with pandas, using ipython shell or terminal and jupyter notebooks", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "understanding of python scripts", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year B.tech(information science) student from Bangalore, Karnataka", - "Speaker Links": "https://github.com/pandyamaru", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marut Pandya (~pandyamarut)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/data-analysis-with-pandas~bWvxa/", - "title": "Data analysis with Pandas" - }, - { - "Content URLs": "Speaker will focus on when and how to use design patterns, rather than what are the design patterns available. Github repository for the talk", - "Description": "Having less time to design software and solving the design problems correctly, to create robust , modular and highly maintainable code is current challenge.\nMight be, you are aware of some of the design patterns but it will never solve your problems until you have deep understanding on the problem and right place to use design pattern. If you think, you need to design a very unique architecture, then may be you are missing powerful available design pattern that can provide you generic solution template. Let's learn ( and become expert), to speed up development process; guessing issues that can come up later development stages and selecting the right design pattern in the right stage of the software development in Python", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Coders and programmers who want to learn about software design and architecture", - "Section": "Others", - "Speaker Info": "A guy who loves challenging stuffs and learning new technologies along with the 'Time'. Shekhar has learnt C, C++, Java in his college time and worked as student developer in Google Summer of Code (GSoC) 2016 (under SymPy organisation - Python language) and 2017 (under SciRuby organisation - Ruby language), also contributed to open source projects like bundler gem. Shekhar is mentoring 3 Projects in GSoC'18 . Currently he is working in Benguluru India as Software developer (Full Stack Developer). Shekhar loves playing chess, cricket , watching and reading about ancient India, spirituality and travelling. Shekhar has given workshop in PyCon India 2017 Delhi and lightening talk in RubyConf India 2018 Bengalore ", - "Speaker Links": " Shekhar's personal webpage Blog Github Twitter LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shekhar Prasad Rajak (~Shekharrajak)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/i-would-have-known-this-software-design-techniques-before~eXwgd/", - "title": "I would have known, this software design techniques before.." - }, - { - "Description": "Data proliferation is putting pressures on business leaders to become data-driven. Although, leaders have to rely on data analysts to run those queries and get insights out from data warehouses. Its a common principle-agent problem wherein data analysts only ask questions from data which they are directed to ask, but its never a one-way street. One has to flirt with data for a long time to get to know it and leaders get stuck in the loop of data analyst direction as leaders are not equipped with or don't have time to write SQL queries. This calls for a natural language query wherein a business leader can ask a question in simple plain English and data is spitting out either in a table or graph. This session is guided towards how Innovaccer has solved this problem and provides an architecture, knowledge base building, and natural language processing guidance to build one on your own. The session will also emphasize on the fact that accuracy of such a software will be very poor if it is industry agnostic as SalesForce and ThoughtSpot have tried in the past. Thus, one has to tame it to their own business context or vertical", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics knowledge on natural language processing, not even how to code it, but what are its basic components. https://www.nltk.org", - "Section": "Data science", - "Speaker Info": "Kanav Hasija is Co-Founder and Chief Product Officer at Innovaccer. He has developed a healthcare data platform with his team which helps connect to various healthcare IT systems to get a longitudinal view of the patient record and turn it into analytical insights on risk, cost, and utilization behaviour of patient to act on them and treat them before they get sick to reduce the cost of healthcare. The platform today has more than 10 million lives on the platform and an estimated $1 Billion has been saved till date in US healthcare costs while keeping people healthy with a quality of care bump of 15%. He is a coder and mathematics enthusiast since the age of 10, completed his bachelor in engineering from IIT Kharagpur and pursued higher studies in Intellectual Property Law from UNH Law in the US. He is recipient of various awards like Samsung-Stanford Patent Prize, Honorable Mention for Excellence in Technology, Best Graduate Student Award, and is also an author in a few publications like IEEE. Harshil Rastogi is a software development engineer at Innovaccer. He has worked on various enterprise-grade software components in the fields of data management, data transformation, and natural language processing", - "Speaker Links": "https://www.linkedin.com/in/kanavhasija/ https://www.linkedin.com/in/harshil-rastogi-3a754b65", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kanav Hasija (~kanav)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bringing-analytics-in-hands-of-leaders-natural-language-query-in-python~bYx2a/", - "title": "Bringing analytics in hands of leaders: Natural Language Query in Python" - }, - { - "Content URLs": "Slides Celery Documentatio", - "Description": "Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. Although it is most popular in the web development ecosystem, it has a wide area of usage from system management to IoT devices. With Celery, transforming a function into a task is quite easy and can add great performance & usability to the applications that we build. This talk aims to give attendants a general overview of Celery and its uses. We will walk through the core Celery architecture by introducing key components with the help of various real-world examples. This will also lead to an understanding of the task queue systems in general. Attendants will also gain knowledge about Celerybeat; a tool that focuses on scheduling tasks", - "Last Updated": "21 Jun, 2018", - "Prerequisites": " Basic knowledge of Python. Ready to learn", - "Section": "Others", - "Speaker Info": "Software Engineer at Essentia SoftSer", - "Speaker Links": "Linkedin Githu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "abhyudaypratap@outlook.com", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-celery~eZy5d/", - "title": "Understanding Celery" - }, - { - "Content URLs": "https://github.com/someshchaturvedi/customizable-django-profiler Will be updating slides soon", - "Description": "Django, as we all know, is an excellent framework for building high stable, scalable, extensible web apps. Django framework operates around middlewares. Do we really understand how a middleware works? What happens when the request comes in and response goes out? Which middleware is used for what purposes? Why is the order of middleware stack important? How can we implement a custom middleware? Benefits and complications of implementing custom middlewares My talk will cover all the above questions along with a live demo of a profiling middleware ( customizable-django-profiler ) which is used to track down the function calls associated with an API call taking more time for execution. Contents of the talk: Introduction : Introduction to middleware. Middleware architecture : I will talk about the middleware architectural design. It\u2019s basics and various use cases Implementation of middleware in Django : Explain how the request-response cycle works along with targeting above mentioned questions on the go. Live demo : I will demo the development of a simple custom middleware which can be used for profiling requests. Conclusion : Possible use cases for Django middlewares. Q & A session : Questions and answers session. In the end, the audience will have an understanding of Django middleware stack, middleware architecture, request-response cycle in Django and will be able to develop their own middleware for Django from scratch", - "Last Updated": "21 Jun, 2018", - "Prerequisites": "Basics of Python and Djang", - "Section": "Web development", - "Speaker Info": "I am recently graduated from IIT Roorkee. I have been working on web applications (especially Django for more than 3 years now). Selected for Google Summer of Code this year and working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API . My areas of interest are Web Applications, Artificial Intelligence and Computational Biology", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-django-middleware-stack-with-a-live-demo~e1qme/", - "title": "Understanding Django middleware stack with a live demo" - }, - { - "Content URLs": "Git Hub Repository : click here Demo: click her", - "Description": "The workshop will be escalating from a very beginner level and so I only require you to know the basics of python and if possible a glance of the OpenCV library. The workshop will be proceeding accordingly : Basics of Image processing. Image classification using Deep Learning ( CNN ). Deploying your own Emotion recognizer. ", - "Last Updated": "21 Jun, 2018", - "Prerequisites": " Basics of Python Please download and install the following libraries in beforehand : Pytorch OpenCV Fastai numpy matplotlib dlib imutilis We will be using all of the mentioned libraries to make the goings of the workshop easy to understand and implement. Additional Files : Please download from her", - "Section": "Data science", - "Speaker Info": "I am shaaran and my main aim is to take technology to everyone and spread my knowledge as far as I can, in a journey to fulfill my dreams I have went to many institutions and have conducted workshops and talks in Robotics and AI, I am currently a second-year student at VIT University and also a part of many organizations like Google Developers Group, RoboVITics and more , I have interned at Toshiba recently and have made a new AHU control system using IOT and AI", - "Speaker Links": "Github: click here Linkedin: click her", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "shaaran Lakshminarayanan (~devshaaran)", - "created_on": "21 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-your-own-emotion-recognizer-from-scratch~b2rzb/", - "title": "Building your own Emotion recognizer from Scratch !" - }, - { - "Content URLs": "A similar version of this talk was recently delivered at Pycon APAC2018 (Singapore). Video An attendee's review", - "Description": "Offensive / abusive content is a major issue for social-media and digital interaction platforms. In some jurisdictions (Eg: Europe), platform providers are required by law to remove such content within 24 hours of posting or risk hefty fines (upto \u20ac50M in Germany). In order to meet the governance mandate, we need to have systems in place that can automatically detect abusive content at scale. This talk is based on my practical experience of building an automated solution to solve this problem. This talk begins with discussing some of the approaches currently being employed for offensive content detection at scale: word filtering, rule-based systems and actual human annotation. The former two are restricted by the following: Offensive content is context specific. A given word (f*ck) can be used in both positive (that\u2019s f*cking awesome) and negative (that\u2019s f*cking terrible) contexts. Robustness to spelling variations (The word \u2018shit\u2019 can be spelt as \u2018sh*t\u2019, \u2018sh!t\u2019, etc) Failure to detect content that is offensive in idea but uses non-offensive words. (Eg: your mom is a fat cow, X people are inferior, etc) Manual human annotation is notoriously hard and expensive to scale. The talk presents a Deep neural network based approach to overcome the previously mentioned limitations. It introduces and discusses the building blocks of model architecture (deep convolutional networks, word embeddings, etc). The second half of the talk focuses on implementing the model to solve the problem at scale as a RESTful micro-service using python, Django, Tensorflow and Docker. This architecture can also be used to implement other text classification systems (eg: sentiment detection, user intent detection systems, topic-of-discussion classifiers, etc.), making the talk relevant for a wider user base. Attendees will: Gain insights into building deep learning based text-classification systems that can scale Learn the nitty gritties of the offensive content detection and text classification Learn about the basic concepts of Deep Learning and NLP (convolutional neural nets, multi-layer perceptron, word embeddings, etc.) Understand the scientific and software challenges involved in text classification and learn to overcome them Be able to apply the learnings from here to other text classification problems as well", - "Last Updated": "22 Jun, 2018", - "Prerequisites": " Elementary knowledge of Python Basic understanding of machine learning (nice to have, not mandatory) An open mind ;)", - "Section": "Data science", - "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. He is currently employed as a Machine Learning Engineer. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", - "Speaker Links": "https://www.linkedin.com/in/alizishaan-khatri-32a2063", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Alizishaan Khatri (~alizishaan)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/detecting-offensive-messages-using-deep-learning-a-micro-service-based-approach~e30Ra/", - "title": "Detecting offensive messages using Deep Learning: A micro-service based approach" - }, - { - "Content URLs": " Apache Beam : https://beam.apache.org/ Apache Beam Python SDK : https://beam.apache.org/documentation/sdks/pydoc/2.4.0", - "Description": "Data together with 3Vs characteristic, volume, variety and velocity is labelled as Big Data. Big Data and parallel processing have been hot topics since Google\u2019s paper on MapReduce and till today the era of different runners like Apache Spark, Google Cloud Dataflow etc. Apache Beam is a unified big data processing paradigm which enables the user to run batch and streaming data processing jobs on multiple execution engines like Apache Spark, Apache Flink, Google Cloud Dataflow etc. *Objective of the talk* : Overview of Apache Beam Python SDK Core SDK constructs like Pipeline , PTransform , PCollection etc. Creating custom DoFns and composite Transforms Creating a Pipeline with customizable options Running a pipeline on different runners like DirectRunner , DataflowRunner etc Unit testing a Pipeline with asserts Demo: StreamingWordCount example using Google Cloud Dataflow Q&A", - "Last Updated": "22 Jun, 2018", - "Prerequisites": " A little knowledge about Python 2.7 Enthusiasm for Parallel Data Processing Motivation to play with lots of Data", - "Section": "Others", - "Speaker Info": "I am Mukul Arora, working as a Software Engineer in Schlumberger India Technology Centre. I graduated from Delhi Technology University in May 2017. I am a Data Science and Big Data practitioner and have been highly involved in solving Computer Vision and Medical Imaging problems using Deep Learning Techniques. Currently, I am exploring efficient ways to solve Big Data problems on Cloud.\nI am an avid cricket fan and love to write poems", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/mukularoradce/ Github : https://github.com/codemukul95 YourQuote : https://www.yourquote.in/mukul-arora-ffds/quotes", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "mukul arora (~mukul11)", - "created_on": "22 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unified-and-portable-parallel-data-processing-using-apache-beam~b4Dxb/", - "title": "Unified and Portable Parallel Data Processing using Apache Beam" - }, - { - "Content URLs": "The code is in this repo :\nhttps://github.com/KaustabhGanguly/Smile-Detector :", - "Description": "In this era of deep learning and machine learning , the beginners may get lost sometimes , as there is a steep learning curve involved with the process .\nWhen I was starting out on machine learning , I always wanted to get my hands dirty in the advanced stuffs but It was hard for me and there was no guidance .\nSo , in this talk and coding session I will guide you through how you can build your own facial recognition system and implement a smile detection very quickly and easily with the power of openCV and python . It will take 10 mins and any beginner with basic knowledge of python can grasp the concepts easily .\nI will not use convNet or anything ,but a model called HaarCascades . It's an old mathematical model which was/is mainly used where deep learning is not an option . I will guide you through the basics and tell you some quick things and facts and we will enjoy a lot . See you on pyCon 2018 ! kindly upvote if you want some quality 10 mins learning something new ", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic Python knowledg", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India .\nI'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 .\nI'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github :\ngithub.com/kaustabhganguly\nConnect with me on linkedin :\nlinkedin.com/in/kaustab", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quick-and-easy-implementation-of-smile-detector-on-your-webcam-using-python-and-opencv-from-scratch-without-any-neural-network-and-for-beginners~e5E8e/", - "title": "Quick and easy implementation of Smile Detector on your Webcam using python and openCV from Scratch without any Neural Network and for beginners ." - }, - { - "Content URLs": "A sample code can be found here :\nhttps://github.com/KaustabhGanguly/Recurrent-Neural-Networks-to-predict-Google-Stock-Pric", - "Description": "I will show you how to predict google stock price with the help of Deep Learning and Data Science .\nThe predictions are not realistic as stock prices are very stochastic in nature and it's not possible till now to accurately predict it .\nAs I'll only have 30 mins to talk , I can't train the data and show you as it'll take several hours for the model to train on google collab . So , I will show you : Basics of Recurrent Neural Networks and LSTM Basics of pytorch Coding line by line with describing every words Then starting to train the model and prematurely closing it and move forward to show you the results that I'll bring with me after training .", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "You should have basic pyTorch understanding but I'll guide you anyways through the basics .\nBasic understanding of LSTM or RNN is preferred but not required ", - "Section": "Data science", - "Speaker Info": "I'm a 3rd year Engineering student at Kalyani Government Engineering College , West Bengal , India . I'm a data science enthusiast and I interned at a machine learning startup called param.ai from June till August , 2018 . I'm obsessed with AI and my hobby is to study new cutting edge deep learning algorithms and research papers ", - "Speaker Links": "Follow me on github : github.com/kaustabhganguly Connect with me on linkedin : linkedin.com/in/kaustab", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kaustabh Ganguly (~KaustabhGanguly)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/google-stock-price-time-series-prediction-with-rnnlstm-using-pytorch-from-scratch~b67Rd/", - "title": "Google Stock Price Time Series Prediction with RNN(LSTM) using pytorch from Scratch" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Dash is a Python framework for building analytical web applications, built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs to your analytical Python code. The workshop will include building interactive dashboard with Dash framework. How to visualise the data purely in python will be the key take away", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Python 3 Pip3", - "Section": "Web development", - "Speaker Info": "I am software engineer working at Juxt Smartmandate, who believes in creating products using open source technology", - "Speaker Links": "https://github.com/kapoorabhish https://www.linkedin.com/in/abhishek-kapoor-4b7b9295", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "kapoorabhish", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-interactive-dashboard-using-plotly-dash~e771e/", - "title": "Building interactive dashboard using Plotly Dash." - }, - { - "Description": "Automation is something we all desire, may it be the twitter feed of a celebrity, or perhaps the latest price of bitcoin. For students, it can range from tracking assignment deadlines or message updates. For developers, it can be the tracking of an important issue or auto merging of pull requests. For management, deadlines for a work assignment or a due presentation. With Python, everything listed above is possible. The talk will feature how to start automating the small things that can prove highly productive. We will use simple libraries first, and this will be followed by using fully headless browsers like selenium and understanding the concepts of web crawling. Integration of API services like Google Calendar and Google keep, to sync all the data collected will be demonstrated. Finally, we will deep dive into an interesting open-source project I made, and how I have automated most of my college work.\nA simple breakdown of the talk is described as follows. REST API Introduction ( Totally 3 minutes ) Libraries we will use ( Totally 6 minutes ) The Requests library The BeautifulSoup library Web Scraping example for IMDb ( Totally 4 minutes ) Code and Logic walkthrough Running Example Automation Example ( Totally 10 minutes ) What we will be doing The Code Google API linking Cron/Scheduling The base logic Running Example Selenium ( Totally 5 minutes ) Introduction Example Conclusion and My work ( Totally 2 minutes )", - "Last Updated": "23 Jun, 2018", - "Prerequisites": "Basic understanding of REST APIs and Frameworks, and Beginner-Intermediate Level of Python Programmin", - "Section": "Developer tools and Automation", - "Speaker Info": "CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms.\nTechnical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "23 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-your-life-with-python~b873a/", - "title": "Automating your life with Python" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/1d061xK27vMdJ8Xjta8K3kuvA4-dbX8MrywzXQmZ1Ln4/edit?usp=sharin", - "Description": "Have you ever been amazed how efficiently and effectively tech giants are processing their data ? Do you want to build an analytics system that is capable of processing billions of records in a day ? For those of you who are wondering how to build a scalable, low latency system for running arbitrary SQL queries in Python, this talk is for you! This system is distinguished by being schema-independent, and processing queries with minimal latency I will describe how to architect this system using the powerful Lambda Architecture (an often used design pattern in big data) and Apache Kafka, how to process and format the raw schema-independent data, and introduce different online analytical processing (OLAP) systems and their respective tradeoffs. The end product will be an analytics engine capable of running arbitrary queries on billions of records. Finally, I will also discuss some exciting extensions of this pipeline, including applying machine learning algorithms and adding a monitoring system. The talks ends with benchmarks of queries made on billions of records followed by a Q&A session. This talk is intended for folks belonging to any of these fields: Involved in the process of revamping their data warehousing systems\n for arbitrary queries with minimal latency Those who want to build their own analytics layer from scratch Analytics enthusiasts", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " General Python knowledge Basic SQL queries Great Enthusiasm Little Familiarity with Databases", - "Section": "Data science", - "Speaker Info": "Shaik Asifullah is currently working as Senior Data Engineer at MoEngage, open source developer who previously worked at WalmartLabs and graduated from BITS Pilani, Goa. He got interested in learning more about Big Data technologies after he learnt about Columnar databases. He was also associated with faculty of University of Zurich & ETH Zurich in building a Sentiment Analyser and worked on predicting results of US 2016 Presidential elections with the model. His recent open source contribution is regarding building a distributed Python environment for building, simulating, and analysing models of biochemical networks, including gene regulatory networks and metabolic networks. He is also a great admirer of Freud Psychoanalysis & Andre Breton Surrealism", - "Speaker Links": "https://www.linkedin.com/in/shaikasifullah https://github.com/ShaikAsifullah/distributed-telluriu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shaik Asifullah (~shaik2)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/processing-billions-of-records-per-day-with-python~e97Db/", - "title": "Processing Billions of Records Per day with Python" - }, - { - "Content URLs": "Will come soo", - "Description": "Blockchain Technology is the talk of the town. Almost all articles published have some relation to Blockchain concepts.\nWhile Public Networks usually pertain to Cryptocurrency, Private networks pertain to business-level implementations. In order to develop with this technology as our base, it is important to understand the key features, as well as make implementations using the existing skillset, which happens to be the Python Programming Language. The talk will feature Complete in-depth explanation of Blockchain technology, and the working of Bitcoin as an example. Developing your personal Cryptocurrency with Python Introduction to Hyperledger Sawtooth, and understanding how and why to use Python with it. Best practices to consider in mind while developing for a blockchain. By the end of the talk, you will be able to Explain the concepts of Cryptocurrency and Blockchain technically. Understand Python's role in one of the most popular frameworks created by Intel, and implement your own ideas with the same.", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "General Pytho", - "Section": "Others", - "Speaker Info": "Hi, I'm Priyansh! Here's a quick bio. CS Undergrad, at Vellore Institute of Technology, Vellore (Batch of 2020). Passionate developer, with specialization in Python scripting, Backend Web Development, and Blockchain Frameworks like Hyperledger Fabric and Ethereum. Presently, hold the positions of Blockchain Intern at Skcript, Senior Backend Developer at IEEE-Computer Society VIT Vellore Chapter, and Backend Developer at CollegeCODE, a student-created organization that has apps on both Android and iOS platforms. Technical Writer, and have authored multiple articles on major sites like Medium and Dev.to. Speaker at Tech Meetups. Very recently spoke at a Gopher meetup. Developed an interest in Python since 2016. Have used Python for general scripting and automation of tasks, along with Desktop Software Development. Actively contribute on open source platforms like Github, and love to discuss anything Python", - "Speaker Links": "Github LinkedIn Some Interesting Open Source Python Projects Captcha Solver Movie Reviews Grabber Assignment Tracker and SMS Reminder Some interesting articles I authored Automating the Boring University Stuff with Python How I developed a captcha cracker for my University's website ABCs of Kafka in Hyperledger Fabric Visualising the JavaScript Event Loop with a Pizza Restaurant analogy", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Priyansh Jain (~Presto412)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-with-python~e0yLa/", - "title": "Blockchain with Python!" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Your machine learning models might be intelligent enough to make predictions but may lack the wisdom to prevent bias. They may be as vulnerable as a child getting influenced by inappropriate sources encouraging racism, sexism or any unintended prejudice. Models learn exactly what they are taught. The more biased your data is, the more biased is your model. For instance, a text model by Google says how \u201cEngineer is to a Man\u201d is the same as \u201cHousewife to a Woman\u201d. This shows how incidental data can lead to unintended bias. Machines are given the power to judge so there is a need for us to ensure we prevent biased/unfair judgments. In this talk, we are going to discuss how to arrive at \"Engineer is the same for both man and woman\" [debiasing gender] by following the steps below : Intro to Machine Learning bias and word vectors? [10 min] Analyse bias from word vectors and it's problems [10 min] Debiasing algorithm [10 - 15 min] Questions [5-10 min] One Famous example of bias:", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Knowledge of python Knowledge of building machine learning models / Interest in building on", - "Section": "Others", - "Speaker Info": "I am a software developer, speaker, opensource contributor and a wannabe developer evangelist. I love everything python and NLP(Natural Language Processing) research. I have been volunteering with various local startup and tech communities to promote entrepreneurship and technology. I work at mroads and help them develop better a.i", - "Speaker Links": "Links: Linkedin: https://www.linkedin.com/in/poornagurram/ Github: https://github.com/poornagurram StackOverflow: https://stackoverflow.com/users/5443381/poorna-prudhv", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "G POORNA PRUDHVI (~poornagurram)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-fair-machine-learning-systems~egVkd/", - "title": "Building fair machine learning systems" - }, - { - "Content URLs": "Errbot's Website: http://errbot.io Errbot's GitHub Repository: https://github.com/errbotio/errbot corobo's GitHub Repository: https://github.com/coala/corobo The slides will be shared to the audience as a GitHub repo after the talk", - "Description": "Abstract The aim of this talk is to introduce you to Errbot, which is a chatbot that can be used to automate software development and operation tasks to facilitate faster development of code. Errbot is a chat bot which connects to your favorite chat service(Gitter, Slack, Telegram, Zulip, IRC, etc) and brings your tools into the conversation. It provides you with a rich and user friendly API, through which you can write your own plugins so you can make it do whatever you want: retrieving some information online, trigger a tool via an API, troll a chat room member, etc. The talk will include: Introduction to DevOps and ChatOps What is Errbot Guide to setting up you own bot Writing your first plugin Fun with the bot Automating GitHub/GitLab tasks right from the chat room - Introduction to corobo", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " Basic knowledge of Python and APIs Will to learn", - "Section": "Developer tools and Automation", - "Speaker Info": "Nitanshu Vashistha is a 3rd Year Engineering Undergraduate in India studying Information Technology. He started learning how to code in his first year of engineering but little did he know that he was just playing with the syntax, which he realized in his second year and his journey as a developer began. His first working application was in Python and that got him interested to develop more using Python. Nitanshu is a Python developer and an open source enthusiast . He has mentored Google Code-In 2017 and is currently a Google Summer of Code 2018 student working on a project based on Errbot for coala . He likes writing about himself as third-person :", - "Speaker Links": "GitHub: https://www.github.com/nvzard LinkedIn: https://www.linkedin.com/in/nitanshu Blog: https://medium.com/@nitanshu.vzar", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Nitanshu (~nvzard)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-automate-development-tasks-an-introduction-to-errbot~ejVve/", - "title": "How to automate development tasks? - An Introduction to Errbot" - }, - { - "Content URLs": "Content will be updated soon", - "Description": "You all would have often faced the issue of not being able to recognize handwriting, either it is a Doctor's prescription or sometimes, even your friend's assignment. This problem might have caused some harm, maybe due to the delay in submitting the assignment or seeking chemists' that can recognize that particular handwriting.\nTherefore, in this talk, we will be focusing on how Python and Data Science can be used to recognize handwritten digits and character which will ease out the pain of recognizing haphazard writings. Topics to be covered: What is Handwritten Digit and Character Recognition? Why we need it and uses of it? How Python can help in achieving this? How NLP and Neural networks can be used to increase accuracy? Future Scope", - "Last Updated": "24 Jun, 2018", - "Prerequisites": " Basics of Python Basics of Data Science", - "Section": "Data science", - "Speaker Info": "I'm Prashant Pandey. I've deep interest in Data Science, especially in Python. I've been working in the domain of Data Science since one year now, and have completed several projects. Presently, I'm working on Handwritten Digit and Character Recognition", - "Speaker Links": "https://github.com/Prashantpandey2398", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Prashantpandey2398", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handwritten-digit-and-character-recognition-using-python~bkV6a/", - "title": "Handwritten Digit and Character Recognition using Python" - }, - { - "Description": "A framework which will give a drag and drop web development option using Django as the backend", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "Python and basics of Djang", - "Section": "Web development", - "Speaker Info": "Sanket Sarkar [ Microsoft Technology Associate {Introduction to Python Programming}]\nA final Year Student of B.Tech", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Sanket Sarkar (~sanket78)", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/drag-and-drop-framework-for-django~elVMb/", - "title": "Drag and Drop Framework for DJANGO" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Get to know Flask and how to create beautiful REST APIs in no time. Fall in love with Flask and learn the best practices for building APis in a hurry. Flask is a lightweight micro-framework for Python. Its simplicity and elasticity make it the best choice for building APIs in no time. In my talk, I will cover the basics concepts of Flask and Requests. I will show the tools that can automate the most common tasks in API development and will share the design patterns to avoid common pitfalls. Some of the specific tools and topics that I'll cover: Flask-Restplus, SQLAlchemy, request lifecycles, REST + CRUD API patterns, Flask architecture", - "Last Updated": "24 Jun, 2018", - "Prerequisites": "No previous experience in Flask is needed", - "Section": "Web development", - "Speaker Info": "Sara is a seasoned software engineer and the Co-Founder of Gradient.gt, a data science and machine learning consulting company based in Guatemala, where she works crafting web applications and solutions to companies in need. When she is not coding, she spends her free time baking sweet treats and watching Rick and Morty", - "Speaker Links": "www.sara-codes.com Linkedin.com/in/sarairisgarcia Gradient G", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "montjoile", - "created_on": "24 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-apis-in-no-time-using-flask~bmVGd/", - "title": "Designing APIs in no time using Flask" - }, - { - "Content URLs": "https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology I will update slides and code soo", - "Description": "Central dogma of life or of molecular biology is the core molecular process which keeps us alive! It's the machinery which converts DNA to mRNA to protein to active protein which eventually gets distributed in the body. DNA -> mRNA -> Protein Through this talk, I'll give a live demonstration of the processes by which this mechanism takes place and unravel its mysteries using Python! I'll explain how python is helping us simulating biological processes in the most elegant manner. How is DNA transcripted to mRNA? How is mRNA translated to protein? These are some of the questions I\u2019ll answer by simulating the actual processes using Python. By solving small challenges involved with this mechanism, I\u2019ll tell the audience, why Python is the best computer language for a bioinformatician and how great python libraries can make the life even easier especially BioPython. The challenges I am talking about are real bioinformatics problem, although basic, including translation, transcription and reverse complement. In the end, I\u2019ll brief some huge accomplishments of bioinformatics and computational biology and how we can contribute to this sector which has a promising future as well. Contents of the talk: Introduction : Introduction to gene and how we (computer scientists)\n recognize a gene Central Dogma of Life : a Live action of how a gene\n is converted to RNA and then to protein using Python. Why Python is best for biology? : Bioinformatics can be best studied using Python Impact of this sector : Accomplishments of Computational Biology and\n bioinformatics Conclusion : Possible ways in which we can contribute. Q & A session : Questions and answers session. Outcome: After the talk, the audience will have an understanding of how we function at a cellular level, how proteins are formed in our body and how can we simulate other biological processes using Python and will recognize the power of Python which can be harnessed in biology as well as other sciences. They will also have a basic introduction of BioPython", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Curiosity to learn :", - "Section": "Others", - "Speaker Info": "I have completed my B.Tech in Biotechnology this year from IIT Roorkee. I have interests in Web applications, Artificial Intelligence and Computational Biology. I have worked a couple of years in Computational Biology and Translational Bioinformatics Lab at my Institute and currently a Google Summer of Code student working with Global Alliance for Genomics and Health on Reference Sequence Retrieval API ", - "Speaker Links": "LinkedIn | Github | Twitter | Portfolio | Mediu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "hulksmash (~someshchaturvedi)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/simulating-central-dogma-of-life-using-python~enV7e/", - "title": "Simulating central dogma of life using Python" - }, - { - "Content URLs": "Content of my talk: Computer Vision with Pytho", - "Description": "We all(probably) love facial recognition feature isn't it?. We all edit our images before posting it to social media to give a flamboyant touch and its done in too simple steps. Open the editing software, select what you want to configure(filters, Sharpness, etc.) and you're done. Quite easy, right? But what if you know how the back-end of how these softwares run? what if you know the what kind of codes make your camera detect objects? Well with OpenCV and python its simpler than you can imagine! My talk will be about OpenCV with Python. OpenCV is an acronym for Open Source Computer Vision Library . Its a library used for image processing. The code can be written in C++, Java or Python but since we all love Python, we'll use that. We will be using ' cv2 ' library for all the image processing and detection. My talk will feature: How images are stored in computer and how each pixels store image. Different types of Colour Bands and the role of Colour Bands in forming an image. Editing images with cv2 library in python. Blurring, Sharpening, Greyscaling, and other uses of image kernels. Object and Face Detection and live object Tracking using python and OpenCV.", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basic knowledge of Python and basic mathematics(Class 10th)", - "Section": "Others", - "Speaker Info": "I am an undergraduate final year student, CSE branch from REVA University. I am a passionate programmer. I am an IEEE Volunteer. I was the Chair of IEEE Computer Society Chapter REVA University. Right now i am Student Branch Coordinator at IEEE Region 10(Asia/Pacific).\nCurrently I am interning at Valtech India as a Java Developer.\nI have taught python to more than 150 students in my college by taking sessions. I have taught OpenCV to more than 80 students.\nI started loving python since 2016 when I read the book 'learn python the hard way by Zed Shaw'. My almost all the undergraduate projects are based on python", - "Speaker Links": "Read my Blog! My Github Connect with me on LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rohan Vijay (~rohan96)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/computer-vision-with-python~bo9Xe/", - "title": "Computer Vision with Python." - }, - { - "Content URLs": "https://github.com/vibrantabhi19/PyConIndia2018 (A Github Link to the slides and the Jupyter Notebooks) https://docs.google.com/presentation/d/1UmT3PbazC6sO_owIeiLNj5G1EdTwrdpS84JWenO-3eE/edit?usp=sharing (Introduction Slide for CNN and PyTorch) Some more slides and notebooks as and when we come up with more ideas to make the workshop interacting and interesting", - "Description": "Just like in our everyday lives, AI and robotics are increasingly a part of our healthcare ecosystem. Currently healthcare is broken; there\u2019s shortage of doctors; poor quality of care. There is a dire need to provide assistance to the whole medical industry to improve healthcare. PyTorch, which is a very popular modular deep learning framework for fast, flexible experimentation is an invaluable resource for such problems. It supports seamless conversion of Numpy arrays into GPU tensors and vice versa. The dynamic computational graph allows to change the network behavior on the fly unlike static graphs and due to Its highly modular nature helps in fast debugging. Unlike other production grade tools, Pytorch helps with lots of Research and Experimentation with novel architectures and is very useful to test ideas a bit more quickly and prototyping. With Medical Imaging being the field most impacted by AI, our goal in this workshop is to give a good head start covering the heuristics of Medical Imaging, the concepts involved in it and how to code your way out. This workshop would be divided into two halfs. First Half: Pytorch Introduction\nDuration: 1 hour 20 minutes\nThe first half would be a gentle introduction to PyTorch framework. We will introduce the audience with the basics of PyTorch. This workshop will cover topics like: What is PyTorch? (Use cases and war stories) Tensor 101 Ndarray/Tensor library Numpy Bridge, Fast CPU to GPU conversion of tensors The automatic differentiation engine or autograd Difference between Static and Dynamic computational graphs Advantages of dynamic computational graph with examples The optimization package Scope of debugging Ecosystem Linear Code flow in Pytorch (One of the core philosophy of PyTorch) Saving and loading models* Deep Learning workflows* Tutorial on Transfer Learning.* Workflows which involve writing custom data-loaders will also be introduced in brief.* A 10 minute coffee/kit-kat break. :-) Second Half: Let\u2019s dive in. Duration: 1 hour 15 minutes. Introduction to Radiology: What is radiology? What do the images look like? How is AI used here? How will AI help improve radiology practice? Liver, Tumor and Vessel Segmentation - setting the context of why it is needed. Challenges faced in solving liver segmentation. How we solved the challenges - edge maps, data imbalance and overall architecture and data used. Hands on with live Liver Segmentation using PyTorch. Challenges faced in vessel segmentation and classification. How we solved the challenges - vesselness filters, overall architecture and data used. Hands on with live Vessel Segmentation using PyTorch. Putting it all together A 15 minutes Q & A session", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Zeal to learn new things would be enough but basic knowledge of Python would be good to go but the following are always encouraged: Basic Knowledge of algebra. Python Libraries such as Numpy. Basic knowledge of working with Neural Network (not a strict requirement as we will be covering most of it). We also encourage the participants to have a look into the following linked talks/videos/literature to get a head start into the topic. The related materials from web for ideas: https://github.com/soumith/talks/blob/master/2017-NIPS/Coding-papers-in-pytorch.pdf https://github.com/soumith/talks/blob/master/2017-GATech-Atlanta/PyTorch-frameworks_overview_deepdive.pdf https://www.youtube.com/watch?v=LEkyvEZoDZg https://www.youtube.com/watch?v=VMcRWYEKmhw https://www.youtube.com/watch?v=Rv9naeLXolY&index=3&list=PLrzfRWNHZPa0gKBEXTJ0gbDu8NsR07KEH https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/01-basics/pytorch_basics/main.p", - "Section": "Data science", - "Speaker Info": "Abhishek Kumar: Deep Learning Engineer, Predible Health, Bangalore. I am presently working as Deep Learning Scientist at Predible Health, here,I work on the the research and development of Predible's core Imaging platform wherein we have build state of the art segmentation algorithms/models in Computer Vision. I have previously taken workshop at IIT-Bombay Techfest, I have spoken at Shri Mata Vaishno Devi University at their SFD celebrations and at MuPy (Manipal Institute of Technology's annual Python Conference), Kongu University and a few other colleges/Universities. I have been a constant contributor in the open source world and have been attending PyCon and other conferences every year. An athlete, a Real Madrid F.C follower and a part time stand-up comedian (good enough to make you laugh). Aditya Bagari: Final year Undergrad, Indian Institute of Technology, Madras I am a final year Undergraduate student at IIT-Madras doing my Dual-Degree in Engineering Design with specialisation in Bio Medical Sciences. I have been working on Medical Imaging and PyTorch for almost a year and I have been a constant admirer of Open Source Technologies and frameworks. Feel free to drop any suggestions or modifications that you want in this workshop. See you at PyCon", - "Speaker Links": "Abhishek Kumar: Website (A very outdated one), LinkedIn , Medium , Github . Aditya Bagari: LinkedI", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Abhishek Kumar (~vibrantabhi19)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/exploring-pytorch-for-ai-assistance-in-medical-imaging~bqXpa/", - "title": "Exploring PyTorch for AI assistance in Medical Imaging" - }, - { - "Content URLs": "Session Content: Introduction to main units of Deep learning Feature engineering techniques for audio data DeepSpeech Architecture Live demo of DeepSpeech Project Common Voice initiative (why and its need) Community Support details Applications of speech recognition Key Takeaways: Unravel the mystery behind the AI which powers speech recognition for services such as Siri, Google Assistance etc Learn about various by which one can contribute to Project DeepSpeech & Common voice project Get introduced to major units of deep learning and state of art DL architectures powering speech to text applications Tags: AI, speech recognition, speech to text, machine learning, Python, tensorflow, deep learning, Voice search Projects links: DeepSpeech : https://github.com/mozilla/DeepSpeech https://arxiv.org/abs/1412.5567 Common voice: https://voice.mozilla.org/ https://voice.mozilla.org/en/data", - "Description": "Pitch: Our voices are no longer a mystery to speech recognition (SR) software, the technology powering these services has amazed the humanity with its ability to understand us. This talk aims to cover the intrinsic details of advanced state of art SR algorithms with live demos of Project DeepSpeech. A research says that \"50% of all searches will be voice searches by 2020\". World\u2019s technology giants have placed big bets with their investments in services providing voice search, personal digital assistant, IoT devices etc. Solving the problem of speech recognition is a herculean task, given the complexity involved with data like the human voice. The talk will cover a brief history of speech recognition algorithms, the challenges associated with building these systems and then explain how one can build advanced speech recognition system using the power of deep learning and for illustration, we will deep dive into Project DeepSpeech. Project DeepSpeech is an open source Speech-To-Text engine developed by Mozilla Research based on Baidu's Deep Speech research paper and implemented using Google's TensorFlow library. Speech recognition is not all about the technology, there's a lot more concerns, challenges around how these AI models are being part of our day to day life , it's biases etc. The bigger question revolves around centralization of these AI services, projects like Common Voice addresses these problems by enabling all to be part of this revolution, a part of the talk will focus on how people need to approach these type of research keeping in mind the community and humanitarian benefits as first priority", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic Python Feel enthusiastic about ML & AI services Interest to learn about speech recognition systems", - "Section": "Data science", - "Speaker Info": "Vigneshwer is an innovative machine learning researcher with an artistic perception of technology and business, having several years of experience in developing robust machine learning solutions for video and text analytical problem statements and have played key roles in analyzing problems, creating hypothesis matrix and delivering novel algorithms and data-driven solutions for many fortune 500 companies. An open Source aficionado, Official Mozilla TechSpeaker and the author of Rust cookbook", - "Speaker Links": "Github | Website | Facebook | Twitter | LinkedIn | Talk", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vigneshwer Dhinakaran (~dvigneshwer)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-speech-recognition-with-project-deepspeech~erNpe/", - "title": "Demystifying speech recognition with Project DeepSpeech" - }, - { - "Content URLs": "TB", - "Description": "The focus is more on teaching core concepts to programmers rather than using libraries. More than one neural network will be implemented. An Easy way to learn Machine Learning An interactive way to learn ML. With ML being a leading platform in the market, the workshop introduces to one of the most important fields of Machine Learning that is Deep Neural Networks. Only basic introduction to Mathematics required. Why Python? Python for Machine Learning Machine Learning What is Machine Learning? Why learn Machine Learning? Types of Machine Learning Regression and Classification Supervised and Unsupervised Neural Networks Deep Neural Networks Feed forward Neural Networks Convolutional Neural Networks CNN Recurrent Neural Networks Layers in Neural Networks Neuron Models Perceptron Sigmoid Neuron Binary Threshold Rectifier Stochastic Binary Cost Functions (A Loss or Objective function) Gradient Descent Gradient Boosting Backpropagation Stochastic Gradient Descent Implementing the classic MNIST dataset problem A Neural Network for handwritten digit recognition Classification using individual pixels Image Classification A simple implementation using deeper networks TensorFlow Expanding the Neural Network using Google's Library for Machine Learning Might change to Caffe - nVIDIA's library for Machine Learning Deep Learning A brief introduction to Deep Learning practices Auto Encoders Other areas of Deep Learning (A qualitative study) ", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "User Prerequisites Core Python - lists, dict, string including functions and classes NumPy, SciPy - not necessary but preferred Elementary Calculus - Differentiation and Integration (Understanding qualitatively is enough) Linear Algebra System Requirements 32/64-bit Windows/Linux architecture with at least 2GB RAM Python3 compiler with NumPy, SciPy and TensorFlow library PDF reader Other Requirements but not necessarily needed Anaconda3 (or support for ipynb files, Jupyter preferred) A graphic card", - "Section": "Core python and Standard library", - "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", - "Speaker Links": "GitHub Instagram Emai", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Aniket Chowdhury (~aniket43)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-advent-of-deep-neural-networks-neural-network-implementation-without-ml-libraries-and-extending-them-with-tensorflow~av75b/", - "title": "The Advent of Deep Neural Networks. Neural Network implementation without ML libraries and extending them with Tensorflow." - }, - { - "Content URLs": "will update soo", - "Description": "Get to Know Tkinter , pyqt5 and pyqtgraph and how to create a data visualization and control interface for your geeky arduino project in no time. Tkinter is a is the standard Python interface to the Tk GUI toolkit pyqt5 is Python bindings for the Qt cross platform UI and application toolkit pyqtgraph is Scientific Graphics and GUI Library for Python I will show you how to send the commands to Arduino using Python GUI and how parse and create a real-time graphs from Arduino dat", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "You should know how to write mighty Hello World program in Python and Arduin", - "Section": "Embedded python", - "Speaker Info": "I'm just a Tinkerer. Been playing with Python , Arduino and Raspberry Pi from few year", - "Speaker Links": "Blog - My Tinkering with Arduino GitHub linkden simple dem", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Kunchala Anil (~anilkunchalaece)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-python-gui-for-arduino-project~dw88e/", - "title": "Building Python GUI for Arduino Project" - }, - { - "Content URLs": "Will be updated soo", - "Description": "The ELK stack consists of Elasticsearch, Logstash, and Kibana. Although they've all been built to work exceptionally well together, each one is a separate project that is driven by the open-source vendor Elastic\u2014which itself began as an enterprise search platform vendor. It has now become a full-service analytics software company, mainly because of the success of the ELK stack. The session will cover basics of ELK stack for a kickstart", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Passion to Lear", - "Section": "Others", - "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International University", - "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chhavnish Mittal (~chhavnish)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-wih-elk-stack~axNBd/", - "title": "Getting Started wih ELK Stack" - }, - { - "Content URLs": "Will be updated soo", - "Description": "Ever thought of Building a brilliant website but don't want to waste time in setting up or do the boring server setup for it or it's too hard for you to make your website secure from attackers. Well, Django is here to solve these problems for you. Django is a rich MVC-MVT Python web Framework for the website which will do all these tasks for you. After this workshop, you will be able to create dynamic high-security web applications and perform CRUD operations by interacting with the database of your choice. We will be creating a blog website where users can log in, create blogs, rate them, etc", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Laptop with Python3 installed and Pycharm (or any of your favourite IDE)", - "Section": "Web development", - "Speaker Info": "Chhavnish Mittal is a Software Engineer at cellOS Software Systems Pvt. Ltd.. a Network Analytics organization where his role is to develop High Speed Softwares capable of handling 20.80 GBPS of data and processing it. Prior to joining cellOS. Chhavnish was a student researcher and project leader at Manav Rachna's Innovation and Incubation centre where he had also written 2 Research Papers. He also founded DELHI NCR JUG in India in collaboration with Oracle. He has received numerous awards for his work including the Young Innovator Award by MeltingPot2020. He earned his Bachelors in Technology Degree in Computer Science and Engineering from Manav Rachna International Universi", - "Speaker Links": "https://www.linkedin.com/in/chhavnish-mitta", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Chhavnish Mittal (~chhavnish)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/first-steps-into-web-development-using-django-framework~dyOna/", - "title": "First Steps into Web Development using Django Framework" - }, - { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research\nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "The Python ecosystem is growing and may become the dominant platform for machine learning. The primary rationale for adopting Python for machine learning is because it is a general purpose programming language that we can use both for R&D and in production. In this talk I will discuss 1. Python and its rising use for machine learning, 2. SciPy and the functionality it provides with NumPy, Matplotlib and Pandas.\n3. scikit-learn for machine learning algorithms, TensorFlow and Keras for Deep learning and PyTorch for Natural Language Processing, 4. How to setup your Python ecosystem for machine learning and what versions to use. At the end I will also give case studies on using this Python ecosystem for biomedical applications", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", - "Section": "Data science", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban\nhttp://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban\nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Parthi", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/mastering-machine-learning-with-python~azNya/", - "title": "Mastering Machine Learning with Python" - }, - { - "Content URLs": " Open Library Website Open Library Github Repository Open Library Client Github Repository Open Library Bots Github Repository", - "Description": "This Workshop is designed to guide developers who are interested in learning more about the basics of open source software and contributing to their first open source project. We'll look at Open Library, a mature open source project, and see how 20 open source contributors are able to make contributions which impact over a million international users. You\u2019ll learn what tools, best practices, and processes help make an open source project successful and what beginning steps you can take to enter the open source world. What is Open Library? Open Library is a non-profit online library created by Aaron Swartz and Brewster Kahle in 2006 with the mission of \u201cOne Web Page for every book ever published\u201d. Open Library is written in Python using the web.py micro-framework, and is open source on Github. Open Library uses Infobase, its own database framework based on PostgreSQL and Infogami which is its own Wiki Engine using Python. Why Open Library? Open Library has an active, supportive community, newcomer-friendly issues, and mature documentation , which makes it a good candidate for engineers who are looking to contribute to their first open source project . Some of the advantages of having Open Library as your entry to the world of Open Source Software are as follows: Open Library is very easy to install and has simple and straight-forward instructions. Issues for Beginners are labelled as first-timer-issues on the repository to help beginners get over their fear of contributing to Open Source and making it a simple process for them. Open Library has a community call every week in order to catch up the progress that each contributor is making. There is a Slack channel where anyone can be invited to and GitHub issues for communication. There is an updated Wiki which keeps getting updated as contributors contribute to the project. All coding procedures followed by Open Library are documented in a CONTRIBUTING / Getting Started guide. Some of the opportunities for new developers looking to get started to contributing to Open Library are as follows: Open Library does poorly as compared to global standards (like a modern js build system) and this is a huge opportunity for people who want to contribute to Open Library. it relies on a lot of custom code like Infogami and Infobase which are not well maintained anymore and are mostly in Python 2. So there is huge opportunity here in building a complete system while migrating to Python 3 while making sure you do retain the ease of the old code. Session Plan Creating a Github account and finding us on Github. Comment on the Slack Invite Issue to be added to the Open Library Slack Org. Understand how communication works on Open Library and getting familiar with using Github Issues and Slack for communication. Introducing yourself to the Open Library Community on Slack and initiating to become an 'Open Library Librarian'. This stage also involves talking with the Open Library community and finding Issues that match your interest. A simple and brief introduction to Git(clone, add, commit, push, pull) and Github (Fork, PRs, Issues). Setting up the project on your local dev environment. Reading Documentation as this is an important part of learning to contribute to Open Source Software. Using the Github Bug Tracker to find First Timer Issues to resolve and work on them. Making your first commit as a Open Library Librarian and submitting a Pull Request. Getting your Pull Request Merged after following community guidelines. Understanding the review process followed at Open Library and making sure to use that effectively to contribute to further Issues!", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic understanding of Python Ability to read documentation to understand the codebase Basic understanding of git and scm", - "Section": "Web development", - "Speaker Info": "Salman Shah is a Final Year Undergraduate Student at NITK Surathkal and a GSoC Student at Open Library, Internet Archive. Salman is a night owl whose primary interests include reading novels, participating in Hackathons and discussing technology. His language of choice is Python which he\u2019s used to add thousands of books to openlibrary", - "Speaker Links": " Personal Website Github Profile LinkedIn Profile", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Salman Shah (~salman96)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/open-library-one-web-page-for-every-book-ever-published~aA7ld/", - "title": "Open Library - One Web Page for every book ever Published" - }, - { - "Content URLs": "TB", - "Description": "This tutorial is meant to familiarize participants with Tensorflow, generally as a tensor library and particularly as a tool for doing day-to-day machine learning tasks. The ultimate goal of the tutorial is to be able to make participants comfortable enough with it so that they can use tensorflow as a scalable substitute for other ML libraries like sklearn. Why Learn Tensorflow? For the same reason that you should learn NumPy. Tensorflow is to Keras (and many other deep learning libraries) what NumPy is to sklearn (and many other machine learning libraries). It is the underlying data model of many deep learning applications. There are always nooks and crannies in any deep learning application that high level wrapper libraries cannot reach. The tutorial is aimed at making these accessible and debuggable with tensorflow. What will I learn? The focus of the tutorial would be on loss functions - ensuring their fundamental correctness with respect to the machine learning problem at hand, ensuring their differentiability and convergence are critical to solving a deep learning problem. There are many ready-made loss functions in tensorflow, and using these as building blocks, we will see how to make arbitrarily complex loss functions. FAQs: Q. Will I need a GPU? A. No. The beauty of tensorflow is that it can seamlessly deploy code to GPUs, without you needing a GPU to develop that code. Q. What is the format of the tutorial? A. Being a tutorial, this session is meant to be highly interactive in nature. It will be a sequence of units where concepts are first explained and then the audience will have to solve exercises in a Jupyter notebook. Q. I don't know anything about neural networks or deep learning. Should I attend this tutorial? A. Absolutely. The focus is on tensors, which are the domain of tensorflow, and not on network layers, which are domain of keras", - "Last Updated": "25 Jun, 2018", - "Prerequisites": " Basic knowledge of Python data structures and NumPy arrays Basic knowledge of linear algebra Elementary vector calculus", - "Section": "Data science", - "Speaker Info": "Jaidev is a data scientist based in New Delhi, India. He specializes in building data-driven products and the tooling around them for a living. His research interests are in signal processing and computational harmonic analysis. He is obsessed with applications of machine learning in personal productivity and recommendation systems. He blogs about these here ", - "Speaker Links": "Twitter GitHub Blo", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Jaidev Deshpande (~jaidev)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tensorflow-101~dB7Ye/", - "title": "Tensorflow 101" - }, - { - "Content URLs": "Weather API: Open Weather Map (OWM) Public Posts: Twitter API", - "Description": "This talk focuses on demonstrating the power of Python's Statistical and Data Science Libraries. I have been working on a project to classify average human sentiments as positive or negative. Classification is completely based on the prediction made by the ML models, which incorporates the weather of the location. I will try to prove that weather is \"one of the factor\" contributing to the moods/emotions of humans and ultimately affects the decision making ability. I have achieved the accuracy of 60%, which is good enough, with the existing and publically available data. The accuracy will certainly grow along with the data", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basic knowledge of Python Basic understanding of Statistics Pinch of common sense", - "Section": "Data science", - "Speaker Info": "I am a Python enthusiast, always a keen explorer of the power of python. I have been passionate about Python since my early college days, and then I went on developing many Web Apps, APIs based on Django and Flask, later on, my journey with Python turned towards exploring the magic of Data Science. It has been quite an interesting time spent exploring this field, and I must say that the depth cannot be determined. The more you experience, the more moments of awe occur", - "Speaker Links": " https://omkar-dsd.github.io/ https://towardsdatascience.com/a-simple-word-sense-disambiguation-application-3ca645c56357 https://medium.com/@omkar_dsd/when-killing-humans-becomes-the-right-choice-e3964419e78c https://stackoverflow.com/users/5130528/omkar-deshpande https://www.github.com/omkar-dsd", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Omkar Deshpande (~omkar08)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/analyzing-the-impact-of-weather-on-human-sentiments~bD7Ka/", - "title": "Analyzing the impact of weather on human sentiments" - }, - { - "Content URLs": "TB", - "Description": "\"Data is the new Oil!\" But, what is the benefit of this oil if you cannot refine (analyse) and sell/use (derive value) it. Big Data has pushed the frontier of analytical processing to gather more actionable insights in the past decade from having separate analytical servers to performing analytics close to the Data Lake/Cloud. A new paradigm of FOG computing has recently emerged which enables analyzing data at the Edge (close to the data capture device). This talk will focus on Edge Analytics enabled by Python & Raspberry Pi. Why attend this session? This session will provide a first hand look into the paradigm of FOG computing and Edge analytics. Model deployment is a critical part of the analytics life-cycle and this talk will provide insights and best practices to ensure seamless and robust model deployment. Also, the audience will get a flavor of python in embedded devices through the live and interactive demonstration using Raspberry Pi. Content The talk will cover the following sections: Evolution of analytics (Dedicated Machines -> Cloud -> Edge) The need of Edge analytics Analytics Life-cycle (ALC): Introduction, Importance of Model Deployment, Adapting ALC for Edge Analytics Model Exchange Formats (PFA, ONNX) for Deployment: Introduction & Need for Democratizing model development process Edge Device Introduction - Raspberry Pi Introduction to Portable Format for Analytics (PFA) Model Deployment on Edge Device (Raspberry Pi) using open source PFA engine implemented in Python Hands-on Application Use Cases - Deployment of Clustering, Regression, Decision Tree, Neural Network/ Deep Learning Models", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Python 2.7.x titus python package (pip install titus)", - "Section": "Embedded python", - "Speaker Info": "A die hard Pythonista, Ankit is a full time open source contributor and a former Google Summer of Code 2013 scholar under Python Software Foundation. Currently, he is developing the open source Portable Format for Analytics (PFA) implementation - Titus on Python 3. Ankit has 4 years of industrial experience in machine learning, quantitative modelling, data analytics and visualization. Over the years, he has developed an expertise in handling the entire data analytics pipeline comprising \u2013 ingestion, exploration, transformation, modeling and deployment. He is a polyglot programmer with an extensive knowledge of algorithms, statistics and parallel programming. He has shipped multiple releases of DB Lytix, a comprehensive library of over 800 mathematical and statistical functions used widely in data mining, machine learning and analytics applications, including \u201cbig data analytics\u201d. An IIT Kanpur alumnus, Ankit is also an active researcher with publications in international journal and conferences. He is actively working in the domain of IoT Analytics and has recently presented his work: \"Discovering Knowledge from Smart Meter Data using Competitive Learning Methods\" in the Data Science Congress 2018. \u201cIn-database Analytics in the Age of Smart Meters\u201d in the 5th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, 2017. \u201cSmart Meter Data Analytics using Orange\u201d in Scipy India 2017, Mumbai. Ankit is an active contributor to the Indian Python Community and has conducted the following workshops in PyCon India and Scipy India: Scientific Computing using Orange in SciPy India 2017, Mumbai. Making Machine Learning Fruitful and Fun using Orange in PyCon India 2017, New Delhi.", - "Speaker Links": "LinkedIn Youtube channel Githu", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ankit Mahato (~ankit60)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fog-analytics-using-raspberry-pi-and-python~eE7gb/", - "title": "Fog Analytics using Raspberry Pi and Python" - }, - { - "Content URLs": "http://www.calmdownkarm.com/2018/clustering (Blog Post)\nhttps://github.com/CalmDownKarm/360classificatio", - "Description": "Quick walkthrough of how word2vec combined with more traditional clustering mechanisms can be used for topic modelling and document classificatio", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Some familiarity with clustering (Kmeans) is helpful, but not required", - "Section": "Data science", - "Speaker Info": "Recently graduated from BML Munjal University, Developer at Gramener", - "Speaker Links": "calmdownkarm.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Karmanya Aggarwal (~CalmDownKarm)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/document-clustering-with-word2vec-and-hierarchial-clusters~dG7Jd/", - "title": "Document Clustering with Word2vec and Hierarchial Clusters" - }, - { - "Content URLs": "http://www.haxel.com/icic/2017/Programme/monday-23-oct-2017#the-next-era-deep-learning-for-biomedical-research \nhttp://www.metrowestdailynews.com/news/20180608/metrowest-courts-biotech-executive", - "Description": "We survey progress in recent years toward developing a theory of deep learning. Works have started addressing issues such as: (a) the effect of architecture choices on the optimization landscape, training speed, and expressiveness (b) quantifying the true \"capacity\" of the net, as a step towards understanding why nets with hugely more parameters than training examples nevertheless do not overfit (c) understanding inherent power and limitations of deep generative models, especially (various flavors of) generative adversarial nets (GANs) (d) understanding properties of simple RNN-style language models and some of their solutions (word embeddings and sentence embeddings", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "This talk will be of general in nature. Those who are witnessing the recent AI hype should be able to follow my talk. Basic python knowledge is assumed", - "Section": "Others", - "Speaker Info": "Parthiban Srinivasan is the CEO of VINGYANI, a data science company deals with Informatics 2.0, that is, Deep learning, Natural Language Processing and Machine Learning for Drug Discovery and Health. Parthiban Srinivasan is an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI", - "Speaker Links": "http://www.haxel.com/icic/2010/speakers/p_srinivasan-parthiban http://www.haxel.com/ii-sdv/speakers/srinivasan-parthiban \nhttp://haxel.com/ii-pic/2017/Programme/thursday-02-11-2017#Artificial-Intelligence-Machine-Learning-And-Deep-Neural-Networks-What-Does-All-Of-This-Have-To-Do-With-Patent-Analytic", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Parthi", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/toward-theoretical-understanding-of-deep-learning~dJjgd/", - "title": "Toward Theoretical Understanding of Deep Learning" - }, - { - "Content URLs": "https://en.wikipedia.org/wiki/Decentralized_autonomous_organization\nhttps://blockchaindevs.github.io/MeetupDA", - "Description": "Open Source Communities and their management. How things work currently A case study of different open source organizations: Advantages and disadvantages of current systems. The issues with Open Source organizations are nothing new, what are the possible solutions available? DAO and automation of majority of the tasks of a \"Open by default organizations\" What part of the organization can be automated, what can't. Important Aspects that usually breed trust among members::\n - Transparency\n - Consistency & Automation\n - Inclusion & support Our Proposal We will be posting codebase and complete websites and mobile apps that offer these solutions: Automated and transparent membership procedure. Transparent Public Elections on Blockchain for a board with automated publication of votes and results. Automate votes based on proposals Automated Procedure to apply for grants: with voting members and results being put up on Blockchain Automated meetings with MOM being recorded and put up on blockchain. Testing Proposal from the ground up: Start Small and test if these methods work locally in meetup groups \n- Automation of Tasks around meetups:\n...\nWe will keep updating here as and when we have deployed solutions on blockchain Tools used for these automation: Blockchain Dapps using : Solidity & Vyper\nPython: Kivy Framework for mobile apps and Web3.js & other such frameworks. Repos:\n They will be made online shortly, currently the experimentation is going on the following repos: https://blockchaindevs.github.io/MeetupDAO please excuse for the alpha quality of the software as they are just experiments as of now. This is a open source initiative based on the needs we feel we have seen arise in open source communities around us. Ultimate Goal Use this proposal as a catalyst and create small Organizations in local communities testing this theory. If things work in local communities, create a National Level Organization for managing the tasks around PyCon India This is just one of the hopefully multiple proposed solutions for moving on post PSSI", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "A willing ness to contribute, ability to learn. \nOpen Mind to experiment even if it leads to failure", - "Section": "Developer tools and Automation", - "Speaker Info": "http://github.com/akshayaurora Akkshay is huge open source enthusiast, he has helped bootstrap different communities around Kivy, PyDelhi, ILUGD, BlockchainDevs , HyperLedger Delhi/NCR & chaired conferences like PyDelhiConf, Pycon-India, Global Blockchain Conference. He has been involved and working on blockchain based projects from 2011 onwards, he is one of the core developers of Kivy python framework & Electrum bitcoin wallet that has been built on top of it", - "Speaker Links": "http://github.com/akshayauror", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Akshay Arora (~akshayaurora)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-open-source-communities-on-blockchain-a-transparent-way-to-manage-organizations~aKkxa/", - "title": "Automating Open Source communities on Blockchain: A transparent way to manage Organizations" - }, - { - "Content URLs": "Slides will be uploaded soon", - "Description": "Python - Turing Complete and easy at the same time. Given its simplicity, one may be tempted to use it to solve a problem of any magnitude. But as the codebase scales, so does the difficulty in managing it. And as the applicability scales up, so does the difficulty in maintaining performance. In this workshop, we will walk through how these problems crop up in the first place, and how to tackle them. This workshop will NOT cover scalability from the perspective of distributing data loading and computation across multiple compute units (horizontal scalability). We will focus more on how to write code from the very start that is both efficient in performance and makes a larger codebase manageable. The topics we will go through are: 1.Performance - How should one write \"fast\" code Finding the bottleneck - Profiling Compiling Python to C - JIT vs AOT / Cython vs Numba vs Pythran vs PyPy - How they differ and choosing which one is for you Concurrency - To parallelize or not to parallelize, to sync or not to sync Choosing the right data structures Hacks and bits that can get us the extra performance 2.Design Principles - How should one write \"good\" code, because we have all written code that we have difficulty in understanding ourselves in no time Logging - Keeping track of what happened when and where Type Checking - The why and the how Unit Tests and beyond", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Cython, numba, and pythran installed. All of them are available on pip/conda Working knowledge of Python", - "Section": "Others", - "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", - "Speaker Links": "R S Nikhil Krishna Personal Website Github Linkedin StackOverflow Lokesh Kumar T Github Linkedin StackOverflow", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/writing-code-that-you-need-not-look-back-at-fast-and-good-python-at-scale~dLlrd/", - "title": "Writing code that you need not look back at - Fast and \"good\" python at scale" - }, - { - "Content URLs": "So, Slides can be seen here: https://slides.com/tanayagrawal/efficient-hyperparameter-optimization#/ Full content is available here: https://github.com/tanayag/pycon_18_hyperopt You can also have a look at my article: https://blog.goodaudience.com/on-using-hyperopt-advanced-machine-learning-a2dde2ccece7 In the Repo iris.csv is the dataset that we'll work on. docker folder contains the scripts to setup Environment \"Introduction to Hyperopt.ipynb\" is iPython Notebook which contains the implementation which we'll work on during workshop and understand the concept \"link_to_slides.txt\" contains the link to our presentation", - "Description": "Hands on Experience with Advanced Hyper-parameter Optimization Techniques, using Hyperopt We'll go step by step, starting with the Hyper-parameter optimization with SkLearn's Grid Search, we'll compare it with the more effective Hyper-Parameter Optimization TPE Algorithm implemented in Hyperopt.\nWe'll also go through on how to parallelize the evaluations using MongoDB making the optimization even more effective. A Docker Image will be provided, so that participants won't have to waste time in setting up the environment. The Workflow of the Workshop would be: We will start with a slide presentation so that participants get some insight on what they are going to do. After that we'll shift on to a Juypter Notebook(pre-installed in the docker environment, so you can just focus on the implementation part), here they will implement the code, and see the best algorithms of hyperparameter optimization working. After that we'll show a working demo of a problem that we were working on and solved using Hyperopt during our Summer Intern at MateLabs. After attending this workshop you will be able to apply Hyper-parameter optimization using better algorithms which decides the hyper-parameters based on information. In short much much efficient model training", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic Python Coding and a little familiarity with Machine Learning/Data Science", - "Section": "Data science", - "Speaker Info": "Tanay Agrawal Working on Machine Learning/Deep Learning and also an Open Source Enthusiast. Currently in Final Year of his Engineering. He is working as Deep Learning Intern at Matelabs. He along with team at MateLabs is creating Meta Algorithms, so that user even with minimum or no knowledge of Machine Learning would be able to use it. Also he is a contributor at SymPy. He has previously worked on state of the art Classification and Object detection Models as well. He has previously conducted Python workshop at SFD-SMVDU and also he conduct the session of AI Circle at his College regularly. Anubhav Kesari Currently at fInal year of engineering from IIIT Guwahati. Two worked on the same problem and solved it using Hyperopt. Anubhav is the summer intern at MateLabs as well. He has worked at Cadence Design Systems in summer of 2017 as Software Development Intern. He has also been working on development of blockchain based distributed neural networks at MateLab", - "Speaker Links": "Tanay Agrawal https://github.com/tanayag https://angel.co/tanay_agrawal Anubhav Kesari https://github.com/kesarianubhav https://www.linkedin.com/in/anubhav-kesari-588a03131", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "tanay_agrawal", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/advanced-ml-learn-how-to-improve-accuracy-by-optimizing-hyper-parameters-using-hyperopt~aMmGa/", - "title": "Advanced ML: Learn how to Improve Accuracy by optimizing Hyper-Parameters using Hyperopt" - }, - { - "Content URLs": "https://gautam-ankit.github.io/HomeAR", - "Description": "In this project, we are going to create a home finder in which we are going to give an individual marker/bar code to each and every home and going to create a web-app which will tell about the home on starring the camera on the marker/bar code. This idea will help out to find some place way better than the Google maps because one can generate its own marker for his/her home and can edit the details of there home, through which one can recognize the home. For management of this data we are going to use several concept of Big data also. But this is the best way possible to implement and link augmented reality with python", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "HTML and CSS and basic Javascript,\nbasic python ,\nsome programming concepts", - "Section": "Core python and Standard library", - "Speaker Info": "As a Microsoft student partner, I gave several presentations for Hour of code. And as a Mozilla campus club caption, I gave several presentations for Virtual reality and Augmented reality using Aframe web framework", - "Speaker Links": "https://www.linkedin.com/in/ankit-gautam-9b0524108", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Ankit Gautam (~Gautam-ankit)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/home-finder-using-python-and-augmented-reality~dNnvd/", - "title": "Home finder using Python and Augmented Reality" - }, - { - "Content URLs": "Will be updated soon", - "Description": "In this talk, I will provide a concise understanding of Threading and Global Interpreter Lock(GIL) in Python. In the modern era of hybrid cores and processors, there is an in demand need for concurrent and parallel programming paradigms. Python, since its inception has amazing support for single threaded applications. The extensive use of Python in booming fields like Machine Learning has paved the way to constantly improve multi-threaded applications in Python. I will speak from ground level covering very crucial aspects of Threading and Locks which will provide a better roadmap for community to develop better Python applications. Program outcomes: How threading can improve performance, its pros and cons. What works best in which environment between threads and processes. Why GIL matters the most in Python How to leverage the power of open source source code to understand the crux of language. Contents to be covered: 1. Threading for noobs: Terminologies: Process, threads, multithreading, multiprocessing, types of threads, locks, mutex, CPU and I/O bound processes. Multithreading in Python: Threading module (with example) Comparative analysis of Sequential vs Multithreaded execution in Python (with example) 2. Understanding the global interpreter lock (GIL): What and why of GIL Impact of GIL on CPU and I/O Bound Processes In-depth understanding of GIL using cpython interpreter source code Reference counting Ticks via context switching 3. Infamous concepts: Cooperative vs Preemptive multitasking Parallelism vs Concurrency Thread Safety in Python 4. Removing the GIL: Famous GIL removal patch Guido on GIL, Larry Hastings Gilectomy 5. Questions Agenda: 0 - 6 minutes : section 1, Threading for noobs 6 - 15 minutes : section 2, Understanding GIL 15 - 25 minutes : section 3, Infamous concepts 25 - 28 minutes : section 4, Removing the GIL 28 - 30 minutes : section 5, Questions ", - "Last Updated": "26 Jun, 2018", - "Prerequisites": " Basics of Python: Class, objects, list, libraries", - "Section": "Core python and Standard library", - "Speaker Info": " I have been into CS field for over 6 years now. I have completed my BTech in Information Technology from Veermata Jijabai Technological Institute, Mumbai (VJTI). Also, I have done my diploma in Information Technology. I will be joining Barclays India as an SDE in the month of August. Software development is my long suit. AI, ML and Data Science are my goto subjects. Competitive programming is something I love to do in my spare time. I like tinkering with new technologies, creating new projects and implementing things by myself from scratch. I have been contributing on github for over a year now. I am an avid learner and I can quickly adopt to new frameworks. Also, I am a mediocre public speaker with modest interest in Fintech\n and Investment Banking. ", - "Speaker Links": " My Github profile Get in touch with me on LinkedIn Ping me on AngelList My personal website created for fun, never updated :! Datacamp profile Coding handle: chiragshah9696 about.me", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Shah (~avidLearnerInProgress)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-multithreading-by-deciphering-the-cpython-interpreter-source-code~aOora/", - "title": "Understanding multithreading by deciphering the cpython interpreter source code" - }, - { - "Content URLs": "Slides will be uploaded soon. Github Repository: https://github.com/MeghaSharma21/WikiCV Project details: https://phabricator.wikimedia.org/T178688 Link to the tool: https://tools.wmflabs.org/outreachy-wikicv/wiki-cv", - "Description": "There lies a huge gap between a website made as a hobby/college project and that made for professional purposes. The journey to cross this is marked through database optimizations, consistent look and feel, efficient cache layer and many other things! Before delving into the open source world, my code screamed that it's owned by a college kid. But things changed once I interned with Wikimedia (under the Outreachy program). I want to share this very experience with my audience that how some gotchas and design decisions can bring about this transition. In this talk, I'll touch upon some of these areas that mainly deal with backend and database. My talk will summarize my learning from using Django in an application built for Wikipedia and is capable of handling huge amount of Wikipedia's data. To give a bit of background - I built this application for Wikipedia under Outreachy Round 15 (https://www.outreachy.org/). The app summarizes the contributions of the Wikipedia editors and presents it in a CV-like format. The biggest development challenge was dealing with millions of edits and doing all the related computations within seconds. Without any kind of optimizations, the webpage took 3 hours to load. Through my talk, I want to bring out the journey from 3 hours to 3 seconds on the table! Broad outline of my talk is as follows: Why Django : It's very important to understand why and when to use Django. Majorly I'll be touching upon the scalability aspect and how it's a full package when it comes to web development. Reducing the response time : When one is dealing with a database as huge as that of Wikipedia's, response time becomes of paramount importance. Optimizations like implementing a cache layer , using cron jobs , sessions etc will be discussed. Also, design choices will be compared - like cache layer using database vs sessions in python. Database Optimizations : In this I'll be covering how database choice and query optimizations can affect the performance when dealing with large datasets. Hope you will find this talk interesting. :)", - "Last Updated": "26 Jun, 2018", - "Prerequisites": "Basic knowledge of Python, Django and querying RDBMS is required", - "Section": "Web development", - "Speaker Info": "I'm a final year student pursuing B.Tech from Punjab Engineering College. College made me fall in love with coding and after that there has been no looking back. I've been an Outreachy (https://www.outreachy.org/) intern and currently a part of Google Summer of Code. When it comes to the open source world, I'm a regular contributor in Wikimedia.\nOther than coding, I love reading, writing and trying out new things", - "Speaker Links": " Blog: https://medium.com/@meghasharma4910 Github: https://github.com/MeghaSharma21 Outreachy project: https://github.com/MeghaSharma21/WikiCV Google Summer of Code project: https://github.com/MeghaSharma21/WorklistTool-GSoC-2018", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Megha Sharma (~megha480)", - "created_on": "26 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/optimizations-in-web-development-journey-from-a-college-project-to-a-professional-product~dPp4d/", - "title": "Optimizations in Web Development: Journey from a college project to a professional product" - }, - { - "Content URLs": "Tutorial Series https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-2 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-3 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-4 https://blog.paperspace.com/how-to-implement-a-yolo-v3-object-detector-from-scratch-in-pytorch-part-5 Github Repo (Most starred repo for a Python implementation of YOLO v3, at 589 stars at the time of speaking) https://github.com/ayooshkathuria/pytorch-yolo-v", - "Description": "The workshop will walk the audience on how to implement a state of the art object detector (YOLO: You only look once) from scratch using the PyTorch deep learning framework. The main The aim is not to merely show the audience how to implement the detector that can work on videos, but give them a deep insight about the problems that rear their heads only when one is implementing a deep architecture. Some of these issues include, Rapid Prototyping with PyTorch : Which PyTorch classes and abstractions to use to quickly code up neural network. How to implement a layer if it doesn't already ship with PyTorch. Our detector has 3 such layers! How to deal with complex architectures efficiently : What if your network has more than a 100 layers? Our detector certainly has 106 ! Do we write 106 lines of code for each layer? What if we want to run our detector over a folder containing 100000 images that we can't fit into our RAM at once. Best PyTorch practices to get around problems like these will be discussed. Speeding up Python code with Vectorisation : Python can be a slow language, but PyTorch does provide a lot of functions that are merely wrappers for super fast C code under the hood. Vectorisation and broadcasting will be covered in great detail. Using vectorised code instead of loops to do iterative tasks can give speed ups as much as 100x. Our detector can not work in real time without these optimisations. Managing GPU resources : How to write device-agnostic code, parallelize GPU/CPU ops, practices to reduce redundant GPU memory usage, and how to time GPU code. We will review the entire code base, and spend much time on justifying design decisions. A lot of non-critical code will be provided as it is to the audience, while they are expected to code along when it comes to the critical parts. These parts would be discussed in greater detail. Important PyTorch features might also be demonstrated using toy examples outside the detector code base, which the audience is also expected to code along. A docker image as well as Jupyter notebook will be provided to the audience. Google Colab may also be considered with notebooks provided. Most of the tutorials online demonstrate how to write code that is more proof-of-concept rather than being performant. When it comes to learning to code complex architectures, especially when we are transitioning from beginner to intermediate stage, most of us have to rely on the laborious process of reading open source code. The idea of this workshop is to help audience move along this journey", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Knowledge of Python Basic understanding of convolutional neural networks, image classification and preferably, but not necessarily object detection (Will spend 15 min or so giving an overview of YOLO algorithm) Basic understanding of PyTorch (the level that can be reached by taking the official 60 min tutorial)", - "Section": "Data science", - "Speaker Info": "I'm currently an research intern at a DRDO Lab where I work on video semantics, detecting violence as well as unusual activity in surveillance footage. My other interests include weakl supervised, unsupervised learning and generative modelling using GANS. I've recently graduated college, and while at college, I founded AI Circle, SMVDU, a club dedicated to helping students get started with machine learning through lectures and hands-on sessions, many of which were conducted by me. I am very passionate about sharing what I've learned, and write articles regularly at Paperspace and Medium", - "Speaker Links": "Paperspace blog: https://blog.paperspace.com/author/ayoosh/ Medium : https://medium.com/@ayoosh Github : https://github.com/ayooshkathuri", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Ayoosh Kathuria (~ayoosh)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-to-implement-a-yolo-object-detector-from-scratch-using-pytorch-and-opencv~aQq9a/", - "title": "How to implement a YOLO object detector from scratch using PyTorch and OpenCV" - }, - { - "Content URLs": "in progres", - "Description": "Data classes have been introduced in Python 3.7 (Refer to PEP 557 -- Data Classes). This talk is to introduce data classes to the audience. Talk about why data classes and how they are different from other alternatives like named tuples, et", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Knowlede of Object Oriented Programming with Pytho", - "Section": "Core python and Standard library", - "Speaker Info": "I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.\nI have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delhi I have done a talk \"How import works in Python\" at Pycon 2017 Delh", - "Speaker Links": "github link - https://github.com/sdonapar\nlinkedin profile - https://www.linkedin.com/in/sasidonaparthi\ntwitter handle - @sdonapa", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sasidhar Donaparthi (~sasidhar)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/what-you-need-to-know-about-data-classes-in-python-37~dRrEd/", - "title": "What you need to know about data classes in Python 3.7" - }, - { - "Content URLs": "http://www.thedurkweb.com/automated-anonymous-interactions-with-websites-using-python-and-tor", - "Description": "Need to get some repetitive task done on your web browser? Want to automatically fill boring forms? Or maybe you want to crawl pages that annoyingly check whether you are a browser or a robot. Or maybe you want to repeatedly bias an online poll in your favour (as long as you don't harm anyone). Circumvent all of that with Selenium, the browser automation tool. And if want you want to protect your IP while doing it then just fire up tor-selenium browser, which gives you the power of tor and browser automation. In this talk: I'll show you how to set up the browser. How to access the website through code. How to design your script to navigate through the pages and button clicks. How to effectively do your activity, like filling up text fields etc. And then a demo of it working completely.", - "Last Updated": "27 Jun, 2018", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ved Mathai (~ved47)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automate-anything-on-the-web-using-python-bindings-for-tor-selenium-and-hide-your-ip-while-doing-it~eVyXd/", - "title": "Automate anything on the Web using Python bindings for Tor-Selenium and hide your IP while doing it." - }, - { - "Content URLs": "Would be uploaded soo", - "Description": "My talk would be starting from the very grounds of machine learning . What is it and how is it connected with our biological brain. I will be introducing some biological concepts and infrastructure of our brain to explain to them how our natural ability of thinking and deduction work, because at last the whole field of artificial intelligence is just an attempt to mimic our brain. Isn't it?\nThis will be through a series of fun QnA . Then we will see the mathematics core which enables us to lay down the logic and basics of the brain as formulas . \n- Then we will start with the classic linear regression . Will study the basic idea behind it and also see what kind of problems we should apply it.\n- Next will be the logistic regression , a classification algorithm. Learn the difference between these two and how logistic regression could be implemented and study the beautiful mathematics behind it. \n- Then we will go for a clustering algorithm, that is, Knn . Study the simple dynamics and application of this algorithm\n- Then a glimpse over the structure and mathematics of neural network . As this talk is for the novice I would keep the mathematics to the minimum and would no go deep into \"deep\" learning.\nWe will wrap up seeing some of my projects in action so that the audience could feel the power of AI", - "Last Updated": "27 Jun, 2018", - "Section": "Data science", - "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", - "Speaker Links": "udayupreti.m", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "uday1201", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/evolution-and-basics-of-machine-learning~bWzxa/", - "title": "Evolution and basics of Machine Learning" - }, - { - "Content URLs": "This talk will be based on my article on Towards Data Science The hands-on examples have also been open-sourced on GitHu", - "Description": "Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. We will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D) using a hands-on approach with Python and popular open-source visualization libraries like matplotlib and seaborn. The talk shall be structured as follows: Motivation for Effective Data Visualization A quick refresher on Data Visualization Brief introduction into python open-source frameworks for visualization pandas matplotlib seaborn bokeh Univariate analysis with hands-on examples Multivariate analysis with hands-on examples Visualizing data in 2, 3, 4, 5 and 6 dimensions Visualizing a combination of numeric and categorical data Strategies for effective data visualization Conclusion", - "Last Updated": "25 Jun, 2018", - "Prerequisites": "Basics of Python, data terminology (rows, columns, feature, data points, data types) helps but we will be covering briefly during the session. Hence it's not essential", - "Section": "Data science", - "Speaker Info": "Dipanjan Sarkar is a Data Scientist at Intel, on a mission to make the world more connected and productive. He primarily works on data science, analytics, business intelligence, application development, and building large-scale intelligent systems. He holds a master of technology degree in Information Technology with specializations in Data Science and Software Engineering. He is also an avid supporter of self-learning. Dipanjan has been an analytics practitioner for several years now, specializing in machine learning, natural language processing, statistical methods and deep learning. Having a passion for data science and education, he is a Data Science Mentor at Springboard, helping people up-skill on areas like Data Science and Machine Learning. He also acts as a contributor and editor for Towards Data Science, a leading online journal focusing on Artificial Intelligence and Data Science. Dipanjan has also authored several books on R, Python, Machine Learning, Social Media Analytics, Natural Language Processing & Deep Learning. More about me: LinkedIn: https://www.linkedin.com/in/dipanzan/ GitHub: https://github.com/dipanjan", - "Speaker Links": "LinkedIn: https://www.linkedin.com/in/dipanzan/ Blog Posts: https://towardsdatascience.com/@dipanzan.sarkar GitHub: https://github.com/dipanjanS Featured stories on KDnuggets: https://www.kdnuggets.com/?s=dipanjan+sarkar Recent books:- https://www.springer.com/us/book/9781484223871 https://www.springer.com/us/book/9781484232064 https://www.packtpub.com/big-data-and-business-intelligence/hands-transfer-learning-pytho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Dipanjan Sarkar (~dipanjan)", - "created_on": "25 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-art-of-effective-visualization-of-multi-dimensional-data-a-hands-on-approach~ep6Vb/", - "title": "The art of effective visualization of multi-dimensional data - A hands-on approach" - }, - { - "Content URLs": "To be uploade", - "Description": "Sarcasm is an intensive, indirect and complex construct that is often intended to express contempt or ridicule. But in speech, it is multi-modal, involving tone, body language, and gestures along with linguistic artifacts used in speech. Sarcasm in the text , on the other hand, is more restrictive when it comes to such non-linguistic modalities. This makes recognizing textual sarcasm more challenging for both humans and machines. Sarcasm detection plays an indispensable role in applications like online review summarizers, dialog systems, recommendation systems and sentiment analyzer . This makes automatic detection of it an important problem. However, it has been quite difficult to solve such a problem with traditional NLP tools and techniques . So we will talk about the ongoing research and techniques developed to counter these problems. I have been trying to solve this problem for a while now so let's discuss it and hope that we solve it in the near future. Some of this techniques include tracking physiological gestures like eye tracking, extraction of psychological triggers or building a sarcasm dataset with the help of context features ", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "The only thing I require from the audience is their attention and interest in this fun but a very serious problem in the world of data science", - "Section": "Data science", - "Speaker Info": "A Researcher | Machine Learning engineer | Backend Developer | Entrepreneur . Currently working as Research Assistant at IIIT Delhi . Director in Greatech Soft Solutions Private Limited . Have taken over 10+ talks on machine learning . Python lover. 99% of my work is in python be it ML or Web Development (Django, Flask). Love to be on stage . Hardcore Hackathon crazy. Won over 7 Hackathons including Angel Hack and TATA Crucible(North Zone) . Participated in F8 Hackathon in San Jose,CA (sponsored) and Ultrahack Sprint 1 in Helsinki, Finland (Remotely)", - "Speaker Links": "udayupreti.m", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "uday1201", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sarcasm-detection-in-natural-language-processing~eXAga/", - "title": "Sarcasm Detection in Natural Language Processing" - }, - { - "Description": "Need to understand the customers better way based on the attitudes and then serve better and also find the algorithm by which we can classify the future customer", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Python , Jupyter notebook and some statistical conceptual understandin", - "Section": "Data science", - "Speaker Info": "A doctor in statistics from Osmania University. I have been working in the fields of data analysis and research for the last 14 years. My expertise is in data mining and machine learning \u2013 in these fields I\u2019ve also published papers. I love to play cricket and badminton", - "Speaker Links": "https://www.linkedin.com/in/statsvenu\nhttps://www.linkedin.com/in/suresh-chekuri", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "statsvenu manneni (~statsvenu)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/understanding-customers-in-better-way-a-market-research-application-using-python~bYB2d/", - "title": "Understanding customers in better way- A Market research application using python" - }, - { - "Description": "Django as a web framework Django is one of the most powerful web frameworks out there! (This is definitely subjective) According to stackoverflow , python has ~10% developer base. They also predict that by 2020, the developer base would be 16-19%, if it grows at the same pace, making it the leader. Usage of python for web development has been increasing significantly. When it comes to python web framework, Django is the name that rings the bell. Will discuss about a social media processing data pipeline that can be processed using the frameworks available for python. Discuss about the pitfalls to be taken care of and advantages of using these.", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Python Basics of web development Rest APIs", - "Section": "Core python and Standard library", - "Speaker Info": "I am Rahul Reddy, graduated from IIT Varanasi, Product Lead at Setuserv informatics PVT Ltd. I lead a team building data analytics pipelines that handles more than 200-300 Million records a month. Enthusiastic about building even larger, robust, secure data pipelines", - "Speaker Links": " Stackoverflow LinkedIn", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "rahul reddy (~rahul01)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-chained-from-personal-interactive-websites-to-complex-data-pipelines~eZD5b/", - "title": "Django Chained - From personal interactive websites to complex data pipelines" - }, - { - "Description": "root@pycon2018:~# python zer0-day_exploit.py [+] Checking for vulnerability.... [+] Triggering BoF.... [+] Sending staged payload... [+] Waiting for server response... <=HeLL0 fri3nd=> Do you want to know how hackers use Python for development of their hacking tools and arsenal? Have you ever thought how hackers compromise vulnerable computers around the globe with the power of automation that comes with python? If you are looking for answers to these quentions then you have come to right place... In this talk, I will demonstrate various use cases of python programming in hacking and cybersecurity. We will go through various python libraries such as Sockets, Httplib2, Scapy, Shodan etc. In the beginning, we will see the various Python implementations to perform computer networks auditing and attacks such as port scanning, ARP spoofing, DoS attack and remote code execution with buffer overflow vulnerability. Shodan is the search engine for computers and IoT devices connected to the internet around the globe and has API wrapper as a python library. With shodan, I will demonstrate how we can look up for IoT devices. We will see python script in action using shodan to find MQTT brokers to extract GPS information out of them via CVE-2017-7650 vulnerability and due to poor access control list configuration in them", - "Last Updated": "27 Jun, 2018", - "Prerequisites": " Python programming Basics of computer networking", - "Section": "Networking and Security", - "Speaker Info": "I am Chirag Jariwala ( @CJHackerz ), B.Tech (4th year) Information Technology student from SRM Institute of Science and Technology - Chennai. I am independent cybersecurity analyst and researcher and have been self-learner in this space quite for a while. I use lots of python scripting in my hacking adventures. I have done numerous workshops and training to teach people about ethical hacking and penetration testing inside my university campus. Have been active community member and given few talks at Null Chennai Chapter (an open source cyber security community which hosts meets for OWASP)", - "Speaker Links": " GitHub: https://github.com/CJHackerz Twitter: https://twitter.com/cjhackerz LinkedIn: https://www.linkedin.com/in/cjhackerz/ Null community profile: https://null.co.in/profile/8808-script-alert-chirag-jariwala-script", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Chirag Jariwala (~chirag18)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/journey-into-the-world-of-hacking-and-cyber-security-with-python-programming~e1zma/", - "title": "Journey into the world of hacking and cyber security with Python programming" - }, - { - "Description": "About a month ago my inbox was flooded with emails beginning with We have decided to update our Terms and Conditions... . Though I am a technical person working in a financial services company and thus terms and conditions are supposed to be my cup of tea, I couldn't get myself to go through any of the actual Terms and Conditions . A python based Natural Language Processing Engine to summarize the often twisted contents of a legal agreement and defining the pros and cons for the agreement in question for the user would better equip an user to understand what exactly they are agreeing to. This is very important in today's age where we've seen our personal data being breached for the benefit of social media based companies who then sell this data to achieve gains that could be political too. In the financial and legal world such documents are of utmost importance. The process of developing a solution like this would be about defining the Gives and Takes of an agreement. Every agreement consists primarily of the things that a user is expected to receive from the other party/user and vice versa. The next step would be quantifying that particular give or take. This would give the user an estimate of what he/she would be expected to give/spend. Comparing that with the takes would help the user make a decision as to whether to agree with the terms and conditions or not. The quantifying system could consist of a number of attributes and the \"twisted ones\" or the ones affecting the user's privacy or other sensitive aspects cold be flagged appropriately so that the user can review and choose. This talk would talk about the steps, right from defining legal contexts to setting up the words, phrases and understandings for typically legal content", - "Last Updated": "27 Jun, 2018", - "Prerequisites": "Anyone who'd want to see themselves make better decisions and understand how agreeing to certain Terms and Conditions could affect their lives and their privacy", - "Section": "Data science", - "Speaker Info": "Aroma is a graduate fresh out of the National Institute of Technology, Warangal. As a techno-activist she has been a part of many projects that promote diversity and inclusion. She believes that Automation is the path to Inclusion. In 2016, a teammate of her \"Shoes for the Visually Impaired\" project presented it at the FOSSASIA. She reads, writes and enjoys walking to explore places. She presently works in a financial services firm and believes that solving problems that she has would solve problems for a large chunk of the world. An ML enthusiast she has about 20+ Coursera Certifications with the respective project work to support her learning in that field. Python is one of her favorite languages and hackathons her favorite party", - "Speaker Links": "Aroma Rodrigue", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "ARodz (~AromaR)", - "created_on": "27 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-nlp-to-demystify-terms-and-conditions-and-summarize-the-contents~b2Aza/", - "title": "Using NLP to demystify \"Terms and Conditions\" and summarize the contents" - }, - { - "Content URLs": "Slides Talk Specific Slides On Their Way References QN-S3VM Python Package: http://www.fabiangieseke.de/index.php/code/qns3vm Semisupervised Learn Python Package: https://github.com/tmadl/semisup-learn S3VM Seminal Work: https://papers.nips.cc/paper/1582-semi-supervised-support-vector-machines.pdf", - "Description": "Machine Intelligence algorithms, in their application to real world problems, are largely models trained in a supervised manner. Hence, they are hindered by the reality that in most practical situations unlabelled data is easier to come across and obtaining appropriately annotated and labelled data may be prohibitively expensive. Herein lies the appeal of semi-supervised learning algorithms that allow us to draw inferences with only a few labelled data samples existing among a vast amount of unlabelled data. In this talk. through the application of a variation of the tried and tested SVM, called the S3VM(Semi Supervised SVM) on standard dense and sparse data sets, we will explore the merits and demerits of semi-supervised learning. We will also take a cursory look at a few approaches used to solve the modified optimisation problem that arises when we adapt the SVM for use in a semi-supervised setting. The outline of the talk will broadly be the following: Why Semi-Supervised Learning Advantages of using Semi-Supervised algorithms rather than Supervised algorithms on limited data Approaches to Semi-Supervised Learning: Transduction vs Induction+Deduction Modifying the SVM for Semi-Supervised Learning Approaches for solving the modified SVM: Label-switching vs deterministic annealing Semi-Supervised Learning is not a silver bullet: Discussion of disadvantages", - "Last Updated": "28 Jun, 2018", - "Prerequisites": " Familiarity with Python Programming Minimal proficiency in Optimisation Methods Intermediate proficiency in Support Vector Machines", - "Section": "Data science", - "Speaker Info": "I'm Indraneil Paul, a final year Computer Science student at IIIT Hyderabad. I have been involved in machine learning, computer vision and mathematical optimisation for the best part of the past three years due to my research work. I was previously working in the Computer Vision lab on an autonomous driving project and am currently working on applying graph based machine learning models to social networks. I was also a Google Summer of Code '17 student under electric vehicle startup Green Navigation (now nav-e). I occasionally foray into experimentation with Blockchain technology with Hyperledger", - "Speaker Links": "Github: https://github.com/iNeil7", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "iNeil77", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/semi-supervised-learning-with-svms-in-python~e3pRa/", - "title": "Semi Supervised Learning with SVM's in Python" - }, - { - "Content URLs": "Talk specific slides will be updated soon. References: https://docs.python.org/3/library/unittest.mock.html https://docs.python.org/3/library/unittest.mock-examples.htm", - "Description": "Testing is one of the cornerstones of good software engineering. It addition to help ensure that your code works as expected, it also has the advantage of iterating over your code faster. With sufficient tests, you can be pretty sure that your new code doesn't break any old ones. One of the biggest issue I find with writing tests is that there is a lot of boilerplate code that needs to be written to get even the basic unittests to work. This talk will focus on mock and patch . These are awesome utilities provided with unittest module to make your testing life much more painless but not a lot of people know about them. The flow of the talk will be as follows: Intro to testing: Why do we actually need testing? The basic problem I find with testing: Boilerplate code. (with examples) Introduction to MagicMock and patch . Applying them to real tests. Enhancing those tests: Assertions on mock. Caveats associated with their use.", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Some basic knowledge about unit testing in Python would be great", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a student at IIIT-Hyderabad on the verge of completing my M.S.\nFor the last two years, I have also been working part-time as a sysadmin for all institute servers and was involved in maintaining services like proxy, directory and the mail server. I have previously interned as a Production Engineer for Facebook and am currently a Google Summer of Code intern with CCExtractor", - "Speaker Links": "Github LinkedIn Blo", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aaditya M Nair (~AadityaNair)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/supercharge-testing-by-mocking~b4qxd/", - "title": "Supercharge Testing by Mocking" - }, - { - "Description": "Less technical people are often afraid of terminal and command line utilities, but are happy to enter the same data on a website. What if Jupyter Notebook could provide cheap, human-friendly UIs for everyone? Less technical people are happy to interact with graphs and tables, but even with Jupyter Notebook, they are anxious to run cells. What would a permissioned nbviewer look like for enterprise? The goal of this talk is to get you thinking about how to use Jupyter to enable rapid-development and low-cost solutions to empower those without technical know-how in constrained environments", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Familiarly with Jupyter Noteboo", - "Section": "Others", - "Speaker Info": "I am a developer for the JavaScript team at the D. E. Shaw group. One of our core principles is that users come first; we are hyper focused on improving the user experience for developers, technical users, and non-technical users of everything from intranet sites to the interactive python environment. We aim to delight", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marc Udoff (~mlucool)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/empowering-the-less-technical~e5r8a/", - "title": "Empowering the Less Technical" - }, - { - "Description": "Nearest Neighbour(NN) algorithm, which is a lazy and a non-parametric method used for classification is one of the most intuitive and widely used machine learning algorithms. It is most often sought by business consultants for its simple and easy to understand framework. The performance of the algorithm can be enhanced by optimally tuning its hyper-parameters, which includes the k-value and the distance metric. However, practitioners tend to focus only on optimising k and ignores the other. The very term \"nearest-neighbour\" means that we employ some notion of near, i.e. we use some distance metric to quantify similarity and thus define neighbours. This emphasises the importance of the Distance Metric in the NN algorithm. In this talk, we present some of the novel approaches used, to learn the distance metric from the training data. Also, we demonstrate how slight amendments to the approach can lead to an inception of a dimensionality reduction technique. The above mentioned approaches are bundled together as a python package and is showcased to the audience. Structure of the Talk: 1. An overview of K-NN algorithm\n2. Theory of Distance metrics\n 2.1 Mathematical definition of a metric\n 2.2 Some common distance metrics\n3. Deep dive into Metric Learning techniques\n 3.1 Why is it important?\n 3.2 The math behind metric learning \n 3.3 Application in Dimensionality Reduction\n4. Implementation using some popular dataset", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Basic programming skills in python, machine learning(familiarity with common classification and dimensionality reduction techniques) and linear algebra", - "Section": "Data science", - "Speaker Info": "Kousik is pursuing his undergraduate studies at Chennai Mathematical Institute and shows immense interest in Machine Learning and Finance. He has contributed to multiple open source projects and has interned with the research and development teams of various organisations. His primary research interests include computer vision, graph based machine learning algorithms and quantitative finance. He has also involved in different technical talks at IIT-M and is one of the members of the Chennai Python Meetup group", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kousik Krishnan (~kousik)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/comprehensive-study-of-distance-metric-learning-in-nearest-neighbor-algorithm~e7w1e/", - "title": "Comprehensive Study of Distance Metric Learning in Nearest Neighbor Algorithm" - }, - { - "Content URLs": "This GitHub repo links to any content relevant to the talk", - "Description": "This talk intends to provide a fairly gentle introduction to the fundamental ideas behind quantum computing and the concepts of quantum physics that allow quantum computing to surpass the limits of classical computing. We then proceed to a quick demo of using the QISKit Python SDK provided by the IBM Q team to run experiments on a simulated (or real) quantum computer", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "This talk touches upon a topic that doesn't have any hard and fast prerequisites (apart from Python syntax, of course), but basic knowledge of the following topics will make things easier to grasp during the talk and later down the line: Some idea of what quantum physics is The concept of a quantum superposition of states Familiarity with linear algebra (not really for the talk, but will help later down the line)", - "Section": "Others", - "Speaker Info": "I'm a full-stack JS developer, Python enthusiast and Rust lover who revels in learning new technologies. I enjoy sharing my knowledge and the company of witty people", - "Speaker Links": " GitHub LinkedIn My Tech Blog on Medium", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ajmal Siddiqui (~ajmalsiddiqui)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-quantum-computing-with-the-qiskit-sdk~e9yDe/", - "title": "Introduction to Quantum Computing with the QISKit SDK" - }, - { - "Content URLs": "Will share slides link soon.. Key Takeaways from the talk: Why we decided to build our own machine learning platfrom from scratch How to build machine learning platform using python Lessons Learned while building machine learning services How to extend this platform by distributed computation engine like Spark and deep learning platform like tensorflow", - "Description": "Abstract The purpose of this talk is to describe how helpshift has leveraged python ecosystem to build a machine learning platform without using any third party framework, and how you can build one too. In particular, You can learn how to build the following components of machine learning platform using python from this talk. How we use python celery framework to distribute model building tasks\n to celery workers How models heavier in size can be served to prediction node in real time How to monitor model building tasks on celery worker Python data science stack in Helpshift - Numpy, Scipy, Scikit-learn, etc Python libraries/framework used - Celery, S3/Azure Storage, Bottle, etc Description Helpshift provides customer service platform to around 2000+ companies across various business domains like gaming, e-commerce, IoT, banking, entertainment, travel, hospitality, productivity apps and many more. Helpshift provides a suite of ML features that include auto ticket classification, FAQ suggestions to user query and other features. As each company using our platform has a different business domain, we build separate ML models for each of our customer and for each of feature. To handle thousands of models and CRUD operations on them in production, we needed highly scalable and reliable machine learning platform for model building and serving models. Possible solution was to use Spark or Tensorflow for model building. But these frameworks did not provide facility to store thousands of models, and serve those for prediction in production. We decided to use celery framework for distributing model building tasks to celery workers and use core python data science libraries to build models. Model building using celery worker Each Celery worker in ML platform is registered to one or more model building queues. Each type of task is associated with one celery queue. In real time, the backend server submits model building task to pre-defined celery queue. One of available celery worker picks the pending task, builds the model and pushes it to blob storage like s3/azure with new model version. Model management in s3/azure We have written python wrapper around s3/azure client library to provide all required CRUD operation on models in s3. CRUD operations are simple operations like get_model, put_model, update_model with some version. Serving models to prediction Nodes Model size ranges from 5 - 25 mb. To do predictions within 30 ms, we have to either load all models in memory or store them on local disk of each prediction nodes. We decided to store all the models on local disk as loading them in memory was not a scalable approach. The challenge here is, whenever a particular model is updated, it has to be copied on each prediction node. A python service on the prediction node takes care of syncing updated model from s3 to local disk. Prediction service Prediction service is gunicorn server which fetches model from local disk and does prediction on incoming requests. Monitoring model building task running on celery worker As there are always some jobs in celery queue waiting for celery worker, we built active monitoring service which tracks the status of each submitted task. Monitoring service decodes metrics from celery worker to find failure of task and time spent by each task in waiting/running state. For any task that crosses the threshold time for wait or run state, an alert is sent", - "Last Updated": "28 Jun, 2018", - "Prerequisites": " Basic knowledge of Python ecosystem Interested in building scalable machine learning platform", - "Section": "Data science", - "Speaker Info": "Hello, I am shyam shinde , actively developing machine learning platform at helpshift . I have diverse experience in developing backend systems, designing and developing system to handle big data. Developed production systems using Java, Clojure and Python. Currently, interested in deploying machine learning services at scale. As side projects, I learn machine learning concepts and try to implement them. Apart from that, I like trekking, reading books and watching movies", - "Speaker Links": "GitHub LinkedI", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Shyam Shinde (~shyam91)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-helpshift-built-machine-learning-platform-using-python-at-large-scale~e0mLa/", - "title": "How Helpshift built machine learning platform using Python at large scale" - }, - { - "Description": "SQL is a powerful tool. It is the simplest way to analyse a dataset. In recent times however unstructured data has started to get a lot of mileage. A lot of effort is spent in converting this to structured data. Some Statistics 80% of the data is unstructured As more people go online, it will lead to generation of more unstructured data. Currently the count sit at 3 billion people, so there is a lot of capacity for data overload in the coming days SQL is the world's easiest and most used programming language. The reason it is most used is because of its simplicity and power What I want to propose is a tool that will help analysts directly use SQL on text data. This will be more than just applying NLTK functions on the SQL text. It will involve the following components Data Structures ( similar to RDBMS etc) Parsing Ability to join etc Advantages The entire world of text data will be open for people with basic SQL skills to analyse. This will not just help in more productivity but help in seamless integration of business and technology Cross functional text data can be analysed easily Injection of populated knowledge graphs etc will ensure that new information gets added easily SQL will help reporting/logic storage very easy", - "Last Updated": "28 Jun, 2018", - "Prerequisites": " Python Jupyter SQL", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a data scientist at Morgan Stanley. I have been working in the analytics domain for the past 7 years\nI love applied machine learning and have been working in this capacity for the past 3 years", - "Speaker Links": "https://github.com/anantguptadbl https://www.recommendbot.in https://www.linkedin.com/in/guptaanant/ https://www.simplyanant.blogspot.co", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anant Gupta (~anant79)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/sql-on-text~egGke/", - "title": "SQL on Text" - }, - { - "Content URLs": "Slides will be uploaded soon", - "Description": "Almost all of us have used VLC, simply because it's so good at what it does. Reads multiple file formats, transcodes videos, makes basic filtering (brightness correction,etc) effortless, and so on. VLC uses libavcodec in the backend, which is just a way for it to access FFmpeg 's api. But have you ever wondered what makes VLC (via ffmpeg) so efficient? At this talk, we will take a look at what it takes to build a video transcoder in python as efficiently as FFmpeg . It will cover Basics of computer vision - What are images and videos really, how they are stored and managed How to handle videos in python using OpenCV, an open source computer vision library Basics of concurrency and parallelism in Python How to use parallelism effectively to handle videos", - "Last Updated": "29 Jun, 2018", - "Prerequisites": " Basic understanding of OpenCV and threads is preferable Working knowledge of Python", - "Section": "Core python and Standard library", - "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", - "Speaker Links": "R S Nikhil Krishna Personal Website Github Linkedin StackOverflow Lokesh Kumar T Github Linkedin StackOverflow", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "R S Nikhil Krishna (~r_s_nikhil_krishna)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-python-to-beat-vlc-and-ffmpeg-at-video-operations~ejkva/", - "title": "Using Python to beat VLC and FFmpeg at video operations" - }, - { - "Content URLs": "TB", - "Description": "Web crawling is hard. Large scale web crawling - which involves crawling millions of web pages in a month across 500 to 1000 websites, is even harder. Python comes with a number of libraries which allow you to do such crawling-at-scale but a lot of real-world issues have to be tackled to get the crawling infrastructure right Some of which are, Crawl rates - You need to strike the right balance here to make sure you don't crawl too aggressively but at the same time don't crawl too slow that the crawl finishes too late. Right Data - You need to make sure you crawl the right parts of the websites to get the right data you want. Dont get blocked! - Crawling from the same set of IP addresses will get you blocked across most modern websites. One needs some kind of rotating web proxy infrastructure to make sure that crawls can continue without getting kicked out. Capturing Errors - How to capture crawling errors so you can detect most issues and surface them up, while doing distributed crawling. Having nearly a decade of experience writing custom web-crawlers, the speakers have developed a set of custom tools to make crawling easy and painless. One of this is a tool to create a set of rotating web proxy caching nodes which use Squid and frontend by a HTTP load-balancer. The other one is a distributed crawler which uses Django as the middleware to distribute crawling across multiple crawler nodes while managing crawls at one place. In this talk, the author(s) discuss about one such tool they have created and have successfully used in multiple businesses and software companies over the last 3 years. The tool allows one to quickly and cheaply create an infrastructure of custom web proxy nodes which supports multiple VPS backends. Using this tool one can rune an industrial strength web crawling infrastructure with a set of rotating proxies of up to 50 nodes with a monthly cost of just under 300 $. The authors will talk about their experience and background creating and using the tool over the years, how it works with any web-crawler and the open source nature of the code which allows it to support different infrastructure backends and also the Squid configuration for the nodes which allows to hide the IP addresses behind the crawler. The other tool is a distrubuted web crawling monitor and management tool which uses Django to schedule and manage crawls across multiple nodes via Redis and simple HTTP APIs with the crawls performed via Scrapy derived crawlers", - "Last Updated": "29 Jun, 2018", - "Prerequisites": " Some knowledge of web crawling and or web scraping. Any knowledge of Scrapy and some experience using it is very handy Knowledge of HTTP proxy servers is a huge plus.", - "Section": "Developer tools and Automation", - "Speaker Info": "Anand B Pillai is a technology professional with 20 years of software development, design and architecture. He has worked in a number of companies over the years in fields ranging from Security, Search Engines, Large Scale Web Portals and Big Data. He is the founder of the Bangalore Python User's Group and the author of Software Architecture with Python (PacktPub, April 2017). Anand has a lot of experience in web-crawling having written the original Python web-crawler HarvestMan in 2005 and developing a number of custom crawlers for various startups solving various problems. Anand is currently VP of Engineering at the early stage Legal Tech startup, Klarity Law. Noufal Ibrahim is the CEO and Founder of Hamon Technologies at Calicut, Kerala. He was key to starting the very first PyCon India conference in 2009 and has since been involved in the conference closely throughout the years. Noufal was the keynote speaker of PyCon India 2017. Noufal has made a name not just by his Python community activities, but also by his creative Python introductory talks he has conducted in various universities and institutions in Kerala. He is also a professional trainer in Python and git. Both Noufal and Anand are Fellows of the Python Software Foundation (PSF)", - "Speaker Links": " Anand B Pillai - https://twitter.com/skeptichacker Noufal Ibrahim - https://twitter.com/noufalibrahim , http://hamon.in/", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anand B Pillai (~pythonhacker)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/large-scale-web-crawling-using-python~bkl6d/", - "title": "Large scale web crawling using Python" - }, - { - "Content URLs": "Python 3.7 Release note", - "Description": "In this talk, we will deep dive into features of Python3.7 breakpoint() Data Classes Customization of Module Attributes Typing Enhancements Timing Precision Order of Dictionaries \u201casync\u201d and \u201cawait\u201d Are Keywords \u201casyncio\u201d Face Lift Context Variables importlib.resources Developer Tricks Optimizations So, Should I Upgrade?", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Core python and its internal", - "Section": "Core python and Standard library", - "Speaker Info": "Bhavani Ravi - Software Engineer - Orangescape Tech Enthusiast - Django & Chatbot specialist Mentor/Speaker Build2learn , Chennai Geeks", - "Speaker Links": "http://bhavaniravi.com twitter.com/@geeky_bhavani Chatbot Workshop - Forge AI Conclave Chatbot workshop - PyDelh", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Bhavani Ravi (~bhavaniravi)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/whats-new-in-python37~elmMa/", - "title": "What's new in Python3.7" - }, - { - "Description": "Users leave; but their credentials usually stick around. And this leaves a security hole to be filled. Though a lot of services integrate with GSuite but tools/third-party services/ssh credentials - places where individual or shared user accounts are managed out of band - remain a security risk. In the spirit of automation and predictability, we have been working towards a \u201c Centralized User management solution \u201d and automating everythin", - "Last Updated": "29 Jun, 2018", - "Section": "Networking and Security", - "Speaker Info": "I am working as an Information Security Engineer at Grofers. Earlier I was with Makemytrip and Expedia, and have a total of 3 years experience in the InfoSec field. I'm also a part time bugbounty hunter - acknowledged by various MNCs and some top companies of India. I am also an active blogger on Medium where I write about interesting vulnerabilities that I find on my bugbounty journeys. Some of the articles have been published in various Security magazines and newsletters like Hakin9, Bugcrowd. Managing application security, performing penetration testing, hardening network and infrastructure, and automating security tasks to reduce manual effort are some of the things I take care of on a daily basis", - "Speaker Links": "https://medium.com/@logicbomb_1 https://twitter.com/@logicbomb_", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Avinash Jain (~avinash86)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/centralized-user-management~eno7a/", - "title": "Centralized User Management" - }, - { - "Content URLs": "Contents related to the talk will be added later", - "Description": "During my M.Tech. programme at IIT Guwahati, I observed that researchers in both industry and academia work with testbeds , both real and virtual, for making advancements in Computer Science , whether it is in algorithms, networking protocols or data science by running exhaustive experiments. I realised that Python, being a very versatile language , can be used to do everything related to experimental research and analysis , without requiring the usage of any other scripting language. Based on my experiences, I am presenting a talk to explain how to build automated testbed experiments, data collection and analysis with Python and a few libraries, avoiding big and bulky frameworks as much as possible . My talk is structured as follows: Building a testbed for computing and networking experiments Using Python and paramiko to provison entities (PCs, smartphones, Raspberry Pis, routers, switches, etc.) in the testbed Running tests on the entities with subprocess and paramiko Collecting log files and other trace data from testbed entities Parsing log files and trace information to collect statistics with basic text processing and regex and storing them in appropriate Python data structures like lists, tuples and dictionaries for easy access Analysing collected statistics with Python math and generating reports Visualizing graphs from statistics with python-gnuplot or matplotlib I hope that after attending my talk, you will be able to automate your testbed experiments to the extent of spending less time on experimentation and data collection and more time on actual research and publishing papers", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "There are minimal prerequisities for my talk. You need to have knowledge of the following: Basic algorithms and data structures Computer networks, especially IP addressing Python basics Also you need to have: The willingness to learn and experiment", - "Section": "Developer tools and Automation", - "Speaker Info": "Hello everyone! I am Sunit Kumar Nandi , a Trainee Teacher at National Institute of Technology, Arunachal Pradesh. I have completed my M.Tech. at IIT Guwahati this year and am also enrolling for Ph.D. I am deeply interested in computer networking, telecommunications, operating systems and distributed systems design . I use Python for most of my daily work involving a great deal of experimentation. Apart from that I contribute to SuperX OS , a Linux distribution with KDE, based out of Assam, India. I love BSD and Linux based systems and have been involved with them since my childhood. As a result, I have had 14 years of experience with managing Linux servers, networking equipment and designing automated systems in the simplest way possible. In my free time, I spend my efforts running Techno FAQ , an e-magazine for science, technology, education and business", - "Speaker Links": "You can follow me on: Facebook Twitter My open source contributions: SuperX OS Packages I maintain for Arch Linux: utserver quassel-core-static Other projects I run: Techno FAQ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sunit Kumar Nandi (~sunitknandi)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-testbed-experiments-data-collection-and-visualization-with-python~bo0Xd/", - "title": "Automating testbed experiments, data collection and visualization with Python" - }, - { - "Content URLs": "http://openaccess.thecvf.com/content_ICCV_2017/papers/Zhang_StackGAN_Text_to_ICCV_2017_paper.pdf https://pytorch.org/ Slides to be uploaded soon", - "Description": " The workshop is intended to introduce, explore and get a hands on experience on one of the most interesting application of GENERATIVE ADVERSARIAL NETWORKS which is - given the description of an image, the GAN model generates an image according to that description. The workshop is to be divided in two parts: \n1. Giving a hands on of using word embeddings to encapsulate the textual information and basics of how to train a vanilla GAN.\n2. Combining the word embedding and training a 2 stage stacked GAN to generate relevant Image ( We will be providing with pre-trained models as training takes a lot of time ) The workshop would then aim to go over the plausible applications that it could have.\nThe first part of the workshop will be as follows: We would be teaching basics aspects of NLP i.e word embeddings with hands on experience of python libraries NLTK etc. We would be then moving on to the next part where we will teach the basics of how to train a vanilla GAN on their laptops using Pytorch followed by a simple application. We will be providing the audience with Jupyter notebooks with skeleton code and the remaining code will be written on the spot.\nAim of the teaching the training procedure is to get the audience a hang of what parameters to keep in mind while training a Neural Network. The second part of the workshop will be as follows We will be training the Gan using the word embeddings to get a rough Image representation followed by another GAN ( stacked one after other ) to get a full resolution image ( details given in Paper ) We will be providing the trained model of GAN as it requires a lot of time to train the GAN. We will be providing the Jupyter Notebooks giving the architecture and will be writing some parts of the Stacked GAN\u2019s on the spot. We will be discussing the possible applications of GAN\u2019s in both research and industry.", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Basics of NLP ( word embedding ), Basics of Neural Network, Basics of Python numpy and Pytorch", - "Section": "Others", - "Speaker Info": "I ( Sairam ) am currently a research associate at Center for Visual Information Technology, IIIT Hyderabad. I graduated from Electronics Engineering from IIT BHU last year. My experience with Computer Vision is of 4 years, with varied internships at CWNU, South Korea working on face recognition, NTU Singapore working on Maritime vessel detection to Crowd modelling. I\u2019m currently working on Cancer detection from slide images of cancerous tissues.I have been the lead of many workshops and tutorials conducted at my college, for acquainting freshmen with the basics of Vision and ML. Zeeshan is currently a research fellow at Center for Visual Information Technology, IIIT Hyderabad. He has graduated in Electrical Engineering from VJTI, Mumbai. He has an experience of 2 years in developing trading systems at Citi. Currently he is working on gradient estimation for stochastic neural networks", - "Speaker Links": "My LinkedIn profile can be viewed at: https://www.linkedin.com/in/sairamtabibu/ Zeeshan's Profile: https://www.linkedin.com/in/zeeshan-ashraf-508587137", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Sairam tabibu (~sairam)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/synthesising-images-from-text-using-generative-adversarial-networks~epqVa/", - "title": "Synthesising Images from text using Generative Adversarial Networks" - }, - { - "Description": "A data scientist's job is usually to train a model often in the form of a jupyter notebook. However, to take this model to production takes different skills, a significant engineering effort and a lot of hidden technical debt accumulated over time. Grace, a platform agnostic deployment framework addresses this problem (thus reducing the machine learning engineering effort) by acting as an orchestration tool to deploy deep learning models in production environment leveraging tensorflow serving , docker and kubernetes. Any deep learning model to be deployed is configurable through a json spec containing input, output, model weights etc,. Other services essential to maintenance like deep-dive monitoring tools, load testing tools, structured centralized logging are provided out of the box", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "python, basics of machine learning/ deep learnin", - "Section": "Developer tools and Automation", - "Speaker Info": "Venkat Karun is a full stack generalist and polyglot with 15 years of experience building high performance, distributed systems including a decade at Google. He enjoys reading up on functional programming and lambda calculus and tinkering with ev3dev and the lego Python ecosystem in his spare time. He is currently working as Chief Architect at NicheAI pvt ltd. Venkatesh Mondi, an aerospace engineer by education worked in ISRO before finding his love for programming and machine learning. He worked as a software programmer in various platforms before co-founding NicheAI pvt ltd . He has been working on a variety of production grade computer vision solutions since it's inception. He can be found experimenting with gadgets, software, mathematics in his free time", - "Speaker Links": "Venkat Karun Venkatesh Mond", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Amith Reddy (~velutha)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/grace-a-deployment-tool-for-deep-learning-models~bqrpd/", - "title": "grace - a deployment tool for deep learning models" - }, - { - "Content URLs": "https://www.dowhatucant.com/pyconindia18", - "Description": "While introducing people to Python metaclasses I realized that sometimes the big problem of the most powerful Python features is that programmers do not perceive how they may simplify their usual tasks. Therefore, features like metaclasses are considered a fancy but rather unuseful addition to a standard OOP language, instead of a real game changer. This talk wants to show how to use metaclasses and decorators to create a powerful class that can be inherited and customized by easily adding decorated methods", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "An experience working with and developing python programs and a general understanding of the python syntax", - "Section": "Core python and Standard library", - "Speaker Info": "I am just an average guy who got into programming and fell in love with it. 3rd year undergrad at IIT Dharwad and a Google Summer of Code 2018 student with coal", - "Speaker Links": "https://github.com/ishanSrt https://gitlab.com/ishanSrt http://dowhatucant.com/gsoc_archive.htm", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "ishan srivastava (~ishan38)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/metaclasses-and-decorators-a-match-made-in-space~ervpe/", - "title": "Metaclasses and decorators: a match made in space" - }, - { - "Content URLs": "Will be updated soon", - "Description": "It seems like every tech company is slinging around buzzwords like \u201cbig data,\u201d \u201cartificial intelligence,\u201d and \u201cmachine learning\u201d. Machine learning is able to make sense of digital data at a much faster rate than any human is capable of doing and hence choosing the application of ML-Recommendation Systems, tends to be a decision of priorities. These systems are personalizing our web experience, telling us what to buy (Amazon), which movies to watch (Netflix), whom to be friends with (Facebook), which songs to listen (Spotify) etc.\nIn this talk I\u2019ll explain the amount of work going behind this, diving into the mechanism of one such way to build these recommendation systems. OUTCOME After this talk, the audience would be able to understand the actual working of these systems. It involves knowledge of different types of recommendation systems, algorithms used, evaluation of the systems generated, working of deep recommendations \u2013 at last eventually building one(model) from scratch.The talk would answer the queries about the domains of the systems created- media, e-commerce, travel & real estate , education , job-boards, etc.- 'how AI has revolutionized e-commerce.' -giving a clear insights to mechanisms responsible for the same. AGENDA Introduction to recommendation systems. Domains of recommendation systems. Categorising algorithms and their evaluations Describing the python libraries used. Building a music recommendation system using the libraries \u2013 popularity based model & personalised collaborative filtering model Performance analysis of both models & real world instances of recommendation systems. Q & A Session", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Basic knowledge of machine learning & love for pytho", - "Section": "Data science", - "Speaker Info": "Aakanksha Chouhan Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence, occasionally working on blockchain projects. I\u2019m a member of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, Blockchains and Computational Biology. I also regularly participate and give talks in paper-reading sessions and meetups like PyData Amaravati ", - "Speaker Links": "Connect with me on linkedin Twitter email : akankshachouhan98@gmail.co", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "AAKANKSHA_CHOUHAN", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-dive-machine-learning-and-media-building-your-own-recommendation-system-from-scratch~avz5a/", - "title": "Deep Dive : machine learning and media -building your own recommendation system from scratch" - }, - { - "Content URLs": "Tensorflow for poets Fast Image classification using Bottlenecks Tensorflow Debugge", - "Description": "Accelerating Transfer Learning using Effective Caching Technique Transfer Learning is something which has become a routine today. Neural Networks have a lot of parameters (millions of them) which are trained iteratively in a data-driven fashion. With these many parameters come huge representational power (ability to model hyper dimensional complex functions). In cases where we train a custom classifier (say a CNN), we might not be having that much data so the network can easily overfit when trained from scratch. So here comes transfer learning, use the previously accumulated knowledge (in form of weights in neural nets) to learn our problem. In case of fine-tuning also we will be training final layers of the network only. (If you are not aware don't worry this will be covered). Huge networks take significant time train completely. To reduce this time comes methods of effective caching or informally called Training with Bottlenecks This method though is easy to implement, can give very good results. ResNet50 which took 45 sec for an epoch to train using normal transfer learning procedure, now takes 8 sec per epoch. Which is almost 6x speed up! * *Trained on Nvidia GeForce GTX 1050, i5-7300HQ Processor (5 category flower dataset) Learning Outcome Why is Computer Vision difficult problem? The role of Deep Learning in Computer Vision Deep Convolutional Networks for Image recognition Different Convolutional Architectures for Image recognition Difficulty in Optimizing large neural nets and hints for effective training Uses of pretrained models and basis of transfer learning What is Transfer Learning and why is it important? Different methods of Transfer Learning Accelerating training a neural network by caching the non-trainable model's output (Hands on Implementation in keras ) Analysing the speedups and potential limitations in this procedure How to debug Tensorflow Program? This presentation is not about how to debug DL model (Example DL model is not fitting well). Its about how to debug your program in programming perspective . Debugging a tensorflow program can be difficult due to many reasons out of which some are, The concept of computational graph construction Abstraction of tf.Session() many more. So we will introduce commonly used tensorflow debugging tools like (main ones are listed) Tensorboard Tensorflow Debugger tfdbg ", - "Last Updated": "29 Jun, 2018", - "Prerequisites": " Basic understanding of Deep Learning , Tensorflow and keras Working knowledge of python ", - "Section": "Data science", - "Speaker Info": "R S Nikhil Krishna Nikhil is a final year student at IIT Madras. He currently leads the Computer Vision and AI team at Detect Technologies and has headed the CVI group at CFI, IIT Madras in the past. In the past, He has worked on semi-autonomous tumour detection for automated brain surgery at the Division of Remote Handling and Robotics, BARC and on importance sampling for accelerated gradient optimization methods applied to Deep Learning at EPFL, Switzerland. His love for python started about 4 years back, with a multitude of computer vision projects like QR code recognition, facial expression identification, etc. Lokesh Kumar T Lokesh is a 3rd-year student at IIT Madras. He currently co-heads the CVI group, CFI. He uses Python for Computer Vision, Deep Learning, and Language Analysis. In DeTect technologies, he has worked on automating the chimney and stack inspections using Computer Vision and on on-Board vision-based processing for drones. His interest in python began during his stay at IIT Madras, from institute courses to CVI projects like face recognition, hand gesture control of bots, et", - "Speaker Links": "R S Nikhil Krishna Personal Website GitHub LinkedIn StackOverflow Lokesh Kumar T GitHub LinkedIn StackOverflow ", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Lokesh Kumar T (~tlokeshkumar)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/accelerating-transfer-learning-using-effective-caching-and-how-to-debug-tensorflow-programs~dwA8a/", - "title": "Accelerating Transfer learning using Effective Caching and How to Debug TensorFlow programs" - }, - { - "Content URLs": "Will provide the links soon", - "Description": "Apache Spark is an open-source Distributed Computational Framework. It sits on top of Cluster Manager and Distributed Storage. Spark program runs in driver and utilizes Cluster manager to run tasks. Apache Spark has become the most preferred option in the field of Machine Learning due to its faster processing utilizing in-memory computations with Resilient Distributed Dataset (RDD). With the Python being the most preferred language for Machine Learning and Deep Learning tasks, PySpark has become most important weapon in the arsenal of Data Scientists/Data Engineers. PySpark is Python API to the Scala Core of Spark allowing Python programmers access to run Distributed jobs in Spark. This session will introduce you Spark architecture and show how to use PySpark to run Machine Learning tasks on Spark", - "Last Updated": "29 Jun, 2018", - "Prerequisites": "Knowledge of Machine Learning Knowledge of Pytho", - "Section": "Data science", - "Speaker Info": "Shashi Jeevan is an author, trainer, architect with over two decades of experience in the software industry working in various domains including Finance, Digital Signage, Rich Media Management, etc. He loves to master new technologies and share his learnings. He regularly presents and organizes free technical sessions through the Hyderabad Software Architects meetup group which he founded in 2015", - "Speaker Links": "https://www.linkedin.com/in/shashijeevan/ https://shashijeevan.com https://github.com/shashijeeva", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Shashijeevan M.P. (~shashijeevan)", - "created_on": "29 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-pyspark~egGGe/", - "title": "Introduction to PySpark" - }, - { - "Content URLs": "Slides Deck: https://slides.com/ineil77/deck/fullscreen References Imbalanced Learn Python Library: http://contrib.scikit-learn.org/imbalanced-learn/stable/index.htm", - "Description": "Classification algorithms are known to under perform when faced with data that is heavily skewed towards one class as most of them are designed to work under assumptions of uniform class distribution. Another such caveat is the assumption of uniform cost of misclassification of all samples. For instance in a transaction fraud detection setting, the fraudulent transactions are vastly outnumbered by the genuine ones. Also the cost of wrongly classifying a fraudulent transaction as a genuine one far outstrips the inconvenience caused by flagging a benign transaction as a malicious one. This talk aims to cover the various approaches used to cope with this commonly faced problem: Oversampling Methods Undersampling Methods Synthetic Data Generation Cost Sensitive Learning Key takeaways from this talk: How imbalanced data sets undermine classifier performance How to eliminate class imbalance The advantages and disadvantages of over/under sampling and synthetic data generation Robust evaluation metrics insensitive to class imbalance", - "Last Updated": "30 Jun, 2018", - "Prerequisites": " Basic Python Understanding of basic performance evaluation metrics", - "Section": "Data science", - "Speaker Info": "I'm Indraneil Paul, a final year Computer Science student at IIIT Hyderabad. I have been involved in machine learning, computer vision and mathematical optimisation for the best part of the past three years due to my research work. I was previously working in the Computer Vision lab on an autonomous driving project and am currently working on applying graph based machine learning models to social networks. I was also a Google Summer of Code '17 student under electric vehicle startup Green Navigation (now nav-e)", - "Speaker Links": "Github: https://github.com/iNeil7", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "iNeil77", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-comprehensive-overview-of-dealing-with-imbalanced-datasets-in-python~ejkPa/", - "title": "A Comprehensive Overview of dealing with Imbalanced Datasets in Python" - }, - { - "Content URLs": "CHAOS", - "Description": "Software development projects, in particular the open source ones, heavily rely on the use of tools such as Git, GItHub and mailing lists to support, coordinate and promote their development activities. \nDespite their paramount value, they contribute to fragment the project data, thus hindering the work of both practitioners and researchers to collect, clean, link and analyse this data to derive insightful analytics about the software project. In this context, the Community Health Analytics and Open Source Software (CHAOSS) project, under the umbrella of the Linux Foundation is currently working towards analysing open source communities and how they function. This talk presents GrimoireLab, a Python-based open source platform, part of CHAOSS. GrimoireLab allows us to seamlessly analyse open source projects, measuring their activities, processes and communities.\nWe will discover the tools composing GrimoireLab and learn how to use them. At the end of the talk we will know how to: Collect data in an automatic and incremental way from almost any tool related with contributing to open source development (e.g., source code management, issue tracking systems, forums), Enrich the collected data with additional information like contributors affiliation and geographical data as well as manage and unify identities (e.g., emails, username) belonging to the same contributor. Visualize your project data through interactive dashboards and reports. I will also touch upon my experience as a Google Summer of Code-18 student under CHAOSS and how you can participate in the community and contribute to the project", - "Last Updated": "30 Jun, 2018", - "Prerequisites": " Willingness to learn about new tools Interest in Open Source Development [A must] A good understanding of how APIs work Knowledge about how the command line works Basics about how Elasticsearch works is appreciated but not necessary", - "Section": "Data science", - "Speaker Info": "Hey!! I am Pranjal Aswani. I recently finished my engineering from TCET, Mumbai . I am an Open Source enthusiast and a Python Dev. As you might have guessed from my Proposal, I am working with CHAOSS under GSoC-18. I have a high interest in Data Analysis and this is going to be my first PyCon talk! (if selected :P) If you are a potential employer or just want to talk, please feel free to visit my website for more information! (link below", - "Speaker Links": " aswanipranjal.github.io blog GitHub LinkedIn Twitter", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Pranjal Aswani (~pranjal2)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-is-your-open-source-project-doing~bklNd/", - "title": "How is your Open Source project doing?" - }, - { - "Content URLs": "Info about selenium: http://selenium-python.readthedocs.io/getting-started.html Project repo: https://github.com/pareksha/WhatsApp-Automatio", - "Description": "I was fed up with the daily 'Good Morning' messages I had to send to my crazy not so important friends as well as waking up till midnight just to send 'Happy Birthday' messages. I decided to automate all this stuff and I found 'Selenium' to be just fit for the purpose. Selenium is simply a web browser automation tool but what you can do with it is totally up to your imagination. This talk will be about the numerous crazy ideas you can implement using Selenium including automating WhatsApp messaging like wishing birthdays at midnight and sending bulk messages on one click. The talk will also include how quickly and easily these things can be implemented using Selenium", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Knowledge regarding basic python syntax (or of any other programming language)", - "Section": "Developer tools and Automation", - "Speaker Info": "Currently, I am a Google Summer of Code intern with coala . I love coding and python is my favorite programming language. Regarding college, I am a CSE 2nd year undergrad at UIET, Panjab University", - "Speaker Links": "GitHub: https://github.com/pareksha GitLab: https://gitlab.com/pareksha GSoC blog: https://pareksha.wordpress.com/ LinkedIn: https://linkedin.com/in/pareksha", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Pareksha Manchanda (~pareksha)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automating-messaging-using-selenium~bmn9d/", - "title": "Automating messaging using Selenium" - }, - { - "Content URLs": "Will update shortly", - "Description": "The talk aims to provide an understanding of popular tools at disposal for writing efficient tests using pytest. This intermediate to advanced talk will do a walk through of all components involved in writing production-ready test cases using fixtures, auto-fixtures, factories, faker, mocker etc in a django application. Once the tests look good, they will be integrated with Jenkins (Blue Ocean) where a coverage report of tests will be displayed. Continuous Integration of code on VCS (GitHub) with Jenkins will provide test-runs on every code push to remote repository. This will arm the audience with a robust test suite which is ready to be deployed", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Familiarity with python web-framework (any)", - "Section": "Developer tools and Automation", - "Speaker Info": "I am Aditi Bhatnagar, a senior software developer at a start-up in Bangalore. I have industry experience of 6 years and find myself constantly in need of writing well-tested code. Robust integration tests have often protected me from accidental errors seeping in production", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Aditi Bhatnagar (~aditi95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/testing-with-pytest-and-continuous-integration-with-jenkins~enoWa/", - "title": "Testing with pytest and continuous integration with Jenkins" - }, - { - "Content URLs": "Will be updated soon", - "Description": "In this talk the enthusiasts will get to see the integration of Django, DRF, Django Channels and Angular to create a modern Real-time web App Goal:\nTo clear the clouds around creating Modern WebApps Using Djang", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Python\nDjango\nDRF\nAngula", - "Section": "Web development", - "Speaker Info": "Hello I am Jaipreet Singh. I am a developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", - "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Jaipreet Singh (~Jaipreet95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-modern-real-time-apps-with-django-drf-django-channels-and-angular~bo0Bd/", - "title": "Building Modern Real-time Apps with Django, DRF, Django Channels and Angular" - }, - { - "Content URLs": "Will be updated soon", - "Description": "Objective To explain the various design patterns that Django programmers use and prevent reinventing the wheel in each of your projects. Takeaways of this talk would be to know the answers to: What are the current best practices in Django and what are not?\nWhich are most common and useful design patterns?\nHow to identify and implement these patterns? Description Design Patterns are patterns we see and code in almost every Django projects. They are scenarios for which we wished had a canonical and elegant solution. Based on the seminal work on design patterns in the Gang of Four book and Martin Fowler's book, the talk takes you through several well known design patterns to improve your Django code. It might also cover several new patterns in web application development that you can apply to other frameworks", - "Last Updated": "30 Jun, 2018", - "Prerequisites": "Basic knowledge of OOPS and Python\nShould have completed atleast one Django Projec", - "Section": "Core python and Standard library", - "Speaker Info": "Hello I am Jaipreet Singh. I am a developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", - "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Jaipreet Singh (~Jaipreet95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/design-patterns-in-python-and-django~epqpa/", - "title": "Design Patterns in python and Django" - }, - { - "Content URLs": "Will be updated soon", - "Description": "If things work out as you\u2019ve envisioned, there will be a time in your webapp\u2019s lifecycle when it\u2019s serving a large number of users. By the time things get to this point, it\u2019s ideal if you\u2019ve architected your webapp to both scale gracefully to meet this load, and also be resilient to arbitrary failures of underlying compute resources. This talk is about how you can use Docker containers and Kubernetes to help your Django webapp achieve these architectural goals. While it meanders a bit through theory and philosophy, it does work up to a concrete example to help solidify concepts", - "Last Updated": "30 Jun, 2018", - "Prerequisites": " Basics of Linux Familiarity with Docker and docker files Kubernetes(optional)", - "Section": "Core python and Standard library", - "Speaker Info": "Hello I am Jaipreet Singh. I am a Sofware developer with 1 year of professional experience and +3 years of freelancing experience. I have a Bachelor's degree in computer science and I am currently working as a Software developer in Falkonry Pvt. Ltd., where I work on exciting new domain of Operational Machine Learning. I am very passionate about creating cutting edge products from scratch and for DevOps", - "Speaker Links": "Github: https://github.com/Jaipreet95 Facebook: https://www.facebook.com/jprts.singh Email: jaipreet.singh95@outlook.co", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Jaipreet Singh (~Jaipreet95)", - "created_on": "30 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/maintaining-scalability-of-django-powered-web-app-by-using-containers-and-kubernetes~bqr0d/", - "title": "Maintaining scalability of Django powered web App by using containers and Kubernetes" - }, - { - "Content URLs": "http://pyflyby.or", - "Description": "Python is a wonderful programming language because of its lack of boilerplate. However, one remaining area of boilerplate is import statements. When writing a python program, it's tedious to go back and forth to the top of the file to add and remove import statements. When using Python interactively, it's tedious to type import statements. I have created a tool called Pyflyby to automate imports. Pyflyby has two killer features. (1) With one button, Pyflyby automatically modifies your Python code to add necessary imports and remove unnecessary imports. You can integrate into your editor or use the command-line tool. (2) Pyflyby enhances IPython/Jupyter to automatically import symbols on-demand. I started Pyflyby in 2011 as a side project. It has become wildly popular within my firm; most developers at my firm swear by it. I recently open sourced Pyflyby to make it available to the community. In this talk, I will present how to use Pyflyby, how it works, and how it has changed Python development at my firm", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "Non", - "Section": "Developer tools and Automation", - "Speaker Info": "I have been a developer in the asset management division of the D. E. Shaw group since 2009. I also manage the Python infrastructure group at the firm", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Karl Chen (~quarl)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/pyflyby-automatic-imports-for-python~erv4e/", - "title": "Pyflyby: Automatic imports for Python" - }, - { - "Content URLs": "Github: https://github.com/arijitsaha/FloodRis", - "Description": "Catastrophic floods had a deep impact on the early human psyche resulting in a potpourri of great flood stories ingrained in the mythology of early human civilisations spread across the globe. Despite all the human progress floods can still cause massive property damages, economic losses and casualty. Several major cities and towns in India reported a series of devastating urban floods in recent times, and the resulting human and financial loss makes study of models that can identify the flood risk of an area extremely relevant. This talk focuses on geo-spatial analytics and describes multiple techniques that can be used to assess the flood inundation risk of a geographical area. The techniques use freely available data captured by different satellites. The talk will demonstrate how we can use python libraries and Digital Elevation Models (DEM) to analyse a terrain with respect to it's elevation. The talk also also focus on how to build a first order flood fill model to identify flood inundation risks of a geographical area due to overflow of water from a nearby water body, and due to heavy rains. Some key take-aways from this talk are An introduction to various types of Remote Sensing data with extensive focus on Digital Elevation Models (DEM) Various types of public data sources available for Geospatial Analytics Working with translator library for raster and vector geospatial data like GDAL How to use other geospatial libraries like PyDEM for topographic analysis Descriptive Analytics using Python packages like numpy, pandas, scikit-learn, seaborn, matplotlib etc.", - "Last Updated": "01 Jul, 2018", - "Prerequisites": " Basic / Intermediate knowledge of Python Interest in Geospatial Analytics using Python or curiosity in application of analytics for catastrophic risk management", - "Section": "Data science", - "Speaker Info": "Arijit Saha Arijit Saha is a data professional with over sixteen years of industry work experience in architecting, designing & developing large-scale data products, platforms & solutions for both big & medium size enterprises. Currently he is busy engineering Enterprise AI data platform & products for some of the most well-known global enterprises. He is an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Big Data Analytics, Geospatial Analytics and application of Artificial Intelligence in Enterprises. LinkedIn: https://www.linkedin.com/in/arijitsaha/ Atul Singh Atul Singh is a data science enthusiast with over sixteen years of software industry work experience in product development, research, and innovation. He has a PhD in Computer Science. He has nine granted US patents, eleven pending US patent applications, and over fifteen research publications in various international forums. He is also an alumnus of the Business Analytics and Intelligence course from IIM Bangalore. His interests include Natural Language Processing (NLP), Geospatial Analytics, and Reinforcement Learning. LinkedIn: https://www.linkedin.com/in/atulsinghphd", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "arijit.saha", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/managing-flood-risk-in-this-modern-age-an-introduction-to-geospatial-analytics-with-python~avz0a/", - "title": "Managing flood risk in this modern age - An Introduction to Geospatial Analytics with Python" - }, - { - "Description": "Why a JavaScript talk at PyCon? JavaScript has become a crucial view for Pythonic data analysis via Jupyter Notebooks. Jupyter widgets have taken python data from read-only to a rich, interactive experience. This talk will focus on providing a delightful and consistent user experience across all platforms. Specifically, we\u2019ll talk about why we should want Jupyter to reuse our JavaScript ecosystem and how we achieve this. Finally, we\u2019ll end with a vision for enabling data to render similarly regardless of whether you view it in a Jupyter notebook, email, or a flask/nodejs powered website", - "Last Updated": "28 Jun, 2018", - "Prerequisites": "Familiarly with Jupyter Noteboo", - "Section": "Core python and Standard library", - "Speaker Info": "I am a developer for the JavaScript team at the D. E. Shaw group. One of our core principles is that users come first; we are hyper focused on improving the user experience for developers, technical users, and non-technical users of everything from intranet sites to the interactive python environment. We aim to delight", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marc Udoff (~mlucool)", - "created_on": "28 Jun, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/an-enterprise-javascript-ecosystem~b6vRb/", - "title": "An Enterprise JavaScript Ecosystem" - }, - { - "Content URLs": "I will share presentation & relevant code soon to github", - "Description": "How I was able to scale training workloads which gave results in 3 days to experiments in 3 hrs! \nOfcourse it came with a lot of pain, but distributing the model across multiple nodes using a centralised control framework was totally worh it. A simple RESTFul framework for conducting Tensorflow training and evaluation \u2013 \nThis talk will help you: get the best results for any Tensorflow task using a distributed deployment scale your expirments to the next level run on multiple nodes to utilize faster and parallel training/inference systems What the talk will cover: Small intro to DeepLearning with Tensorflow - What it is? Why is it diffirent from other python libraries? Conducting an image segmentation task in Tensorflow How do you make it run on REAL data? ( Train + explore ) x N How to setup the an experiment for the best results in the least time", - "Last Updated": "01 Jul, 2018", - "Prerequisites": " Understanding of python object oriented programming Knowledge of RESTFul APIs Basic understanding of machine learning", - "Section": "Data science", - "Speaker Info": "Kshitij Agrawal I am a strong believer of using technology to solve real problems. With a deep specialization in computer vision, I have developed and deployed a wide array of computer vision applications on hardware as well as cloud. A deep interest in reliable large scale computer vision led me to work at solving challenges around autonomous driving at Intel India. Post my MS from IIIT-Hyd, I was working at Tonbo Imaging, a leader in thermal imaging devices for the military", - "Speaker Links": " LinkedIn Udacity Webinar on Computer Vision", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "kagrwl", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-zen-of-deep-learning-managing-tensorflow-models-using-simple-resttful-frameworks~dwA1a/", - "title": "The Zen of Deep Learning \u2013 Managing Tensorflow Models using simple RESTtful frameworks" - }, - { - "Description": "As we move towards microservices and distributed architectures it is important to ensure your tooling acts as an effective communication between different teams. This talk is not only about building better applications but improving business delivery through better visibility into your application through the elastic stack. The Basic structure of the talk shall be: Understanding logging and exceptions. What to log and what not to log? Building pipelines to ship logs for your distributed application. Understanding ElastAlert alerting rules. Real-world examples and mechanism of how you can tie in ElastAlert with your IT operations.", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "Some understanding of building business applications for any stack should help", - "Section": "Developer tools and Automation", - "Speaker Info": "Amit Sethi, is a Software Developer at E2E networks. A cloud computing company out of Delhi. His day job involves writing code for distributed applications running using API's and Infrastructures. Some of which he owns and some which he does not. He is passionate about understanding how to deliver a better customer experience of application he writes while ensuring sanity for himself and fellow colleagues", - "Speaker Links": "twitter linkedi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Amit Singh Sethi (~dusual)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/better-visibility-into-your-distributed-application-through-elastalert~axB3d/", - "title": "Better visibility into your distributed application through ElastAlert" - }, - { - "Description": "All web developers who use python have come across django. It is both hated and loved to varying degrees. But what about day 500. What happens when you have a team of 15 people developing and 5 teams talking to the django application. What kind of baggage does django bring for day 500th. What kind of things it solves for the day 500. Some of the points we shall talk about? What kind questions does the day 500 bring? Admin. Your friend and your foe. Managing your database changes Configuration Management Django in a muti-skill, multi-team environment. Django in a distributed environment. Building visibility in your django app.", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "An understanding of django and web development basics should be helpfu", - "Section": "Web development", - "Speaker Info": "Amit Sethi, is a Software Developer at E2E networks. He has had his own love-hate relationship with django. Apart from that he has worked with frameworks like pyramid, tornado and flask with python. And also used rails and beego with ruby and golang. He is an opinionated developer with love for elegant API'", - "Speaker Links": "twitter linkedi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Amit Singh Sethi (~dusual)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-on-day-500~dyDEb/", - "title": "Django on day 500" - }, - { - "Content URLs": "To be updated soo", - "Description": "I wrote a few lines of code to build a web application using Flask back in University. Everyone found it so good, it was like a forest fire. I could never have estimated that a few lines of code can help thousands of people with stuff they do every day. In my case, I designed and developed a website 'Papercop' which did the simple job of downloading all the relevant question papers from the university's portal and all the student had to do was enter their roll number. No Ads. No signups. No logins. One input. One output. And everyone out there loved it. Thousands of students used the site before every examination I'd like to take the audience through the ups and downs of seeing how a simple idea they keep thinking of, can be brought to life using Python while talking about best practices and growth hacks", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "Non", - "Section": "Web development", - "Speaker Info": "I am an IIT Kharagpur graduate(2017) who spent over 4 years coding in Python. Worked with all styles of python from website development using Django and Flask to scientific computing using numpy and scikit-learn to web-scraping using Selenium. It's been a wonderful journey all along and I'm now looking forward to bring as many people on board as I can to experience what I've experienced. I am also the founder of Papercop, an examination preparation portal for the students of IIT Kharagpur which has about 70k+ hits. I am a very passionate speedcuber( Can solve the rubiks cube in about 10s odd). Won plenty of medals in speedcubing competitions across the country. I now work as an analyst with American Express. Speaker at Pycon India '17 and invited to Pycon Italy'1", - "Speaker Links": "Links to previous talks: Pycon India'17 Twitter Linkedi", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Anuj Menta (~anujmenta)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/can-a-few-lines-of-python-help-thousands-of-people~azEZe/", - "title": "Can a few lines of Python help thousands of people?" - }, - { - "Content URLs": "To be updated soon", - "Description": "We have always been taught that the earlier you book a flight, the cheaper it is. What if I said it isn't? You see it's not a straight line and it has a minimum at some point(someday before the flight). We are going to see how historical Airfare data can help us derive the best day to book a flight so that you 'actually' get the cheapest fares. The talk would talk about the entire process, from getting the data, to training a basic Neural network on the data. With advancements in deep learning in these few years, it is very easy to train a simple statistical model to predict the prices. Also, my thesis at IIT Kharagpur was titled 'Forecasting of Airfare prices using Neural networks' and the talk is based on that along with a few improvements I made on top of that", - "Last Updated": "01 Jul, 2018", - "Prerequisites": "A brief understanding of neural networks or any machine learning model in general could help you make the most out of your talk", - "Section": "Data science", - "Speaker Info": "I am an IIT Kharagpur graduate(2017) who spent over 4 years coding in Python. Worked with all styles of python from website development using Django and Flask to scientific computing using numpy and scikit-learn to web-scraping using Selenium. It's been a wonderful journey all along and I'm now looking forward to bring as many people on board as I can to experience what I've experienced. I am also the founder of Papercop, an examination preparation portal for the students of IIT Kharagpur which has about 70k+ hits. I am a very passionate speedcuber( Can solve the rubiks cube in about 10s odd). Won plenty of medals in speedcubing competitions across the country. I now work as an analyst with American Express. Speaker at Pycon India '17 and invited to Pycon Italy'1", - "Speaker Links": "Links to previous talks: Pycon India'17 Twitter Linkedi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anuj Menta (~anujmenta)", - "created_on": "01 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/forecasting-and-observing-airfare-trends-using-python-and-neural-networks~aA23b/", - "title": "Forecasting and observing Airfare trends using Python and Neural Networks" - }, - { - "Content URLs": "https://github.com/audreyr/cookiecutte", - "Description": "When starting with a new python project/django web app, starting with initial project structure may not be that easy. Thinking about best practices that you have seen some other popular opensource projects and doing it over and over is very tiring.. what if we can just create a project with very little effort and share your set of tools that used in project to other team members? This talk is mainly about cookiecutter, it is a cli utility that creates projects from templates. We will see how to use existing cookiecutter template and finally create a template that works well for you and your team and share that template", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "Knowledge regarding basic python and may be jinja templating", - "Section": "Developer tools and Automation", - "Speaker Info": "Working as developer at Pramati technologies..Working with python from past 3 years, loves programming and automation", - "Speaker Links": "github - https://github.com/code-R\nlinkedin - https://www.linkedin.com/in/vamsi-krishna-29690614", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/scaffolding-made-easy-with-cookies-cookiecutter~dB2kd/", - "title": "Scaffolding made easy with cookies (Cookiecutter)" - }, - { - "Content URLs": "https://www.slideshare.net/veerskyfire/cyber-disorde", - "Description": "How social media is affecting our real life, what would be the prevention we can take to protect our digital identity and will share many real life case studies of cyber-crime with whom people will relate easily to better understand the scenario of cyber disorder and how to prevent such data leakage", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisites", - "Section": "Others", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog\nhttps://www.viralparmarhacker.com Linkdin\nhttps://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter \nhttps://twitter.com/viralparmarhack Github \nhttps://github.com/Veerskyfire", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cyber-disorder~bD2ye/", - "title": "Cyber Disorder" - }, - { - "Content URLs": "For Reference: https://github.com/Veerskyfire/auth0-pytho", - "Description": "This is introductory talk about the Authentication, where I will discuss about the role that Auth0 authentication plays in modern software development where it is a lot more than just the login screen. You will be able to learn about the different concept of authentication with python and In this talk the audience will learned about the different concepts that make up modern identity important for us to be secure, it will also enable people from the different peers technical as well as non-technical enthusiast to take opportunities to rethink of Authentication process of applications", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Networking and Security", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog\nhttps://www.viralparmarhacker.com LinkedIn\nhttps://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter \nhttps://twitter.com/viralparmarhack GitHub \nhttps://github.com/Veerskyfire/ Facebook \nhttps://www.facebook.com/viralparmarhacke", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/authentication-with-auth0~eE2Ya/", - "title": "Authentication with Auth0" - }, - { - "Content URLs": "https://www.slideshare.net/veerskyfire/who-is-spying-on-yo", - "Description": "Topics is about how our privacy is compromised every day, how it happens due to mass surveillance by governments, big tech company, data brokers & 3rd party apps etc., what are our rights to privacy & why it matters, what are the precaution we can take to secure it, secure communication channels like TOR and also will discuss about Broadband Policy, Net Neutrality & Cyber Warfare", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Others", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog https://www.viralparmarhacker.com LinkedIn https://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter https://twitter.com/viralparmarhack GitHub https://github.com/Veerskyfire/ Facebook https://www.facebook.com/viralparmarhacke", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/who-is-spying-on-us~dG2Lb/", - "title": "Who is Spying on us ?" - }, - { - "Content URLs": "https://www.slideshare.net/veerskyfire", - "Description": "Topic is about how AI and ML are building dystopia for us. The big companies like Google, Facebook, Amazon who are in business of capturing-selling data & our attention to advertisers, gathering our data, harvesting it and use against us to manipulate us & control us. How Social media Ads influence us using its persuasion architecture. Will explain how AI prediction is a threat to our freedom with Case study of smart health care", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No Prerequisite", - "Section": "Others", - "Speaker Info": "Founder of Infinite Defense Foundation (NPO), Reps at Mozilla Foundation. Initiator of \u201cLogOut\u201d- World\u2019s Biggest Cyber Awareness Campaign. 3+ years of experience in Information security & Cyber Crime Investigation. Expert in Cyber Crime Investigation, Digital Forensics, Public Key Infrastructure, Social Engineering, Reverse Engineering and Malware Analysis. Found sever vulnerability in more than 50 websites like YourStory, Intel and etc. Solved more than 40 cases of cyber-crime and online frauds. Trained 50,000+ people till now and aware them about privacy and security. Given Seminars and workshops in 100+ Organizations", - "Speaker Links": "Website/Blog https://www.viralparmarhacker.com LinkedIn https://www.linkedin.com/in/viral-parmar-8402a04a/ Twitter https://twitter.com/viralparmarhack GitHub https://github.com/Veerskyfire/ Facebook https://www.facebook.com/viralparmarhacke", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Viral Parmar (~Veerskyfire)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/we-are-building-dystopia-using-ai-ml~dJ2Jd/", - "title": "We are building dystopia using AI & ML" - }, - { - "Content URLs": "N.A", - "Description": "When I started using Python for scientific computing, it was simply a tool that helped me get the results I needed. It was a simple tool with a large and helpful community. Most of my code was simply an working amalgam of solutions found on Stack Overflow. I didn't take the time to learn about the fundamentals of the language, the tools that the language provided and the best practices. Only after I started working professionally did I take the time out to learn Python at a more basic level. As professional software developers, I think our job is to not just write code that works but to write code that uses the best practices. It's our duty to keep ourselves up to date about the advancements in the language and understand the language and the ecosystem at a more fundamental level. Towards this end, I will talk about a few language fundamentals such as attribute access on classes, decorators and closures in Python. I will talk about best practices such as using list comprehensions instead of explicit for loops. I will introduce a number of packages in the standard library that help write better Python code such as argparse and Path. Finally, I will introduces resources that helped me better understand the language and the ecosystem such as online documentation, books and talks by experts", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "No prerequisites are expected from the audience. This talk will be accessible to developers with all levels of experience", - "Section": "Core python and Standard library", - "Speaker Info": "I'm a Scientific Software Developer. I've been using Python professionally for just over two years. I was using Python for almost 3 years before that for scientific computing. I have a B.S. & M.S. in Physics from IIT Madras.\nI've given a number of talks in the Pune and Chennai Python meetups. I've also conducted workshops at SciPy India, PyCon India and a few other locations", - "Speaker Links": "More information about me and my work can be found at - http://rahulporuri.github.io/\nI occasionally blog at https://rahulporuri.blogspot.com/\nI'm @rahulporuri on twitter and you can reach out to me personally at rahul.poruri@gmail.com ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "rahul .poruri (~rahul66)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/growing-as-a-python-developer~aK2Me/", - "title": "Growing as a Python Developer" - }, - { - "Content URLs": "https://pytest.org", - "Description": "Nowadays everyone follows agile and care about code quality and testing their code, which gives them the confidence to maintain their application. Do people take shortcuts while writing unit tests? what are the common things to look out for while writing unit tests and good patterns to follow? This talk would be focused on those set of people who already know about unit testing in Python but they often feel the need of knowing the unit test best practices or they question themselves whether they are doing it the right way or not. Writing unit tests for your code is fairly simple but if you don't write them in the correct way or not following some of the best practices then it becomes a nightmare in the long run. Some of the things that will be covered during the talk are, why your unit test suite should be faster, effective usage of mock/stub. During my talk, I'd not only be emphasizing on writing good quality unit tests and would also hope to motivate the audience to follow these practices by showing them some practical use cases. For this, I'll be illustrating real code examples of such scenarios, best practices, and principles during the talk. How do tests help maintain good documentation? Why people suggest following TDD and how tests help to improve the design of your code and maintain for the long run", - "Last Updated": "02 Jul, 2018", - "Prerequisites": "People should be familiar with writing unit tests using any test framework", - "Section": "Developer tools and Automation", - "Speaker Info": "Working as developer at Pramati technologies..Working with python from past 3 years, loves programming and automation", - "Speaker Links": "github - https://github.com/code-R \nlinkedin - https://www.linkedin.com/in/vamsi-krishna-29690614", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/unit-testing-best-practices-some-common-pitfalls~dL2Xa/", - "title": "Unit Testing best practices & some common pitfalls" - }, - { - "Description": "Introduction to creating RESTful APIs in Python using django framework. This workshop is for everyone who develops web application backends or mobile app backends. Content which will be covered in workshop are as follows: HTTP methods Django Models Request & Response Status Codes Serializers Nested Serializers DRF classy views Hyperlinked APIs Permissions Authentication Authorization Viewsets and Routers In this workshop, we will be building Medium Clone from scratch by creating RESTful APIs", - "Last Updated": "02 Jul, 2018", - "Prerequisites": " Familiarity to *nix operating system. Basic python 3 & OOP concepts. Knowledge about HTTP and web development is plus.", - "Section": "Web development", - "Speaker Info": "Piyush Maurya: Piyush is currently working at Infosys, Mysuru & active volunteer @bangpypers . He has 2.5 years of experience in Python/Django, which includes building college event portal to large scale enterprise. He lives in Mysuru and can be found at every BangPypers Meetup. Nowadays, he is experimenting with Flutter SDK and uses django-rest-framework to build APIs for mobile apps. Karan Shah: Karan is currently working at Infosys, Mysuru. Right now he is exploring Flutter SDK and trying to develop a cross platform app", - "Speaker Links": "Github: https://github.com/piyushmaurya23 Twitter: https://twitter.com/piyushmaurya23 Linkedin: https://www.linkedin.com/in/piyushmaurya23", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Piyush Maurya (~piyushmaurya23)", - "created_on": "02 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/restful-apis-in-python-django-rest-framework-101~aM2Ob/", - "title": "RESTful APIs in Python: Django Rest Framework 101" - }, - { - "Content URLs": "Content will be updated soon", - "Description": "Note:- This talk will be co-presented by Me and Saurabh Ghanekar. Talk Summary:- For a long time we have faced many problems in transferring a file from one place to another without the use of a central server. But with the use of peer to peer, BitTorrent protocol, it is relatively easy for us to share our data. But there is a problem in here. It is not fully decentralized. There are still centralized servers that host these files. Moreover we at our college find it quite difficult to share our study material over LAN as nobody hosts their study materials (duh!!!). So we decided to create a decentralized file sharing application that enables us to share our file to all our friends even if we didn\u2019t hosted it on a server. In this talk we will be explaining the basics of decentralization. We will expand on what and how this could be used to make a file sharing application. We will also shed some light on how to make a fairly secure file sharing application based on the topics we will be covering at the beginning of our talk. Once we are through with the theory and our code, we would be presenting our proof of concept i.e. a small demo of the application. Outcome of the Talk:- After this talk you would expect to learn the basics of decentralized network, how to make a secure decentralized application and successfully learn how to make a decentralized file sharing system. Agenda:- Brief Introduction of Decentralization. [6 min] Basics of File Transfer over a Network. [4 min] What a fairly secure File Sharing Network mean? [5 min] Making and Implementation of making a Decentralized File Sharing Network. [10 min] Making and Implementation of making a Decentralized File Sharing Network. [10 min] A small Live Demo. [3 min] Q and A. [2 min]", - "Last Updated": "03 Jul, 2018", - "Prerequisites": "Love for Pytho", - "Section": "Networking and Security", - "Speaker Info": "This talk is co-presented by Me and Saurabh Ghanekar. Shubham Rao Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData . Saurabh Ghanekar Hi, a Computer Science sophomore whose research interests lie in Machine Learning and Artificial Intelligence , occasionally working on Virtual and Augmented Reality projects. I\u2019m part of a QS award winning student-led multidisciplinary lab called Next Tech Lab where we research in Artificial Intelligence, Mixed Reality, Internet of Things, and Blockchain. I am also co-organiser of PyData Amaravati . I also regularly participate and give talks in paper-reading groups and meetups like PyData ", - "Speaker Links": "Shubham Rao Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitHub E-mail me at : cshubhamrao [at] gmail [dot] com Saurabh Ghanekar Follow me on Twitter Connect with me on LinkedIn Visit my Website Find me on GitLab and GitHub E-mail me at : ghanekarsaurabh8@gmail.co", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Shubham Rao (~shubham66)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/a-cool-way-to-share-files-in-this-21st-century~dNRDd/", - "title": "A Cool Way to Share Files in this 21st Century" - }, - { - "Content URLs": "if possible download Firefox: https://www.mozilla.org/en-US/firefox/new/ on your computer and/or phone", - "Description": "We as programmers often do not give a lot of thought/importance to our online privacy while using the web. This session/talk will be useful for programmers to guard their online privacy. Consider a programmer using google search engine to search for errors or using stack overflow to find answers to fix a broken python dependency. All of it is stored and profiled against the online identity of the programmer. This data can then be used to sell ads which as we all feel are annoying.\nThis session/talk will help everyone (who uses the web) learn the best practices of anti-tracking, ads blocking, anti-profiling clean browsing environments. We as programmers might be using the same browser for professional and personal work/browsing causing mix-match of data and annoying ads popping up during work sessions. \nThis session/talk will help such programmers keep it all separate via firefox profiles, just like clean python virtual environments :) What will happen during the session? Introduction to Firefox and Icebreaker - 3 mins Customize Firefox, Profiles, and Preferences - 10 mins How you can change Firefox configs to have a more customized and private experience - 10 mins How to block trackers on the web - 10 mins Best Privacy extensions - 5 mins Use of privacy respecting search engines - 5 mins QA - 7 mins This session/talk is for anyone and everyone who uses the web", - "Last Updated": "03 Jul, 2018", - "Prerequisites": " A couple of screens/monitors or a projector at the session will help participants hack, make, learn and share with other participants. Sticky notes Sharpies Optional firefox installed on computers or phones of participants. Open mind", - "Section": "Others", - "Speaker Info": "Ankit Gadgil is an open source and open web advocate who believes the web should be equally accessible to all for equal opportunity. He strongly supports data privacy. Ankit works for Red Hat as a senior software engineer and enjoys working with python, Js, algorithms, and architecture.\nHe usually contributes to open source projects like Mozilla, MediaWiki, Wordpress. He has also served as a member of the Mozilla Reps Council", - "Speaker Links": "Info: https://reps.mozilla.org/u/ankitgadgil/ Twitter: @anknit", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Ankit Gadgil (~anknite)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/using-firefox-like-a-boss-privacy-settings~aORYe/", - "title": "Using Firefox like a Boss - Privacy Settings" - }, - { - "Content URLs": "Coming soon", - "Description": "Abstract Tox is a generic virtualenv management and test command line tool you can use for: checking your package installs correctly with different Python versions and interpreters running your tests in each of the environments, configuring your test tool of choice acting as a frontend to Continuous Integration servers, greatly reducing boilerplate and merging CI and shell-based testing. Description In this talk we will see what is tox and how we can use it to test our application using different python versions or different Django versions etc., we will see how tox help us in reducing the boilerplate code when integrating with jenkins/travis Outline Introduction to tox (3 min) Diving into tox (how tox works) (5 min) Writing a basic tox configuration - tox.ini (3 min) See how OpenStack leverages tox with Jenkins (4 mins) Some use cases with tox ex: bandit, pep8 (3 mins) Demo (5 mins)", - "Last Updated": "03 Jul, 2018", - "Prerequisites": "Basic understanding or virtual environments and unit testing using python", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/tox-python-testing-wrapper~dP81d/", - "title": "Tox - Python testing wrapper" - }, - { - "Content URLs": "https://tutorial.djangogirls.org/en", - "Description": "Django Girls is a non-profit organization and a community that empowers and helps women to organize free, one-day programming workshops by providing tools, resources and support.\nYou'll work through a tutorial in small groups with a coach, so you'll be able to learn at your own pace. Every coach will guide their group of attendee and teach them Django. There will be general 2-3 meta coaches to help these coaches. \nDuring Django workshop you will create your website in Django ", - "Last Updated": "03 Jul, 2018", - "Prerequisites": "Basic knowledge of Python will be sufficient", - "Section": "Web development", - "Speaker Info": "As per workshop structure, there is no one speaker. There will be group of coaches, metal coaches, volunteers and organizers. I am final year student of Bachelor of Engineering in Computer. I have organized Django Girls workshop before at our city and it was amazing experience to see 45+ women get inspired and learned. I love contributing to open-source and got my first internship Zulip-Winter-of-Code at Zulip. Also got selected for GSoC-2018-with-Zulip and interned at IIT-Bombay", - "Speaker Links": "Portfolio GitHub Linkedin Django Girls Bhavnaga", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Dave Yashashvi (~dave)", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/django-girls-start-your-journey-with-programming~aQR0b/", - "title": "Django Girls - start your journey with programming" - }, - { - "Content URLs": "To be updated soon !", - "Description": "90% of data in the internet today is either image or video.The exponential rise of visual data has continuously urged researchers to develop robust and efficient Object detection algorithms,but CNN or R-CNN or YOLO or SSD which algorithm can give best results.In this talk I will try to cover salient features in some of the most influential works in this problem statement.The talk begins with intro to CNNs and goes into detailed discussion of state-of-the-art deep learning algorithms used for object detection. Structure of the talk - The talk is structured into 3 sections :\nIn the first 20 minutes we will have a talk on the architectures, then 10 minutes will be dedicated for some hands-on demo to build a CNN using Keras/Pytorch and the rest of the time will be for QnA. Contents - The talk will begin with a discussion on Convolution Neural Networks and various terms associated like Convolution,pooling,activation used etc and there after discussing about the various state-of-the-art algorithms like R-CNN,Fast R-CNN,Faster R-CNN,R-FCN,YOLO and SSD.One of my analysis criteria will be on their speed at inference allowing real-time analysis. Take aways : What is a CNN,what are convolution,pooling etc. What are R-CNN,Fast R-CNN,Faster R-CNN,R-FCN,YOLO and SSD How to implement a CNN using keras/Pytorch.", - "Last Updated": "03 Jul, 2018", - "Prerequisites": " Basic python or any other language programming. Basic knowledge of Machine Learning and Neural Networks. Most importantly an interest to learn a new concept.", - "Section": "Data science", - "Speaker Info": "The speaker is a 4th year undergraduate student from the department of Computer Science and Engineering at IIIT Bhubaneswar. He is a Data science, Machine Learning and Deep learning enthusiast.He has an experience of over 2 years in this field and has worked on Machine Learning and Deep Learning and it's application to Computer Vision(CV) and Natural Language Processing(NLP). He has worked on few self projects and been a part of 2 research Internships, One at IIIT Bangalore and another at IIT Kharagpur . He has experience of working with various libraries like sci-kit ,Tensorflow ,Keras ,Torch and Pytorch", - "Speaker Links": "Get in touch with me through LinkedIn Also reach me on Twitte", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "saiamrit", - "created_on": "03 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/object-detection-demistified-state-of-art-deepnets~dR7Oe/", - "title": "Object Detection Demistified-State of art DeepNets" - }, - { - "Description": "Short description. Unit testing and continuous integration are core part of any software development team, in this talk you will understand how py.test and pytest-bdd (behaviour driven testing) helps us accelerate this process. Things you'll learn pytest basics, gherkin basics for pytest-bdd pytest Intermediate concepts - fixtures, parametrizing test cases pytest-bdd intermediate concepts - step definition, reusing pytest fixtures Jenkins integration for pytest", - "Last Updated": "05 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "I'm the head of technology at TenderCuts and Envee. We are an omni-channel meat delivery startup. At our company we make heavy use of python from our ERP to our mobile app", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "varunxyz", - "created_on": "05 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/super-charging-python-testing-with-pytest-and-pytest-bdd-jenkins-integration~eXR5b/", - "title": "Super charging python testing with pytest and pytest-bdd + Jenkins Integration" - }, - { - "Description": "A face animation software which will be very useful in the media and entertainment industry. Here, by just showing your face you can create an avatar", - "Last Updated": "05 Jul, 2018", - "Prerequisites": "Should know basics of Pytho", - "Section": "Core python and Standard library", - "Speaker Info": "A final year BCA student who is very enthusiastic about artificial intelligenc", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Swarnali Singha (~swarnali)", - "created_on": "05 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/face-avatar-using-artificial-intelligence~bYRMd/", - "title": "Face Avatar using Artificial Intelligence" - }, - { - "Description": "Django has swiftly made its way to the top of the web application stack and it is becoming extremely popular among the developers whether freshers or veterans due to its robust framework and inbuilt security features. However, a lot of the developers take this security for granted while developing a web application or an API and therefore often end up with some loopholes that can be exploited by the attackers directly impacting the consumer\u2019s data and the website's reputation. This workshop is intended to talk about those common and uncommon flaws giving special focus to the Owasp Top 10 standards of web application security, use cases where developers might fail to implement them and secure coding practices wrt the same. We will be presenting a live demo on intentionally made vulnerable Django applications with real-life use cases. We will understand how hackers may exploit them, common mistakes developers might make which can lead to a specific vulnerability and how to patch them/build them securely along with secure coding best practices. The demo application will be open source for the audience to try live during the workshop and after it too", - "Last Updated": "05 Jul, 2018", - "Prerequisites": " Beginner level Django and Python knowledge Interest in understanding common attack methodologies and developing secure web applications.", - "Section": "Web development", - "Speaker Info": "Soumya Singh Soumya Singh is a programmer at heart and she has 2+ years of experience in professional Django development and over 3 years experience with Android application development. She is currently working at BugsBounty.com - A crowd-sourced security platform for ethical hackers and organisations where she heads a team to build various security-related products. Besides this, she is LCCSA certified Ethical Hacker and takes cyber security rather seriously", - "Speaker Links": "LinkedIn Profil", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Soumya Singh (~soumya96)", - "created_on": "05 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/owasp-top-10-web-security-loopholes-vs-django-which-is-allegedly-secure-no-matter-who-is-coding-with-it~eZRwe/", - "title": "OWASP Top 10 Web Security Loopholes v/s Django - Which is \u201callegedly\u201d secure no matter who is coding with it." - }, - { - "Content URLs": "Details of this talk can be found on my website. This talk was previously given at EuroPython 2017 slides on speakerdeck video of this talk being given at EuroPython 201", - "Description": "Command execution time can become important in a number of applications. Commands executed in command-line completion need to execute in less then 100ms or users will perceive a delay. In Shell scripting one might want to execute commands repeatedly in a for loop and fast execution times makes this more feasible. Python is a very powerful language but has a much slower startup time compared to other interpreted languages like Perl, Lua and Bash. It can take up to 10 times longer to startup then some of these other languages. MicroPython was written as a lean implementation of Python 3 with a small subset of the standard library mainly intended to run on microcontrollers. But it happily runs on Unix systems with excellent startup performance, making it an ideal candidate for implementing certain time sensitive commands. This talk will: Explain when achieving fast execution times matters and when it doesn\u2019t. Present two different approaches to measuring command execution time, one simple and the other more detailed and accurate. Compare execution times of a simple set of scripts that add two numbers in an number of different interpreted languages (micropython, python3, awk, perl, lua, bash). Present an example use case of MicroPython on Unix. Bash completion for pip install that completes the names of available packages live from a remote pypi mirror. Demonstrate the auto completion script with pip on a local pypi mirror. ", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "Basic understanding of running python scripts on the command line", - "Section": "Embedded python", - "Speaker Info": "I'm a passionate Python developer living on the sunny island of Bahrain. I've been a speaker at Python conferences before and ran the Bahrain Linux User Group for five years. During that period I was a regular speaker at the groups monthly meetups. I\u2019ve taught courses in python programing and computer networking to both students and working professionals", - "Speaker Links": "I've given talks at two python conferences before: EuroPython 2017: Executing scripts in a few milliseconds with MicroPython PyLondinium 2018: Snow globe intruder alert syste", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Marwan Al-Sabbagh (~marwan)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/executing-scripts-in-a-few-milliseconds-with-micropython~e1DVd/", - "title": "Executing scripts in a few milliseconds with MicroPython" - }, - { - "Content URLs": "Details of this talk can be found on my website. This talk was previously given at PyLondinium 2018 slides on speakerdec", - "Description": "Learn how to build a snow globe that sounds an alarm and flashes a red alert when intruders are about. Me and my six year old daughter designed and built this project to have fun with friends and learn a bit about computers along the way. Adafruit\u2019s Circuit Playground Express is a fantastic $25 computer packed with sensors, buttons, LEDs and a little speaker. Add this DIY Snow Globe Kit and some Conductive Thread and we have the makings of an ingenious Snow globe intruder alert system. All written in python using a simple text editor without the need for any special software, drivers or soldering. The globe has a rainbow mode that randomly fades different colors in and out and an alarm mode to detect intruders. Modes can be switched by giving the globe a tap which it detects with it\u2019s motion sensors. Once in alarm mode the globe will flash green until an intruder steps on the conductive thread which will sound the alarm and flash the globe red. The Circuit Playground was used to teach my six year old daughter the differences between computer inputs and outputs and how to issue commands to computers using the Python REPL. She learned about the different frequencies of sound waves by calling the beep function with different frequencies. This opened up the topic of the hearing range of humans compared to other animals like dogs. She then learned to set the color of each of the ten NeoPixel LEDs into a rainbow pattern by calling the light function multiple times with each color and position. We explored how any color can be displayed as a combination of red, green and blue by using a digital microscope to see these three LEDs change with different colors. This talk will cover: Tour of the Circuit Playground Express Assembling the snow globe The rainbow and alarm code REPL sound and light with a six year old Troubleshooting tips", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "Basic exposure to python", - "Section": "Embedded python", - "Speaker Info": "I'm a passionate Python developer living on the sunny island of Bahrain. I've been a speaker at Python conferences before and ran the Bahrain Linux User Group for five years. During that period I was a regular speaker at the groups monthly meetups. I\u2019ve taught courses in python programing and computer networking to both students and working professionals", - "Speaker Links": "I've given talks at two python conferences before: EuroPython 2017: Executing scripts in a few milliseconds with MicroPython PyLondinium 2018: Snow globe intruder alert syste", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marwan Al-Sabbagh (~marwan)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/snow-globe-intruder-alert-system~b2E1a/", - "title": "Snow globe intruder alert system" - }, - { - "Description": " With the rise of MEAN(MongoDB Express AngularJS NodeJS) stack framework with Python for secure server-side scripting. A simple introduction to using Python Capabilities for Server Management. Using NumPy and SciPy libraries in Javascript.", - "Last Updated": "04 Jul, 2018", - "Prerequisites": "Core Python. Javascript", - "Section": "Core python and Standard library", - "Speaker Info": "Aniket Chowdhury While I have been programming for more than a decade, my chosen language for the lesser half of the decade has been C++, with a wandering interest in Java, MySql, PHP and Ruby. The last few years were spent in cultivating the language we now all know as Python. The enamoured feasibility of the language over C++ and the ease of understanding over PERL. While being a bit slower due to being it's interpreted nature, better speed benchmarks are being discover by it's PyPy implementation. My field of interest is Deep Neural Networks. Machine Learning may perhaps helps us to cure even cancer using gene sequencing. Apart from that I am an avid reader. I read book from all genres and time. My hobbies include football, music, art, drama and of course, programming", - "Speaker Links": "GitHub Instagram Emai", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aniket Chowdhury (~aniket43)", - "created_on": "04 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/integrating-python-with-nodejs~eV9vd/", - "title": "Integrating Python with NodeJS" - }, - { - "Description": "The hardest part of building a text classifier is finding labelled data to train the model. The next hardest part is making sure that data is fair and representative. In this talk we will discuss some approaches to rapidly generating corpora suitable for supervised training from public data and with open-source tools. This talk will include some practical tips as well as some less-obvious pitfalls, and is suitable for both novices and more experienced Natural Language Processing Practitioners. At the end of the talk you will be able to give a convincing answer to the eternal question: How do I build a text classifier for a product that doesn't exist yet? Co-presented with Alex O'Conno", - "Last Updated": "06 Jul, 2018", - "Section": "Data science", - "Speaker Info": "Alizishaan's professional passions revolve around two things : using technology to solve real-world problems and sharing solutions with the community. He is currently employed as a Machine Learning Engineer with Pivotus where he works on problems in the Natural Language Processing space. Over the summer of 2017, he designed and built an offensive content detection system for a Silicon Valley company. Past industry projects include a price-prediction system for cars and a status communication system that minimized false alerts. Outside of work, Alizishaan's passions include mountaineering, skiing, travelling and photography", - "Speaker Links": " My talk at PyCon APAC 2018 An attendee's review of my talk", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Alizishaan Khatri (~alizishaan)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/something-for-nothing-boostrapping-text-classification~e3GOe/", - "title": "Something for Nothing: Boostrapping Text Classification" - }, - { - "Description": "At Sumo logic which is entirely cloud-based, one component of it resides out of the cloud and rests in the hands of users, in their own infrastructure. This component is sumo's installed collector. This is an installable package for which various forms of binaries get generated in form of rpm, deb, tar, sh, exe and docker images. These packages, along with a plethora of functionalities of the installed collector, need a test bed which not only gives the user freedom to select which tests to run but also which kind of OS the packages might be installed at. We have created a testbed which is multi-platform and runs on the back of AWS cloud infra. The automation testbed has been designed such that we get to write code in a platform agnostic manner, hence the same set of tests can be run in Windows, Debian or RHEL systems. The testbed helps us with managing various versions of installed collectors and help us with verifying our upgrades and various flows across them. We use Ansible for our box setups, of various Linux and windows types, and pytest to write various test scenarios, these tests verify various functionalities of collector along with the installer themselves. Using pytest we can leverage huge armada of python libraries available such as ansible libraries, fabric, sumo's own search, metrics libraries. This kind of test-bed has uniquely brought down our 2 weeks of tests cycles to now less than 3 days and gives us immense confidence in delivering projects at a much rapid pace", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "A beginner's knowledge of ansible and pytest is all people will need to know of", - "Section": "Developer tools and Automation", - "Speaker Info": "Vivek Gupta , Lead QE - platform, Sumologic Vivek has been working with python through most of his career with experience of 7 years in companies like Adobe and Quad Analytix previous to Sumologic. Responsible for Sumologic's entire platform testing, his team works on a wide scope of challenges related to their installers, hosted collectors and their core services. Gourav Garg , QE - platform, Sumologic Gourav has an experience of 1 year and was hired straight out of college. He is responsible for the collection team QE activities along with quite a few QE Jenkins activities at Sumo. He takes care of the entire range of installed collectors as well as hosted collectors", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "vivek gupta (~vivek73)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/multiplatform-automation-test-bed-using-ansible-and-pytest~b4JVe/", - "title": "Multiplatform automation test bed using ansible and pytest" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of Github Repository", - "Description": "Named Entity Recognition is the task of extracting named entities like Person, Place etc from the text. It is an important step in extracting information from unstructured text data.\n I will explore various approaches for entity extraction using both existing libraries and also implementing state of the art approaches from scratch Agenda for the Talk: Introducing Named Entity Recognition Standard Named Entity using NLTK and Spacy Training Custom Entity Tagger using Spacy or Rasa Standard Algorithms for NER Conditional Random Field (CRF) Deep Learning for NER using LSTM in Keras Structured Deep Learning for NER using LSTM-CRF End-to-End NER via Bi-directional LSTM-CNN-CRF", - "Last Updated": "06 Jul, 2018", - "Prerequisites": "A Basic Knowledge of Python, Machine Learning and Natural Language Processing", - "Section": "Data science", - "Speaker Info": "Subramanya T A is Senior Data Scientist at Sentienz. He heads the Data Science team at Sentienz", - "Speaker Links": "LinkedIn Profile: \n https://www.linkedin.com/in/subramanya-t-a-7306a729/ Sentienz Website:\n http://www.sentienz.com", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "T. A. Subramanya Paddillaya (~t._a._subramanya)", - "created_on": "06 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/named-entity-recognition-in-python~e5gKb/", - "title": "Named Entity Recognition in Python" - }, - { - "Description": "How many times have you banged your head on the wall while using Javascript to build a page showcasing your shiny new Python project? Wouldn't it be great if your blog readers could run and play with the code right away? Fancy running Jupyter-like notebooks entirely in the browser without any server? This talk will get you a headstart into running Python directly in the browser. Agenda Introduction (2 mins) About me Why the Browser is an important stack to target? Three major approaches (20 mins) We will be peeking at the official demo and docs for these projects and dig deeper on how they work. Brief details below : Transpilation - Python code is converted to Javascript before the page is loaded. Examples include PyScript and Transcrypt Python implementation in Javascript - Python code conversion to JS takes place in the browser itself Examples include Brython , Skulpt and Batavia Brython converts Python code into JS in the browser with access to the DOM elements and events The way Batavia works is marvelous! It takes the bytecode for the Python program generated and interprets the Python bytecode as a running program in the browser realtime using a Javascript implementation of the Python VM. Web Assembly - Converting full implementations of Python to run on the web Examples include PyPyJS and Pyodide PyPyJS as the name suggests is the entire PyPy implementation compiled to Javascript. It is PyPy compiled for the web via emscripten, with a custom JIT backend that emits asm.js code at runtime. Pyodide takes this to a different level. It takes the entire Python scientific stack and compiles it to run on the browser using Web Assembly. That means every data library you love - numpy, pandas, matplotlib will run directly on the browser - no installation needed! Conclusion (5 mins) Learnings about Python internals This area is still in its infancy - what to look forward to?", - "Last Updated": "07 Jul, 2018", - "Prerequisites": "General overview of how Python works under the hood - What happens when you run a Python file using CPython, what Python bytecode is etc", - "Section": "Core python and Standard library", - "Speaker Info": "Currently working as a Freelance Python Developer based in Kochi. Originally did Bachelors in Mechanical Engineering from CUSAT.\nI have completed consulting projects in ML and AI with multiple startups and companies. My work on CNNs was the winning solution for IBM\u2019s Cognitive Cup challenge in 2016 and gave a talk on the same at the Super Computing conference SC16 at Salt Lake City, Utah : Slides Previously I was a Technology Innovation Fellow with Kerala Startup Mission where I started a non-profit student community TinkerHub, that has a focus on creating community spaces across colleges for learning the latest technologies. I've been dabbling around with browser technologies since my college days since 2011 being a Mozilla volunteer which got me interested in finding ways to run Python in the browser", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/praveensridhar/ Previous talks : Anthill Inside talk on Explainability in AI SpeakerDeck", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Praveen Sridhar (~psbots)", - "created_on": "07 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-in-the-browser-run-run-run~b6jVb/", - "title": "Python in the Browser - Run! Run! Run!" - }, - { - "Content URLs": "Find me on Quora My WordPress blog My LinkedI", - "Description": "Computers can tell us whether we\u2019re happy, sad, angry or any of the several emotions we feel. Computers can understand what we\u2019re saying and answer back. How does all this magic happen?\nThis concept of teaching a program to analyze speech and understand it is called speech recognition. I\u2019ll talk about speech recognition and its various nuances, and how it is handled using Python. I\u2019ll also talk about various branches of speech recognition such as speech emotion recognition and text generation based on speech data, and speech recognition implementations on hardware as well. Here is a basic summary of what all I will cover: Speech recognition: what is it, why is it required - concepts like spectral analysis, MFCCs (Mel Frequency Cepstral Coefficients), Fourier transforms, signal processing etc. How Python can make speech recognition easier Branches and new areas of speech recognition: speech emotion recognition, sentiment analysis etc., work done in these fields in the past few decades How speech recognition models are built: acoustic and language models etc. Resources like blogs, libraries, toolkits etc. for studying and getting started with speech recognition models in Python Basic workflow and tips on how to create your first speech recognition model using Python A brief on various repositories of speech databases, how they can be accessed and prepared for input to speech models Speech recognition models implemented on FPGA (hardware), some seminal (and thoroughly comprehensive) research papers to read on the latest work in the field Other media such as video data and face emotion recognition, resources for studying them up further Applications and future scope, closing remarks I will cover the basics of how speech is read, processed and quantified, concepts like the Fourier Transform and spectral analysis, the various Python libraries and resources that exist for the same, and how one can build their own speech recognition system easily. Perhaps an Alexa 2.0", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "Basic knowledge of Python and data science should suffice", - "Section": "Data science", - "Speaker Info": "I am a third year undergrad at Delhi Technological University. I am passionately fond of data science and machine learning, and have worked on several projects and authored research papers on the same. My research area particularly centers around ensemble learning and methods, and I've started taking an interest in speech recognition systems in recent months. I have worked with professors across several universities, and am always up for discussing Python, machine learning and data science with anyone", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anjalib123", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speech-recognition-using-python-how-a-computer-can-tell-if-youre-angry~e7kye/", - "title": "Speech recognition using Python: how a computer can tell if you're angry" - }, - { - "Description": "Can we make any machine talk or give speech, naturally like any human ? Can my digital personal assistant like Siri, Alexa etc mimic my voice or give response in my own voice ? Generating human like natural voice has been a topic of research for a long time and a quite challenging task. But recent development in field of Speech Synthesis using advance deep learning technologies has made it achievable. Speech Synthesis has been integral part of any voice driven application. Although we have been able to generate good quality voice using standard method but in reality the generated voice is still too robotic ,emotionless and far away from the actual human voice. In the recent AI development in this field has made it possible to generate expressive human level voice. There are many recent papers like wavenet ,Tacatron and deep voice which do well upon precisely generating actual human voice and even mimic any person voice. In this talk , I will cover literature of voice synthesis and how we can generate human level voice without doing phd in speech processing. Key Components of talk : 1. Understand the basic literature of speech synthesis 2. Components of speech synthesis engine. 3. How to create own voice dataset. 4. Building basic text to speech engine using Tacotron2. 5. Application of real time speech synthesis", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Basic knowledge of python and jupyter notebook. Familiarity with machine learning components. Basic knowledge of linear algebra, probability distribution and calculus. Knowledge of speech processing is bonus .", - "Section": "Data science", - "Speaker Info": "Myself Rishikesh ! I am working at Humonics Global Pvt. Ltd as Data Scientist. Apart from my job I am actively contributing to open source projects and speaker of many data science communities like PyData Delhi, Delhi Kaggle Group etc. \nMy area of expertise are Speech processing, Data science, Deep learning and statistical modeling ", - "Speaker Links": "Linkedin Githu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rishikesh kumar (~rishikesh)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speech-synthesis-engine-for-generating-human-like-natural-voice~e9mBe/", - "title": "Speech Synthesis engine for generating human like natural voice" - }, - { - "Description": "Is there a better time to be a developer! Thanks to Cloud Computing, deploying applications is much more comfortable than it used to be. Serverless computing is an abstraction layer in the cloud. It does not mean that there are no servers, but instead, underlying infrastructure (VM, storage, containers, etc.), as well as the operating system, is abstracted away from the developer. Applications are run in compute containers that are event triggered. Developers have to create functions and depend on the infrastructure to allocate the proper resources to execute the task. Manage the load by creating copies of the functions and scale to meet the demand. OpenFaaS (Functions as a Service) is a framework for building serverless functions with Docker Swarm or Kubernetes which has fantastic support for metrics. We can package/deploy any simple API / service as a function. At a high level in this session: We will discuss and implement a live python function via template and deploy this python functions to Docker Swarm & Kubernetes. We will design and host a page which is broken into many functions. We will touch up the architecture of OpenFaaS and how python community can contribute to OpenFaaS Store We will discuss how to use K8's and it's Operator to push python function using OpenFaa", - "Last Updated": "08 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "Vivek is a tech enthusiast with over 11 years experience in the Software Industry. He is currently working as a Developer Advocate with DigitalOcean and has been a Technology Advisor to several tech startups. Previously he was Head of DevOps & QA at Blackbuck and was a DevOps Solution Architect at HCL (Australia) in client engagement and pre-sales roles. Vivek started his career with IBM Rational (INDIA Software Labs) and is passionate about working with software developer communities", - "Speaker Links": "https://www.linkedin.com/in/vivsridh https://twitter.com/vivek_sridhar https://github.com/vivsridh4 https://hasgeek.tv/rootconf/2018-day-2/1509-distributed-tracing-with-jaeger-at-scale https://hasgeek.tv/rootconf/cloud-sever-management-delhi/1435-auto-remediation-at-scale-using-watchers-vivek-sridha", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vivek Sridhar (~vivek861)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/build-push-deploy-serverless-python-function-with-openfaas-framework-on-kubernetes~e0Byb/", - "title": "Build, Push & Deploy serverless Python function with OpenFaaS Framework on Kubernetes" - }, - { - "Content URLs": "To be added soon", - "Description": "Human psychology has remained and continues to remain one of the most challenging areas of research as it aims to understand individual\u2019s behavior and mind, including conscious and unconscious phenomena, as well as feeling and thought. The extent of impact social media has caused on the human mind is huge and perhaps, hard to imagine. Thanks to python and it's brilliant capabilities to process natural language, we can now understand how social media is affecting our lives from a psychological perspective and if it is capable of changing our behaviors, our expressions, our sleeping patterns, or even emotions. From social posts, we can draw interesting conclusions about both men and women if we can comprehend what are the topics they are most interested in, what time of the day are they most and least active etc. Core idea: Collect a dataset from Twitter (or any other social network) of the world's top 400 most influential women for the year 2013 and for the year 2018 Train an NLP model and use this model to classify the collected data under various categories like education, religion, etc. and identify if the post is a concern, compliment, complaint etc. Perform a year-wise trend analysis to identify the topics they are most interested in and parameters like the most/least active time of the day, the most active/least active day of the week the average time spent on twitter per week/month etc. Carry out behavioral analysis by evaluating how the ways of expression, activity levels etc. have changed on social media over the last five years and what might have been the possible reasons for the same Structure: 5-10 mins \u2013 Introduction and discussion ( algorithms and concepts being used ) 10-20 mins \u2013 Code walkthrough followed by discussions on the results obtained (Please refer the core idea section for more details) Remaining time \u2013 Q/A or general discussion Contents: An introduction to natural language processing - text normalization, n-grams, PoS tagging An introduction to deep learning - neural networks and neural language models (framework - keras) A brief discussion on the implementation of a sentiment classifier - Naive Bayes classifier/RNN classifier If time permits, test out a few tweets to understand the working of the classifier Conclusion - how can the results help identify opinions, attitudes, emotional states & future scope (of the project) Note: The entire talk will be a powerpoint based presentation along with illustrative code snippet", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "Python - Beginner/Intermediate Machine Learning - Beginner NLP/Deep learning techniques - Beginner Keras/Tensorflow - Beginner Basic familiarity with the following libraries/tools: 1. numpy 2. pandas 3. matplotlib 4. jupyter noteboo", - "Section": "Data science", - "Speaker Info": "The speaker of this talk is Reyha Verma . She is currently working as a data scientist at Sprinklr, Gurgaon. Since her organization is the world's best social media management platform, she spends most of her office and her personal time juggling between new, efficient deep learning models and tons of social media data. She is an open-source enthusiast who has also previously been a mentor with Zulip, an open-source python based chat application for FOSS Outreachy program 2016 and has undertaken research projects at National Sun Yat-Sen University, Taiwan and Bhabha Atomic Research Center (BARC), Mumbai while pursuing her undergraduation at the National Institute of Technology, Srinagar", - "Speaker Links": "LinkedIn - https://www.linkedin.com/in/reyhav Github - https://github.com/reyha Twitter - https://twitter.com/reyhav", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "reyha (~reyha)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/decode-human-behavior-through-code-a-counter-intuitive-approach~b8lgb/", - "title": "Decode human behavior through code: A counter-intuitive approach" - }, - { - "Content URLs": "1.Understanding Convolutional Neural Networks - CS231n Stanford-http://cs231n.stanford.edu/\n2.Any Deep Learning Library preferably Tensorflo", - "Description": "This talk will cover understanding limitations of Convolutional NN in detecting images. \nAfter understanding this limitation, I will introduce the concept of capsules.\nThis talk is highly inspired from the paper from Geoff hinton- Dynamic routing betwen Capsules-https://arxiv.org/pdf/1710.09829.pdf\nI will try to explain the process of training a multi layer capsule system on MNIST and comparing it with a convolutional net at recognizing highly overlapping images.\nI will use Tensorflow or Keras to show my demo Jupyter notebook.\nI will also discuss the limitations of capsules", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "1.Linear Algebra\n2.Probability and Statistics\n3.Any Deep Learning library (Tensorflow/pytorch/Keras)\n4.Deep Learning layers- Fully connected and Convolutional layer", - "Section": "Data science", - "Speaker Info": "Hi, I am Swapan Jain. After graduating in Computer Science from Delhi Technological University, I self studied AI by reading books,papers and taking courses online. I am a prospective graduate student from fall 2019", - "Speaker Links": "I currently do not have open source contributions, but I will begin the blog from August.\nmy twitter handle is @swapanj162. I will update about my blog or any project on my twitter", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "SWAPAN JAIN (~swapan)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/capsule-networks-overcoming-limitations-of-convolutional-neural-networks~egPGa/", - "title": "Capsule Networks - overcoming limitations of Convolutional Neural Networks" - }, - { - "Content URLs": "Contents will be updated here: https://github.com/dipakkr/pycon-2018 You can also find the presentation here after the session", - "Description": "Computer vision enables the machine to see and analyze objects like humans do. Despite the significant recent advancement in computer vision, implementing it efficiently at a scale presents a serious challenge. Computer Vision deal with techniques like Object Recognition, Object Detection, Face Recognition, segmentation and many more. \nThe best example of this would be a Self-driving car. In this session, we will discuss, how to get started with computer vision using OpenCV. OpenCV is a computer vision library which provides an implementation of the various algorithm on a single call. However, It takes a lot of time and a good understanding of Convolutional Neural Network to build a good computer vision technique. Let\u2019s Start !!!!!! We will also see few demos DEMO - Image Filtering Object Detection Image Recognition", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Beginner or Intermediate in Python Basic numpy operation Love for Computer Vision and Python", - "Section": "Data science", - "Speaker Info": "a Researcher , Backend Developer , and Machine Learning Enthusiast . I am currently working as Deep Learning Research Intern at MNIT Jaipur . You can find out more about him at : https://github.com/dipakkr https://www.linkedin.com/in/dipakkr/ https://medium.com/@dipakk", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Deepak Kumar (~dipakkr)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/getting-started-with-computer-vision-using-opencv~ejPPb/", - "title": "Getting Started with Computer Vision using OpenCV" - }, - { - "Content URLs": "Functional Programming Blog: Functional Programming 101 Took inspiration from Mary Rose Cook and her blog which moved me to write \nFunctional Cod", - "Description": "Introduction This is an intermediate level talk, that\u2019ll help the audience appreciate the Functional Programming Paradigm and how it can be helpful in the day to day scripts that we write.\nIt\u2019ll also touch upon how the concept of functional programming can help elevate the thought process. What can folks expect? To learn what the functional programming paradigm is. To develop the thought process of thinking \u201cfunctionally.\u201d How python can be used to write functional code How day to day work can be made quick and easy The focus of the talk What is functional programming? - 10 mins This segment comprises of exploring what first class objects are and how we\u2019ve been conditioned to think that just variables can be taken as first class objects.\nThen we move on to explore how even functions can be considered first class objects, and what prime features need be followed to be able to say that functions are first class objects. What are first class objects? - 5 mins This segment explains what first class objects actually are and gives a really brief introduction on what makes variables or functions be treated as first class objects. \nThis also include a live coding section, explaining how functions can be: Assigned to a variable Passed as a parameter Returned from another function How does Python fit in? - 10 mins This section showcases the different utilities python inherently provides to support functional programming. It explains how map, filter and reduce, fit in and used in our daily habit of writing code. This also will be accompanied by live code examples and scenarios that we face regularly. We dive a little into partials and look at the tip of the iceberg called decorators. The Whys and Wherefores of Functional Programming - 5 mins This is a segment about various real life experiences; situations where functional programming can be the right tool and where this should be a total no, no. \nLike they say \u201cRight horses for the right courses\u201d, this segment will cover where not to use functional programming and when this debate shouldn\u2019t be brought up. This segment will also cover what is the best place to bring in functional programming and its benefits", - "Last Updated": "08 Jul, 2018", - "Prerequisites": "You should have A basic Knowledge of Python Written about 1000 lines in Python A curiosity to learn more and get better ", - "Section": "Others", - "Speaker Info": "Farhaan is a Software Developer at Clootrack , a Bangalore base startup. He also contributes to FOSS projects and is lucky enough to have few documentation patch in Core Python. He used to heavily contribute to Pagure and still trying to make time to do the same. He actively maintains a blog and indulges in online discussion on twitter. He mentors students to contribute to Open Source Projects, he is also actively involved with Dgplug and is always up on IRC to have a quick discussion", - "Speaker Links": "Website: farhaan.me Functional Programming Blog: Functional Programming 101 Personal Blog Twitter: fhackdroi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Farhaan Bukhsh (~farhaanbukhsh)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-functional-programming-what-when-and-how~bkPNd/", - "title": "Python: Functional Programming - What, When and How?" - }, - { - "Content URLs": " Project source code: https://github.com/sunainapai/makesite Additional material such as slides will be shared after the session in a GitHub repository", - "Description": "The session is about a static site generator named makesite.py that is written in less than 125 lines of code. It is a single Python module that contains everything necessary to develop a static site or blog from scratch. There is no need to read any documentation to understand how it works. There is no need to learn how to write configuration files to produce some desired effect. With makesite.py : The code is the documentation. The code is the configuration. The talk would focus on: A brief code walkthrough of the project that shows how a simple static site generator can be built from scratch without a lot of effort. How this project can be used for your static websites or blogs. Agenda First 5 minutes: Introduction and background: whoami ? What do I do? Prior experience in Python. Problem to be solved: a static site generator written in shell script to be rewritten in a sane language. A new project idea: Write some Python functions to render my static site generator. Scope of the project. Next 15 minutes: Code walkthrough (<= 125 lines of code). A particularly nice pull request from another developer. How to use the project for your own static websites or blogs. Last 5 minutes: Announcing the project on Hacker News and reaction from Hacker News community. Lessons learnt from the experience. Role of the community as a motivator for small projects. What next?", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Basic knowledge of Python", - "Section": "Web development", - "Speaker Info": "Sunaina Pai is a software developer from Bangalore. She works on big data technologies during the day. In the evening, she dabbles in Python and Lisp to explore the beauty in programming", - "Speaker Links": " LinkedIn - https://www.linkedin.com/in/sunainapai/ GitHub - https://github.com/sunainapai/ Blog - https://sunainapai.in/", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sunaina Pai (~sunainapai)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/makesitepy-a-simple-lightweight-and-magic-free-static-siteblog-generator-for-python-developers~elPge/", - "title": "makesite.py - A simple, lightweight, and magic-free static site/blog generator for Python developers" - }, - { - "Content URLs": "http://prezi.com/89s2vr6bmar0/?utm_campaign=share&utm_medium=cop", - "Description": "I will be discussing how the use of Python in Africa has grown significantly since 2010 and how, as a result new innovation centers like the High Performance Center in Zimbabwe are beginning to build an industry using it", - "Last Updated": "04 Jul, 2018", - "Prerequisites": "no perquisites require", - "Section": "Others", - "Speaker Info": "Marlene Mhangami is the first African to have been voted onto the board of directors of the Python Software Foundation, the group organization behind the popular computer programming language Python. She is the Chair of PyCon Africa and heads up the Google's Women Techmakers Harare. \nMarlene is also the co-founder of ZimboPy an organization getting Zimbabwean girls excited about code. The organization has been working with girls around Harare to teach them Python programming and is excited about their progress. They also frequently host mentorship weeks and learning programs with local Universities including HIT, the UZ and CUT. Finally, Marlene is also the co-founder of the Purple Lipstick Trust a Zimbabwean non-profit organization that empowers young women to achieve their goals. The organization creates social media content and events that help girls make the best decisions about their lives.\nShe is excited about seeing technology and science used for social good. Marlene is interested in advocating for, and seeing software developer communities grow to create the best environments for innovation to happen! Minority representation in tech spaces is also something she is passionate about and hopes to be part of increasing", - "Speaker Links": "www.linkedin.com/in/marlene-mhangami-90a740130\ntwitter: @marlene_zw or @zimbop", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Marlene Mhangami (~marlene)", - "created_on": "04 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-growth-of-the-python-community-in-africa-and-how-zimbabwe-is-building-one-of-the-biggest-artificial-intelligence-labs-in-the-world~bWRQa/", - "title": "The Growth of the Python Community in Africa and How Zimbabwe is Building One of the Biggest Artificial Intelligence Labs in the World" - }, - { - "Description": "A/B testing is widely used to compare 2 alternatives of doing something in order to find out the best alternative. Typical A/B testing involves statistical hypothesis testing which is not intuitive. On the other hand, Bayesian methods are much more intuitive and are based on less assumptions. This talk aims to give a brief on how to do an A/B test with Bayesian methods using Python", - "Last Updated": "08 Jul, 2018", - "Prerequisites": " Basic understanding of Python Basic understanding of probability", - "Section": "Data science", - "Speaker Info": "Vaibhav Pawar is the head of analytics at Loylty Rewardz. He has 10+ years of experience in using data science to solve business problems across industries like banking, retail, airlines, insurance etc. in the areas of marketing, product, digital and consumer loyalty analytics. He has deep understanding of machine learning techniques and has hands-on experience in automating and deploying ML solutions at scale. He graduated from IIT Bombay in 2008. His master's thesis was in the field of Bayesian networks", - "Speaker Links": "https://www.linkedin.com/in/vaibhav-pawar-588391a", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Vaibhav Pawar (~vaibhav41)", - "created_on": "08 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/bayesian-ab-testing-using-python~bmP9a/", - "title": "Bayesian A/B testing using Python" - }, - { - "Content URLs": "Participants should know about the classification of text using ML and little knowledge about name entity recognization", - "Description": "So, there will be a simple reminder chatbot made by using a machine learning algorithms. There will name entity recognization and classification algorithms combined to have a chatbot work", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "tensorflow\nkera", - "Section": "Data science", - "Speaker Info": "I am AI enthusiasts. Love to make an end to end AI products", - "Speaker Links": "I am a chatbot developer. https://github.com/sam-a", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sambit Sekhar (~sambit74)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/making-of-chatbot-without-using-any-platform~enPWb/", - "title": "Making of chatbot without using any Platform" - }, - { - "Content URLs": "Pyqtlet: A library that integrates Leaflet into PyQt Source Code on Github Code for example applications using Pyqtle", - "Description": "Qt is a popular GUI framework used across industries for many different purposes. PyQt is the python wrapper around Qt , and thus it has access to all of the same features. Interestingly, Qt implements the code of Chromium Web Engine, which gives you all the power of a browser, and thus the functionality of any JavaScript library. For the purpose of this talk, we will discuss how to integrate LeafletJS ( a JS library for maps ) into PyQt , thus allowing apps written in native python to have beautiful interactive maps. Then we will go into further details of how to add these maps into simple apps. Finally, we will talk about how to integrate other JavaScript libraries into Python, and all the benefits this can bring", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " A familiarity with Front End Development concepts Beginner level JavaScript Experience with any GUI framework", - "Section": "Others", - "Speaker Info": "I am a developer at a Banagalore based start-up called Skylark Drones. As one of the few developers in the team, I get to don many hats across domains. I create POC web applications, work on internal tools dealing with GIS, automate processes involving large volumes of data flow and write code that runs on the drone itself. And that's just a typical week. I have been working in Python for over 2 years, and love it. The Zen of Python is essentially my life philosophy and I enjoy the simplicity and expressiveness that the language grants. My interests include: Biryani, Ultimate Frisbee and Hating on JavaScript", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Samarth Hattangady (~samhattangady)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/integrating-js-libraries-into-pyqt~boPBd/", - "title": "Integrating JS libraries into PyQt" - }, - { - "Description": "Blockchain is one of the most revolutionary technologies of our times, which is still maturing and with immense potentials yet to be realised. In essence, it is a distributed public database of records which opens rooms for cryptocurrencies and smart contracts to be built on top of it. While the internet is abuzz with blockchain, the concept is difficult to comprehend in its entirety. It lies at an intersection Game Theory, Cryptography, Network and Data Transmission, Economic and Monetary Value, and Trust Systems. It becomes difficult to wrap one's head around each of these domains and get a 360 view of the subject. The workshop tries to help the audience build a comprehensive understanding of the subject, with Python being the programming language. The attendees will leave with a complete picture of the moving pieces of the jigsaw puzzle that blockchain is, and by the end of it will be able to build their own blockchain, cryptocurrency and a smart contract POC on ethereum. The workshop is divided into three parts : Context Building - 45 mins Blockchain fundamentals and principles - 90 mins Coding a smart contract in Vyper (pythonic solidity) - 30 mins 1. Context Building : Basic of Game Theory - Introduction and the Iterated prisoner's dilemma (IPD), creating matches and tournaments using Axelrod python library Cipher encryption and decryption in python Demonstration of network fundamentals and internet data handling Evolution of money and trust systems and why bitcoin is not a mainstream currency When blockchain should be avoided Why decentralisation matters 2. Blockchain with Python: Understanding mining, incentives, payment records, and ownership Programming a basic prototype of a blockchain Adding a proof of work to our prototype Putting our prototype on a database Doing transactions on unique addresses Adding decentralisation to our prototype by distributing it over a network 3. Coding a smart contract with Vyper Understanding what a smart contract is Programming one with Vyper on Ethereum", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Intermediate understanding of Pytho", - "Section": "Others", - "Speaker Info": "Saket is founder-techie at Sosio . Sosio caters to the large-scale data needs of enterprises in payments, supply-chain, Ad-Tech, and non-profits. He has been programming in Python for over 10 years and has been semi-active in tech-conferences attending and delivering talks across the globe. In his personal capacity, he has introduced Python to more than 500 individuals and conducted training sessions at corporate houses like Oracle. In his previous life, he spent a good chunk of his time optimising computational mechanics algorithms. He is implementing blockchain with one of his supply-chain partners and would like to share his learning experience in the workshop", - "Speaker Links": "LinkedIn Twitter Github SpeakerDeck Medium Instagram", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Saket Bhushan (~saket)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/blockchain-and-smart-contracts-from-first-principle-in-python~epPpe/", - "title": "Blockchain and Smart Contracts from First Principle in Python" - }, - { - "Description": "Do you or your team write lots of services? Do you worry about the less glamorous bits about maintaining your service? Is your company growing aggressively and adding code in lots of different programming languages? Are you tired of writing HTTP clients for all your services in every programming language? Do you build your APIs with Python and then write HTTP client code in Java for your mobile apps? Do you want to deprecate your old API but are worried all your clients won't be able to keep up? - Then this is the talk for you. Did you know that you're not the only one who has these problems? Companies big and small struggle with these but most of them seem to have settled on how to approach them. In this talk we'll look at how we can structure our data for compatibility with our present and future clients using Protocol Buffers. We'll also learn how to communicate this data effectively to our clients using GRPC, with almost no effort spent on serialisation/deserialisation. We will also see how we can write services that can be consumed by non-Python clients and how we can consume services written in languages other than Python but without having to learn a new language or a clunky framework. The goal is to build a service that is easy to write, easy to consume and scales very efficiently as the problem grows. In short, we'll learn to do more with less. This will be a demo-driven talk with few slides. We will look at and write real Python code that gets things done", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Basic understanding of REST over JSON would be helpful, but is not necessary. We will cover the basics at the beginning of the talk. Basic understanding of Python classes would also be helpful, but is also not necessary. No other pre-requisites", - "Section": "Web development", - "Speaker Info": "Hi, I've spent almost all my adult life building distributed systems and understanding how they work. I've worked on interesting problems almost exclusively in a polyglot environment and this often reflects in the code I write or my approach to dealing with problems. I've debugged strongly consistent* key-value stores, run container orchestration systems at scale and broken my foot once from falling down a stairwell. I work with Grofers trying to make developers more productive and infrastructure more reliable. I look forward to seeing you at PyCon Indi", - "Speaker Links": " https://kasisnu.com https://www.linkedin.com/in/kasisnu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Kasisnu Singh (~kasisnu21)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/protocol-buffers-and-grpc-building-friendly-services~bq90b/", - "title": "Protocol buffers and GRPC - Building friendly services" - }, - { - "Description": "Submitting a proposal for to deliver a talk on \u2018EEG based Cognitive Brain Mapping using Python\u2019 under the broad area of signal processing. An intensive and in-depth theoretical and practical aspects in EEG signal processing for different research applications will be discussed. The development of a brain computer interface using EEG for control applications shall be explained with relevant research results. The demonstration to control the interfaced hardware using acquired brain signals via EEG shall be provided. The talk is intended for beginners in EEG signal processing but intermediate users will find it informative as well. Cognitive neuroscience is being widely explored these days to develop more interactive brain computer interfaces (BCI) particularly for device control applications. Neural driven BCIs are gaining importance while providing assistance especially to paralytic/ physically locked-in patients in order to restore a useful life. An attempt shall be made to explain that how a cognitive activity of human subjects and associated neural activation captured via electroencephalography (EEG) vcan be translated into action. A framework to develop an automated control application environment using Python shall be discussed in detail . The analysis of a multichannel EEG dataset acquired from human subjects shall be explained and discussed in Python environment to extract the relevant features to develop possible control applications via hardware interfacing through Arduino. The proposed methodology can be utilized to offer patients with severe motor neuron disorders an alternative means of communication and control over their environment via applications for neurorehabilitation of motor and cognitive functions", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Biomedical signal processing\nBasic Pytho", - "Section": "Others", - "Speaker Info": "Rashima Mahajan (PhD ECE)\nAssociate Professor\nFaculty of Engg and Technology\nManav Rachna International Institute of Research and Studies, Faridaba", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "rashima", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/eeg-based-cognitive-brain-mapping-using-python~er64e/", - "title": "EEG Based Cognitive Brain Mapping using Python" - }, - { - "Content URLs": "https://speakerdeck.com/siliconsenthil/how-we-built-heroku-like-paas-over-aws-with-just-pytho", - "Description": "We wanted an easier way of creating and deploying microservices implemented in different tech stacks. We wanted it as simple as PaaS platforms like Heroku. On the other hand, we did not want to miss the high level of customizability with IaaS like AWS. So, we blended the benefits of these two. i.e. utmost convenience with high-level of customizability. Instead of taking the route of Puppet, Chef, Ansible etc. , we built a CLI tool in Python that enables our developers to create & deploy service with a single command. We call this cloudlift :). It's been more than a year since we started using it and it's been fantastic. You will learn about our journey of building and using cloudlift", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Python Basics of AWS ecosystem", - "Section": "Developer tools and Automation", - "Speaker Info": "Converting human aspirations into reality via software has been my fascination and my job. \nHave been a programmer for more than a decade and leading teams for a while now. \nWorked at ThoughtWorks for 8 years. Currently, I lead the engineering team at Simpl. Have lead projects that are diverse in terms of tech stack and scale. Worked for enterprises and startups.\nInterested in talking about on design, technologies, the philosophical angle of tech etc.\nBelieve software building is a unique combination of science, art, and collaboration", - "Speaker Links": "http://siliconsenthil.i", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Senthil Velu Sundaram (~senthil13)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/how-we-built-heroku-like-paas-over-aws-with-just-python~avk0b/", - "title": "How we built Heroku-like PaaS over AWS with just Python" - }, - { - "Description": "Python 3.5 RC introduced type hints in the standard library, since then a lot of projects use Python hints in the code. The large open Python source projects like Zulip use it. For past one year, at work, I have been using Python type hints in the data pipelines and neural networks. The talk is based on the experience. In this talk, I'll cover the following topics. Code before and after using type hints. Advantages of using type hints Pain points of using type hints Developers view of using type hints Second thoughts of using type hints", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " You should possess familiarity with Python, and grasp of the type system.", - "Section": "Core python and Standard library", - "Speaker Info": "I'm kracekumar, working as software engineer for past seven years. My experience has been around building web applications, data pipelines, and automating servers. Currently, I work as a Software Engineer at minds.ai", - "Speaker Links": " GitHub", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kracekumar Ramaraju (~kracekumar)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/experience-with-python-type-hints~dwl1e/", - "title": "Experience with Python type hints" - }, - { - "Description": "Most of us use micro-services for all the goodness that they bring in. But there are some pain points too, to be addressed while using multiple micro-services. One of the them is testing. With all the micro-services as moving parts, how does one ensure that the whole app is coherent and well tested ? Is it enough if all the unit tests pass in each micro-service code base ? What else do we need to be confident in order to ship the code like a boss ? Outline of the talk Challenges in testing micro-services Consumer driven contract (CDC) tests - what are they, how they work ? How Pact works and what are the available tools in Python ? How are CDC tests simpler than integration tests ? Best practices in maintaining the pact file Demo: how to write CDC tests with Pact for a simple micro service", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Awareness of micro-service environments or APIs would be helpful", - "Section": "Developer tools and Automation", - "Speaker Info": "Devi is an independent software consultant and trainer with an experience of more than 12 years in the industry. She has been working with PowerToFly as a lead developer/architect. She has given a couple of talks at PyCon India, RootConf before, which were well received. She has done M.Tech in Computational Science from IISc, before which she tried out teaching mathematics. She spends her free time enjoying with her 2 daughters and painting with water colors", - "Speaker Links": " https://www.linkedin.com/in/asldevi/ https://powertofly.com/talents/devia https://speakerdeck.com/asldevi/rest-apis-at-pycon-india-2015", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "asldevi (~asldevi)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/testing-micro-services-made-easy~axm3b/", - "title": "Testing micro-services made easy" - }, - { - "Content URLs": "The content of the talk will be shared after the session in form of Github Repository", - "Description": "Deep Learning has revolutionized areas like Speech recognition. Recently, deep learning approaches have obtained very high performance across many different NLP tasks.\nIn this workshop, we will see the application of deep learning to common NLP Tasks and implementation in python using Keras Library. Agenda for the Talk: An Introduction to Deep learning - MLP, CNN and RNN and its implementation in Keras Discussion of Common NLP Tasks Language Modelling with RNN Word Embeddings - Word2Vec and Glove Sentence Embeddings - WMD and Doc2Vec Embed, Encode, Attend, Predict - Deep Learning formula for state of the art NLP Models Text Classification with 1D-CNN and LSTM Sentiment Analysis with Recursive Neural Network and Tree-LSTM Building Question Answering with Bi-Directional Attentional Flow Model Entity Extraction using Bi-LSTM and CN", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "A Basic Knowledge of Python, Machine Learning, Deep Learning and Natural Language Processing", - "Section": "Data science", - "Speaker Info": "Subramanya T A is Senior Data Scientist at Sentienz. He heads the Data Science team at Sentienz", - "Speaker Links": "LinkedIn Profile:\n https://www.linkedin.com/in/subramanya-t-a-7306a729/ Sentienz Website - http://www.sentienz.com", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "T. A. Subramanya Paddillaya (~t._a._subramanya)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/applying-deep-learning-for-nlp-using-python-workshop~dynEe/", - "title": "Applying Deep Learning for NLP using Python - Workshop" - }, - { - "Description": "Description \u201cTradition is not to preserve the ashes, but to pass on the flame\u201d. Running Python coding workshops in areas with unreliable internet access and with outdated hardware among the participants present a challenge for capacity building and knowledge sharing. Jupyterhub run in a local area network can bridge this gap and therefore make your workshops more resilient. Contents The talk will demonstrate how to set up and run a workshop successfully in an environment without internet access and the absence of uptodate hardware on real-life projects using Python, PySpark and Jupyterhub. Contentwise the session focuses on data science and the preprocessing of mobile phone metadata in order to extract features. The talk will include time for Q&A. Take aways What are the challenges running a coding workshop in adverse\n environments? How to set up a Jupyterhub in a local area network?", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Interest in spreading your own knowledge to people beyond the usual suspects", - "Section": "Data science", - "Speaker Info": "We are a young university spinoff project of the department of statistics of the Freie Universit\u00e4t Berlin, Germany called \u2018knuper\u2019. We work with governments around the world by augmenting official statistics with mobile phone metadata and other big data sources", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "knuper", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/coding-for-everyone-setting-up-coding-workshops-in-challenging-environments~azoZb/", - "title": "Coding for everyone - Setting up coding workshops in challenging environments" - }, - { - "Content URLs": " https://medium.com/@anandology/designing-restful-apis-671e091a2561 https://github.com/anandology/restful-apis/", - "Description": "APIs are all around. Everyone talks about RESTful APIs, but what does \u201cRESTful\u201d really mean? This hands-on workshop takes you through everything that you need to know to design great RESTful APIs. During the workshop, the participants will understand the key concepts behind RESTful APIs, critically examine some of the popular APIs, design an API from scratch and see how APIs evolve. We'll also take couple of popular APIs, rip them apart and design a better version of them. Participants will be divided into smaller groups to allow discussions and most of the time is spent thinking about the design. Please note that this is about designing APIs, and not about the tools. Participants will spend lot of time thinking about and designing API endpoints and request/response format, but will not write any code. OUTLINE Introduction to HTTP Internet vs. World-Wide-Web Key Concepts of Web URL, HyperText, HTTP Representational State Transfer (REST) What is REST? Thinking in Resources HTTP Methods Status Codes Resource Representation Examples of RESTful APIs Good and bad examples of RESTful APIs Designing an API version 0 - Naive CRUD API for blog posts. version 1 - blog api made RESTful version 2 - add support for tags version 3 - add support for comments version 4 - add suport for authors Authentication and Secutity Introduction to authentication patterns Study of Basic Auth, OAuth, access keys and JWT Adding authentication to the blog API Excercises Best Practices Pratical tips and tricks Versioning APIs Documenting APIs ", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "The workshop is targeted at web developers interested to build APIs. The participants are expected to have good understanding of how web works", - "Section": "Web development", - "Speaker Info": "Anand has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, rorodata , which he recently co-founded. He regularly conducts advanced programming courses through Pipal Academy . He is co-author of web.py , a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive", - "Speaker Links": " https://anandology.com/ https://pipal.in/trainers/anand https://github.com/anandology", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Anand Chitipothu (~anandology)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/designing-restful-apis~aAx3e/", - "title": "Designing RESTful APIs" - }, - { - "Description": " Introduction to ensembling techniques About XGBoost Parameters and their tuning Application using python Latest updates", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Basic knowledge of python and machine learnin", - "Section": "Data science", - "Speaker Info": "Ina Jain is currently working as a Data Scientist in Pramati technologies and has 6+ years of industry experience", - "Speaker Links": "https://www.linkedin.com/in/inajain27", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "ina jain (~ina)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/xgboost-tree-based-ensembling-technique-using-python~dBykb/", - "title": "XGBoost - Tree based ensembling technique using Python" - }, - { - "Content URLs": "Slides Ur", - "Description": "Ever wanted to play your favourite song on guitar quickly even when you don\u2019t know how to play guitar? Our Python based MIDI to guitar tabs Transcriber can help you do that: \u2022 Find your song in MIDI format (with .mid as file extension) \u2022 Let our Python Transcriber do its magic \u2022 Enjoy the tablatures Transcribing MIDI files directly to tablature creation ready JSON A lot of people take to learning the guitar every year. But most of them give up mid-way because of one or more of the following reasons: Guitar is a difficult instrument to learn People want to learn guitar by playing songs but are unable to do so right from the beginning Results are often not visible immediately depending on a person's existing knowledge of music and willingness to learn guitar Enter Python Though it seems to be quite easy to manually create and make the app read guitar tablatures for songs, the following challenges need to be addressed: Readiness of the output to support playback of a song along with tablatures - this essentially means storing the timing for each note/chord (when many notes are played together) in order to play the song exactly as it is The whole process would be incredibly time consuming In order to overcome these challenges, a simple yet efficient solution was derived - to convert a MIDI file directly into guitar tablatures. Python was chosen for implementation of the solution for the following reasons: Python has a very efficient and time saving file I/O mechanism and the current use case operates completely on MIDI files and the Transcriber outputs a JSON file, which in turn is served to the client. More libraries to read MIDI files and present them in an understandable manner than any other language and their ease of use. These libraries, when used in conjunction with each other offer all the features that Java's javax.sound.midi package offers. Availability of renowned libraries such as numpy and scipy for the algorithm to determine most optimal finger positions A plethora of options for using a server side framework to host the Transcriber as a service Since Python is an interpreted language, it is really useful for quick experimentation with tools like IPython unlike languages like Java in which complete programs need to be compiled beforehand. This saved us a lot of time. ...Where Credit is Due The solution could not be achieved without the use of the fantastic libraries used below for reading MIDI files: Mido by olemb Python Midi by vishnubob music21 by Prof. Michael Scott Cuthbert (MIT) The authors have our gratitude. How the Transcriber Works The high level working of the Transcriber is as follows: MIDI files are read and all the guitar parts in the song (commonly referred to as guitar tracks ) are extracted in the form of notes and chords An algorithm calculates the best possible finger placement on the guitar fretboard for these notes and chords A time driven JSON is generated for use by any platform that can parse JSON to do one or more of the following: Play the song Display guitar tabs in sync along with song playback Only display guitar tabs Why Use the Transcriber? Some work has already been done in this area and there are existing open source solutions like TuxGuitar and a few others. But the Transcriber here produces up to 70% better results than any of these solutions. By better , the following is meant: Transcriber generates more easily playable tablatures The tablatures also mimic up to 60% of most of the original tablatures", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Core python Ability to integrate and use third party libraries", - "Section": "Core python and Standard library", - "Speaker Info": " RIshabh Shah Rishabh has around 4 years of python programming experience, he has developed an array of applications of which one was this Transcriber. Inputs from real world guitar players have been quite useful while developing the Transcriber. He developed this transcriber with one of his colleagues Srinivas Kalyani\n 2. Srinivas Kalyani Srinivas has around 3 years of technical experience with nearly 1.5 years of experience in Python. He has worked primarily on Django and entered the world of Core Python while writing the Transcriber", - "Speaker Links": "A list of few of our blogs can be found as follows: Rishabh: A Guide On Building REST API\u2019s Using Python Frameworks Slash Down Your Hosting Costs By 95% On Google App Engine Finding Your Google App Engine Hosting Costs Too High? Here\u2019s How To Fix It Srinivas: Need A Web Scraper? Here\u2019s How To Build One Using SCRAPY AND XPATH", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rishabh Shah (~rishabh104)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/learn-guitar-via-python-programming-midi-parsing~bDAyd/", - "title": "Learn Guitar Via Python Programming (MIDI Parsing)" - }, - { - "Content URLs": "You can view my blogs 1. Women and Data Science 2. Quantization and need for TPUs 3. Application of signal processing in machine learning You can view my various slides her", - "Description": "Imagine a play in a small theatre, where you are a producer sitting with the audience. Let us suppose the actors are weights and there are rows and rows of TPUs/GPUs behind. The director has assured you that they have rehearsed the play about 10 times, now all you do is pray that the performance goes well\nImagine you have 100 different tasks to be performed backstage, but the theatre given to you is really tiny. How will you manage? The answer is by optimizing the tasks. Divide tasks between individuals in such a way that you require less time and space. But how do you manage that with a neural network? How does quantization affect neural computations? When you are dealing with a large amount of data, one has to keep in mind the ever-changing values that one might obtain. Especially, signal data with large SNR (Signal to Noise Ratio) in them, which causes different sets of data to be produced. The best way to deal with such signal data is to apply truncation or rounding off such values, typically making it a many-to-few mapping. This mapping happens from 32-bit(at training) to 8-bit(at inference). On the other hand, traditional Internet of Things (IoT) infrastructures has two main parts \u2013 the edge and the cloud. The edge is the part of the system that is closest to the source of data. It includes sensors, sensing infrastructures, machines, and the object being sensed. The edge actively works to sense, store, and send that data to the cloud. So how does quantization help with edge computing? Does it have the potential of changing how we run models on the cloud? TALK AGENDA Introduction: 5 mins A Beginner's Guide to Quantization: 5 mins Understanding Quantization in TPUs: 10 mins Demo: Implementation of Quantization in Edge computing: 10 mins", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Knowledge on Tensor Processing Unit . Knowledge of IoT and Edge Computing Knowledge of Deep Learning", - "Section": "Embedded python", - "Speaker Info": "I am a fresher from SRM Institute of Science and Technology. I understand that engineering is not everyone's cup of tea and that everyone has a different perception of it. During my second year of study, I realized that for me education was something that was present beyond books and into practical applications. So I collaborated with a few other mates in college and started this place called the Next Tech Lab which was involved in cutting-edge innovation and novel research ideas. As a few of my achievements that the lab made me achieve included winning the Smart India Hackathon 2017 as the first prize under Ministry of Steel for using machine learning to detect power theft in India. Recently I was invited to the WiPDA conference in Xi'an China for presenting my work in GaN modeling of devices using machine learning, a collaboration with the University of Cambridge. I have around 3 IEEE Xplore Paper s (https://ieeexplore.ieee.org/document/8293259/)and 1 Elsevier papers for my contribution to electrical and machine learning fields As a lab, we have done so much more to protect gender diversity even among the strength of 200 members keeping a ratio of 50:50. We were portrayed for accomplishments by the News 18 in a short video. Over the past 6 months, I have had the opportunity to work and intern at Saama Technologies where I research on Machine Learning in order to accelerate clinical trials. A part of this work has exposed me to how models are necessary to be optimized across all devices big or small", - "Speaker Links": "My various talks in meetups in chennai 1) A Glance into Image Recognition of Cursive Text using OCR . 2) A Beginner's Guide to Machine Learning-Women Who Code Chenna", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "archana iyer (~archana52)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/quantiziting-of-neural-networks-for-edge-computing~eEBYa/", - "title": "Quantiziting of Neural Networks for Edge Computing" - }, - { - "Content URLs": "Rough draft of slide", - "Description": " tl;dr : As data becomes increasingly extensive, it becomes important to move your models away from the cloud to where your data is being generated to reduce latency, increase security and save internet bandwidth. This talk will be about how you can run trained TensorFlow models on Edge devices and how you can use Edge Computing accelerators like the Neural Compute Stick to make your models run even faster. Long Version There are a lot of very compelling reasons for shifting computations away from the edge and into the cloud, with the most important being latency issues. Here, latency refers to the time it might take to send data to a server and then receive the response. The few seconds of delay caused by this might not be a problem for your smart home applications, but when in an industry, those few precious seconds, or even microseconds can cause a machine to breakdown or even take lives. Furthermore, many industrial processes might be happening in places where running an internet line may not be possible: a mine, for example. And even if having an internet connection is possible, most companies are hesitant to send data over an internet connection and risk exposing their data to hackers prompting them to keep their data in-house. Finally, if you have a lot of sensors, you will probably be streaming data in the order of gigabytes every hour. It does not make sense for companies to pay for the bandwidth to send that much data when most of it will be discarded anyways. Thus it is important to shift all that computation to where the data is being generated. This talk will be about how to move your existing TensorFlow models to Edge devices like Raspberry Pi's. The talk will also introduce other Edge Computing hardware like the Neural Compute Stick to make your models run even faster on Raspberry Pi. Why Attend this talk This talk will give the audience an understanding of Edge devices and Edge Computing. You will also learn the best practices to deploying models on the Edge. The live demo's will also give the audience an idea about how to run TensorFlow models on embedded devices. Topics covered: Edge Computing and Raspberry Pi - 5 Minutes TensorFlow Models - 5 minutes Demo on how to run models on the Edge - 10 minutes Demo with Benchmarking tests - 5 minutes Q/A - 5 minutes", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Python 3.5 TensorFlow 1.7", - "Section": "Embedded python", - "Speaker Info": "I have been working in the field of ML for the last year. I am currently working as a Deep Learning Research Engineering Intern at Saama Technologies, where I am using TensorFlow to reduce the time taken for clinical trials and help get patients medicines quickly. My primary work was with the University of Cambridge. There I used TensorFlow to create a model that can optimize the design of Gallium Nitride circuits. This work was published in one of the world's largest conferences on Power Electronics - WiPDA . In my second year of UG studies, I realized that engineers should have more practical knowledge. I started a student-run cross-disciplinary research lab called Next Tech Lab . As a part of the lab, I won the Smart India Hackathon for creating an app that could be used to detect electricity power theft . I have also published many research papers in IEEE and Elsevier . I am also an active member of the Indian Deep Learning Community . I also write articles such as this one: convolutional filter types and Data Correlation and Machine Learning . I believe in spreading knowledge and teaching others about Machine Learning", - "Speaker Links": " Links to slides for my talks - here Links to talks and github- here Website - csoham Medium articles - here LinkedIn Saama blog", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Soham Chatterjee (~soham48)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/running-tensorflow-models-on-a-35-device~dGELa/", - "title": "Running Tensorflow models on a $35 Device" - }, - { - "Description": "If you\u2019ve been using python for any length of time, you know it as this versatile tool that can be used to build almost anything, and in a very friendly way. But Python use in the large codebase arena is very different from Python for a small service. What if you knew that that shift was due? What if you knew that the next project you started was definitely going to be collaborated on by a hundred developers? Let\u2019s look at these differences and prepare ourselves and our codebases for that shift. We\u2019ll learn how: Maintaining large codebases isn\u2019t free, and how the Python ecosystem\n supports you in your efforts. Testing a large application isn\u2019t easy, and how to use the latest and\n greatest testing methods to make sure your code does what you expect\n it to. Immutable data structures aren\u2019t just easier for humans to process,\n but also for machines to validate. Python has learnt from its neighbouring languages, and now has a type\n system that is here to help.", - "Last Updated": "09 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/reliable-code-what-the-giants-have-taught-us~dJRJd/", - "title": "Reliable code: What the Giants have taught us" - }, - { - "Description": "Do you use isinstance() frequently and know there is a better way, but you just don\u2019t know how? Have you been bitten from using mutable arguments to functions? Python has an interesting data model as a dynamic language. This model shapes the programs you write and a good understanding of this goes a long way in writing effective code.\nThis talk covers the various approaches you could take to handle the behaviour of your objects from duck-typing to the new dataclasses introduced in Python 3.7 .\nWe will also take a deep dive into the Python data model itself and see how we can leverage it to give intuitive APIs to our libraries. All the benefits of having a thought out data model apply. Your code can be cleaner and easier to test. \"Bad programmers worry about the code. Good programmers worry about\n data structures and their relationships.\" - Linus Torvalds \"Show me your flowcharts and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won\u2019t usually need your flowcharts; they\u2019ll be obvious.\" - Fred Brooks", - "Last Updated": "09 Jul, 2018", - "Section": "Core python and Standard library", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-type-system-building-an-effective-mental-model~aKRMe/", - "title": "Python Type System: Building an effective mental model" - }, - { - "Description": "Static code checking should be easy, but in practice, it\u2019s easy to be overwhelmed by the volume of tools available, and disappointed with the returns on time spent integrating. The world of static code analysis has evolved a great a deal and appears to be underutilised for Python. Here are some of the things we are going to cover: Linting - automate your code reviews Measuring test coverage - legacy code is that which is not tested Security checks - what can you get for free? Static type checking with a dose of gradual typing Dead code analysis - reduce the noise Setting up an effective CI pipeline - aiming for less process and more results Setting up productive developer environments - leverage code completion and type hints", - "Last Updated": "09 Jul, 2018", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-static-code-checking-asymptotically-approaching-perfection~dLRXa/", - "title": "Python static code checking: Asymptotically approaching perfection" - }, - { - "Content URLs": "Slides: https://slides.com/yashmehrotra/distributed-tracing/ Github Repository to be added soo", - "Description": "This talk would be about our journey to successfully trace every request in our Python-based microservice Architecture. An outline of the talk: Why distributed tracing ? How distributed tracing works at a glance ? Distributed tracing using Python Insights you can gather from distributed tracing Performance Observability Easily debugging microservice failures", - "Last Updated": "09 Jul, 2018", - "Prerequisites": " Basic knowledge about python based web applications An idea about microservice architecture Unhappiness with existing inter-service debugging tools ", - "Section": "Others", - "Speaker Info": "This talk will be given by Yash Mehrotra. He is currently working at Grofers where he is a part of the Search Team. He has also interned at HackerEarth, AdWyze and is a former Mozilla Winter of Security Participant. He recently acquired a keen interested in distributed systems and loves to beat people at FIFA in his free time", - "Speaker Links": "Website: https://yashmehrotra.com/ Github: https://github.com/yashmehrotr", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Yash Mehrotra (~yash2)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/distributed-tracing-for-your-python-based-microservice-architecture~aM6Ob/", - "title": "Distributed Tracing for your Python-based microservice architecture" - }, - { - "Description": "In recent times, we have seen a startling rise in data aggregation and reliance on machine learning models. This has grave consequences when our data is not protected and when model behaviour is deliberately modified. Differential Privacy is a privacy aware sampling technique that ensures that no one individuals property can be extracted from the model. Adversarial examples look similar to real images but are engineered in such a way that they result in nonsensical predictions from ml models. Recent research has shown that the issue of adversarial attacks on machine learning models could be solved by using differential privacy. This talk aims to introduce differential privacy, adversarial examples and introduce the audience to the vibrant python research community around these topics", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "An understanding of how neural networks wor", - "Section": "Data science", - "Speaker Info": "I'm Sadhana Srinivasan, I did my master's in Mathematics from BITS Pilani. I've been coding in python and working in machine learning for the past 3 years, having taught deep learning and machine learning courses at BITS. I interned at EY working on chatbots for analytics. I'm currently a research engineer at Saama Technologies working on AI based solutions for the healthcare industry", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Sadhana Srinivasan (~rotuna)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/differential-privacy-and-adversarial-examples~dNyDb/", - "title": "Differential Privacy and Adversarial Examples" - }, - { - "Content URLs": " https://speakerdeck.com/anandology/deploying-ml-apps-in-minutes https://github.com/rorodata/firefly https://github.com/rorodata/rorolite https://github.com/amitkaps/full-stack-data-science", - "Description": "Often, the most convenient way to deploy a machine model is an API. It allows accessing it from various programming environments and also decouples the development and deployment of the models from its use. However, building an good API is hard. It involves many nitty-gritties and many of them need to repeated everytime an API is built. Also, it is very important to have a client library so that the API can be easily accessed. If you every plan to use it from Javascript directly, then you need to worry about cross-origin-resource-sharing etc. All things add up and building APIs for machine very tedious. In this talk demonstrates how deploying machine learning models an APIs can be made fun by using right programming abstractions. The talk presents the couple of open-source libraries firefly and rorolite created to solve this very problem and also shares the experience of building cloud-based PaaS platform that addresses these issues", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "The participants should have understanding of machine learning models and APIs", - "Section": "Data science", - "Speaker Info": "Anand has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, rorodata , which he recently co-founded. He regularly conducts advanced programming courses through Pipal Academy . He is co-author of web.py, a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive", - "Speaker Links": " https://anandology.com Firefly documentation Rorolite documentation", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anand Chitipothu (~anandology)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/machine-learning-as-a-service-how-to-deploy-ml-models-as-apis-without-going-nuts~aOzYe/", - "title": "Machine Learning as a Service: How to deploy ML Models as APIs without going nuts" - }, - { - "Content URLs": "Example of one of our outputs:", - "Description": "Have you ever wondered how snapchat filters work? In this talk we will give you a thorough explanation and demo of the famous face swap filter using OpenCV, dlib and NumPy. Talk Summary: We will do a line-by-line walkthrough of our code to extract facial landmarks of both images using methods like convex hull and delaunay triangulation. We then swap faces of the two input face images and blend them using the seamlessclone method. We will also go through various computer vision concepts required to understand the underlying mathematics. Outcome: After this talk you would be able to learn how to do the above mentioned tasks and some insights into a few OpenCV methods and we will also go over a little bit of numpy basics. Agenda: Introduction and live demo [5 min] Explanation of facial landmark detection methods [5 min] Overview of functions used in our code [5 min] Line by line walkthrough of the code [10 min] Questions from the audience [5 min", - "Last Updated": "09 Jul, 2018", - "Prerequisites": "Love for Python, Familiarity with Python3 synta", - "Section": "Others", - "Speaker Info": "Sarvesh Shroff: I am currently a sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. I have won a national level robotics championship held at IIT-R. Miran Junaidi: I am MTH Junaidi, sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. Also gave a lightning talk at PyCon Taiwan 201", - "Speaker Links": "Sarvesh Shroff: GitHub LinkedIn Miran Junaidi: GitHub LinkedI", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Sarvesh Shroff (~sarvesh77)", - "created_on": "09 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/creating-your-own-snapchat-filter-using-opencv~dPA1e/", - "title": "Creating your own Snapchat filter using OpenCV" - }, - { - "Description": "Monitoring and alerting are essential components of any system. As the number of services grow, monitoring all of them all the time becomes a mammoth task in itself. Hence, there's always a need for having an intelligent system to monitor other systems\u2019 behaviour and notify the appropriate stakeholders when an anomaly occurs.\nHere are some of the things I am going to cover: The need for effective anomaly detection in systems monitoring. System metrics that matter to you - CPU, memory, disk, etc Using StatsD and CollectD for data collection. Building a useful data pipeline Using PySpark for real time data processing Using NumPy and SciPy for business intelligence Implementing anomaly detection algorithms.", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Participants should have some basic knowledge of systems monitoring. Having used tools like New Relic, Grafana would be an added advantage. Basic knowledge of streaming data and Kafka would also be useful", - "Section": "Data science", - "Speaker Info": "I am an Engineer at Grofers. Worn multiple hats throughout my career starting from Full-stack Engineering, to Backend, to Data, and now to Release Engineering. Co-founded crowdsource logistic platform DbyT. Worked as a Programmer Analyst at Virginia based RTS Labs and as a Salesforce Consultant for Richmond based MCIM. Worked with clients from Healthcare, Mission Critical, Datacenter management, Payments industries", - "Speaker Links": "https://medium.com/@sharmaNK/ https://www.linkedin.com/in/nand-kishore-sharma-49902219/ https://github.com/sharmaN", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "nandkishore sharma (~nandkishore)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/real-time-system-monitoring-using-pyspark~aQB0b/", - "title": "Real time system monitoring using PySpark" - }, - { - "Content URLs": "I will upload the Slides after the talk", - "Description": "In this talk I want to cover the following topics around Test Automation : Generating python REST API Client with swagger codegen. Automating the python REST API Client generation using swagger spec. Writing automated API Tests/Functional tests (which consume the API\n Client libraries) using pytest as a test runner. Dynamically installing the REST API client and executing the tests\n in the CI pipeline - Jenkins. Invoking the Tests and including them in product\n qualification via the CI Pipeline - Jenkins. ", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Familiarity to REST APIs. Familiar with Test Runner pytest - https://docs.pytest.org/en/latest/ Basics of CI - Jenkins - https://jenkins.io/", - "Section": "Developer tools and Automation", - "Speaker Info": "I am a software test automation engineer and a python lover", - "Speaker Links": "https://linkedin.com/in/hemamalini-rengarajan-55248a", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "HemamaliniRengarajan", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/automated-rest-api-client-generation-and-test-execution-in-ci-pipeline~dRDOa/", - "title": "Automated REST API Client generation and Test execution in CI pipeline" - }, - { - "Description": "SecureDrop is an open-source whistleblower submission system that media organizations can use to securely accept documents from and communicate with anonymous sources. It was originally created by the late Aaron Swartz and is currently managed by Freedom of the Press Foundation. In the modern age of Internet, keeping privacy in the online world has become a bigger battle ground. It became an even bigger challenge for the journalists, lawyers, and anyone else who is dealing with sensitive material. Whistleblowing and leaking have dominated news coverage in recent years. SecureDrop (a Python application) project provides a reasonably safe way for the journalists to receive tips/sensitive materials from anyone, and still safeguarding the sources and keeping the materials secured. SecureDrop also won The Award for Projects of Social Benefit from Free Software Foundation in 2016. This talk will be divided into three sections, why, how and what is in future. Introduction How is SecureDrop working in newsrooms? The top view of the technical stack (Flask application + rest of the stack) Tips for web developers thinking about privacy What are the biggest challenges and threats? What is in future? (SecureDrop workstation project: explaining the new PoC workstation using Python on QubesOS). As a project SecureDrop has many different parts running in different systems. This talk will provide an overview of the technical backgroud of the project, and will try to help the curious minds to go a step ahead to contribute or use the similar ideas in the other applications", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Non", - "Section": "Others", - "Speaker Info": "Kushal Das is a regular speaker in various conferences. He is a CPython core developer and director at The Python Software Foundation.\nHe is currently working on SecureDrop project full time as a staff member of the Freedom of the Press Foundation ", - "Speaker Links": " https://kushaldas.in https://github.com/kushaldas", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kushal Das (~kushal)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/securedrop-the-open-source-whistleblower-submission-system~eVKva/", - "title": "SecureDrop, the Open Source whistleblower submission system" - }, - { - "Content URLs": "The slides accompanying the talk, along with all the examples may be found at RJ722/reducing-dead-code . Other useful links: RJ722/example-vulture displays an example on how we can integrate vulture with CI tests. vulture coala.io ", - "Description": "Maintaining a high level of code quality is important for any serious project. One aspect of this is ensuring that all code is actually used. There are many reasons for dead code ending up in a project. The most common is refactoring, but another is misspellings, which are only detected at runtime for dynamic languages. Finding and removing dead code allows to keep the code base clean and reduces bugs. This talk is focussed on how we can use Vulture to find dead code. It helps you find unused code in Python programs and it is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python's dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused. Nonetheless, Vulture can be a very helpful tool for higher code quality. One part of this talk is to discuss how to automate testing for dead code with Vulture. There are quite a few options available: Adding vulture to your continuous integration testing. A script using the Vulture API for custom tests. Identifying false positives and creating whitelists VultureBear : Integration with coala - a static code analysis tool. This talk is a revised version of a similar talk given at PyCon India 2017 (by the same speaker)", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " python and pip installed Optional requirements: coala coala-bears", - "Section": "Developer tools and Automation", - "Speaker Info": "Rahul Jha He is currently pursuing B.Tech. (ECE) from Zakir Husain College of Engg. & Technology, Aligarh Muslim University. He develops free and open source software. His key contributions in the Vulture community include the vulture API, and the whitelisting scripts . Apart from computers, he likes playing with Robot Cars and editing Wikipedia pages", - "Speaker Links": "You may find more about Rahul here: https://rj722.github.io https://github.com/RJ722 https://twitter.com/rahul722j You may contact him through: e-mail: rahul722j@gmail.com IRC: #vulture on freenode (nick: RJ722)", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Rahul Jha (~RJ722)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/scavenge-dead-python-bits-with-vulture~bWXQd/", - "title": "Scavenge Dead Python bits with Vulture" - }, - { - "Description": "You\u2019ve heard a lot about concurrency. Asyncio has been in the standard library for a while, and concurrency is picking up mindshare. Why does the world suddenly care so much about concurrency? How did people write concurrent code before asyncio? Do we still need multithreading, multiprocessing, Gevent, Tornado, etc now that asyncio is here? You\u2019ve also heard about the GIL. Supposedly, it doesn\u2019t let you write parallel programs - so why does Python have it? We\u2019ll also discuss the kinds of problems that can be solved faster with concurrency and the kinds of problems that definitely can\u2019t. Let's answer all these questions and more in this light, demo-driven talk", - "Last Updated": "10 Jul, 2018", - "Section": "Core python and Standard library", - "Speaker Info": "I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration.\nI have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python", - "Speaker Links": "LinkedIn githu", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Madhukar Mishra (~madhukar93)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-python-concurrency-story~eX25b/", - "title": "The Python concurrency story" - }, - { - "Content URLs": "Will update soo", - "Description": " playing makes learning fun. And how do you make learning mathematics fun? Obviously playing with mathematical abstractions. Early days people used to play with mathematical objects using pen and paper. But imagine playing with repetitive things using pen and paper. That will make it boring soon, won't it? in this talk I will show you how python can be used to make simple to advanced iterative mathematics fun. Yes you are reading it right. From shuffling of a deck, sequences of numbers, calculus these are few steps of our journey through iterative mathematics using python. I will be using basic python data structures , list comprehensions, and some functional programming aspects to demonstrate this. \n\u200c take aways from this talk - if you are a maths enthusiast , you will understand how to write python code to solve your problem. If you are a programmer you will understand how do you make use of simple python functionality to do recreations in mathematics.", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "School level mathematics and zeal for recreational mathematic", - "Section": "Core python and Standard library", - "Speaker Info": "Vikrant has over 12 years of experience in crafting software solutions. He conducts python trainings through pipal academy. He has worked on diverse areas like Computational Fluid Dynamics, mathematical algorithms for bioinformatics, network-based license servers etc. He has worked at Strand Life Sciences and DRDO. He has a Masters in Computational Science from Indian Institute of Science", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "vikrantpatil", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/adventures-in-iterations~bYNMd/", - "title": "Adventures in iterations" - }, - { - "Content URLs": "https://docs.google.com/presentation/d/19inq4BNUi3U74uIBz-nN7gSVOvtC9S4s-FBW0Im1gUg/edit?usp=sharin", - "Description": "Master data is at the heart of an efficient and effective modern business.Master data management (MDM) is the effort made by an organization to create one single master reference source for all critical business data, leading to fewer errors and less redundancy in business processes. The real challenge is the real world data is messy and it's difficult to make a decision out of this data. There are lot of records which can be duplicates or have the same entity references which leads to ambiguity and resource consumption. Entity resolution (ER) is the task of disambiguating records that correspond to real world entities across and within datasets. Problems associated with entity resolution are equally big\u200a\u2014\u200aas the volume and velocity of data grow, inference across networks and semantic relationships between entities becomes increasingly difficult. Data quality issues, schema variations, and idiosyncratic data collection traditions can all complicate these problems even further. When combined, such challenges amount to a substantial barrier to organizations\u2019 ability to fully understand their data, let alone make effective use of predictive analytics to optimize targeting, thresholding, and resource management. Dedupe it's a modern day python library for entity resolution, which works on machine learning algorithms to perform Deduplication and Record Linkage", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic Knowledge of Python and Basics of Machine Learning Classifiers like LR,KNN, DT etc.", - "Section": "Data science", - "Speaker Info": "Vinay is working as a Data Scientist and he loves creating the Data Driven Applications and really love working with the messy data and cleaning it to implement Machine Learning Models to the new age applications. In his leisure time he blogs on Kanoki.org and writes articles on Data Science central.\nHe is an Electrical Engineer from an academic perspective and earned certificate in Data Mining from Indian Statistical Institute and currently pursuing his masters in Statistics. He has delivered talks in the past in PYCON - New Delhi and other conferences Internationally. Beside Data, he is a passionate cyclist and rides 100KM average in a week", - "Speaker Links": "personal Blog: https://kanoki.org/ Pycon-2016: https://www.youtube.com/watch?v=ADjRj6qPF7o&t=29s Selenium Conference 2016: https://www.youtube.com/watch?v=mS3dzczv1ZQ&t=9", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "vinaybabu", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/demystifying-mdm-entity-resolution-using-dedupe~eZNwe/", - "title": "Demystifying MDM & Entity Resolution using Dedupe" - }, - { - "Description": "We propose to build a deep neural network model that can learn to mimic the handwriting of an individual. Given an input text, the model will learn to synthesize the same but in the form of handwritten text", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Curiosity and willingness to learn something new. :)", - "Section": "Data science", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Deepayan (~Deepayan137)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/teaching-machines-to-write~e1PVd/", - "title": "Teaching machines to write." - }, - { - "Description": "Many people are moving towards machine learning and artificial intelligence in python without even knowing the basics of the language.\nI would like to focus on the point of knowing the core basics of the language including its syntax and basic commands. After knowing the basics can only a person learn other details of the language. I would after explaining the basics like to focus on some standard libraries like numpy, pandas and matplolib and how they help in data visualisation", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Non", - "Section": "Core python and Standard library", - "Speaker Info": "I am Prabhleen Kaur Bindra, currently pursuing a bachelor's degree in computer science and engineering, from government college of engineering, Aurangabad. I moved towards python from the last 2 months as I developed my interest towards artificial intelligence especially machine learning. I am a novice to the python environment and do not know much details of it though. I would like to share my experience of python", - "Speaker Links": "https://www.linkedin.com/in/prabhleen-b-538ba210", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "prabhleen bindra (~prabhleen)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/python-baiscs-and-some-standard-libraries~eplpe/", - "title": "Python baiscs and some standard libraries" - }, - { - "Description": "What is Language Model ? Language Model is basically a way to determines how likely a certain sentence is in the language. \"You are reading my LM write up now \" is more likely to be said than \u201cNow you are my LM reading write up\u201d , even though both sentences contain only correct English words; and the sentence \"I had ice-cream with a\" is more likely to end with \"spoon\" than with \"banana\" . LM helps impart this understanding of a language to machines. What\u2019s the need? \"Computers are incredibly fast, accurate and stupid; humans are incredibly slow, inaccurate and brilliant; together they are powerful beyond imagination.\" (Albert Einstein) Computers don\u2019t understand our language! All they are programmed to understand are very specific instructions. Languages we speak are much more complex than that; you can say one thing in multiple ways, for example \"where do I go for party tonight?\" and \"could you give me name of the best restaurant near me?\" -- this is called language variability. As if this was less burden to translate to computers, sometimes you say something that can have several meanings, like \"Look at the dog with one eye\" -- this is called language ambiguity. A human being usually understands the correct meaning in the context of the conversation. A computer... doesn't really. There are many amazing work already done in the field with Siri autocompleting what you forget to type or Google responding to your \u201cokay Google\u201d calls. This said, there still exists immense room for research in the field of making these models more and more intelligent, be it in disambiguation, intent understanding etc. The basis of all starts from a language model. Types Language model is broadly of two types: Statistical LM: A language model is formalized as a probability distribution over a sequence of strings (words), and traditional methods usually involve making an n-th order Markov assumption and estimating n-gram probabilities via counting and subsequent smoothing (Chen and Goodman 1998). The count-based models are simple to train, but probabilities of rare n-grams can be poorly estimated due to data sparsity (despite smoothing techniques) Neural LM: The use of neural networks in the development of language models has become very popular, to the point that it may now be the preferred approach. The use of neural networks in language modeling is often called Neural Network based Language Models, or NNLM for short.\nNeural network approaches are achieving better results than classical methods both on standalone language models and when models are incorporated into larger models on challenging tasks like speech recognition and machine translation. What does it take to build a language model? A corpus large enough to contain multiple variations possible and a good model :D Sample Use cases Autocorrect Automatic summarization Automated reply to emails Spell Corrector (Grammarly)", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic idea of NLP Concept of tokenization, lemmatization etc. Just a skim through read of n-gram modeling(if possible, else what use will I be of :P) Basic python coding Scikit learn, NLTK libraries of Python", - "Section": "Data science", - "Speaker Info": "Data Scientist with ~4 years of experience. For more info, please pay a visit to my LinkedIn", - "Speaker Links": "https://www.linkedin.com/in/divyachoudhary28", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Divya Choudhary (~divya798)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/language-model-text-analysis-using-python-from-scratch~bqm0b/", - "title": "Language Model (Text Analysis) using Python from scratch" - }, - { - "Content URLs": "https://github.com/bhoom10 https://www.linkedin.com/in/bhoomika-agarwal", - "Description": "Do you spend too much time manually testing your user interfaces? Automation is the answer. Python and Selenium offer a simple but powerful framework to script any testing. In this talk, I will show you how to use the combination of Selenium WebDriver and Python code to automate web UI tests. Follow along and learn how to locate elements, navigate pages, test user interactions with forms and drag-and-drop elements, and use waits to control test timing and execution. The lessons are practical and can be immediately applied to your development workflow. \nTopics include: What is automated testing? Python-Selenium bindings Parsing the DOM structure Locating elements in the DOM Navigating and interacting with pages Explicit and implicit waits", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Python basics HTML basics", - "Section": "Developer tools and Automation", - "Speaker Info": "Bhoomika Agarwal is a developer associate at SAP Labs India. She works in the field of cloud development, machine learning and open source technologies at SAP Labs. Prior to this, she has worked in Sprinklr and completed her graduation in Computer Science from PES Institute of Technology, Bangalore. She has done research in Big Data, Quantum Computing, Linear Algebra and Brain Computer Interface. She has published research papers and given presentations at numerous conferences about these topics. She has published tutorial courses online on Unacamedy and Lynda to disseminate the knowledge she has acquired over the years with experience", - "Speaker Links": "https://www.lynda.com/Python-tutorials/Python-Automation-Testing/651196-2.html https://unacademy.com/user/bhoomika1", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "bhoom10", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/web-ui-automation-using-selenium~ern4e/", - "title": "Web UI automation using Selenium" - }, - { - "Content URLs": "https://github.com/Blaze404/Digit_Recognitio", - "Description": "As neural networks, or in general, machine learning, form the crux of almost all the new technologies , its good to know the internal machinery of these algorithms. We will, in this workshop, train a neural network and study its ins and outs, and finally classify hand written digits with any image of choice . First we will get our hands onto numpy and using that matrix calculus . Next will be learning about gradient descent with multiple multidimensional visualizations using matplotlib( not necessary to be acquainted with). Here we will understand why it is best way to find a needle in a very very big haystack, by performing live comparisons with other methods. And that will be all you'll need to kill in this session. The Neural Net : This will start with structure of neural networks and why it is that way . Then forward propagation , and getting our heads over what is multiplied/dotted with with what. \nThen we'll study about different activation functions and cost functions , and where to use which. And finally, back-propagation , conquering the last enemy and minimizing the cost function for Keanu Reeves like precision. In addition to it, we'll differentiate between stochastic, batch and mini-batch gradient descent , and compare their results. At the end of session, we'll test our neural network on digit images of our choice , and further train the network if necessary", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Introductory knowledge of python Basic calculus Basic Matrix operation", - "Section": "Data science", - "Speaker Info": "I'm Mustafa Qazi, a third year Engineering student in Computer Science, from Govt. College of engineering, Aurangabad. I have four to five months of experience in Python and two months now in machine learning. I have a few projects in machine learning and this being one of them. I know somewhat about big-data jargons like map-reduce, Pig and Spark .Ya, I'm not an Ian Goodfellow in machine learning, but I'll be happy share what I have learned uptill now, and learn further with what experience I'll get from this", - "Speaker Links": "Github LinkedI", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Mustafa Qazi (~mustafa65)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/training-and-optimizing-an-artificial-neural-network-for-classification-from-scratch-with-just-numpy~avr0a/", - "title": "Training and optimizing an Artificial Neural Network for classification from scratch with just numpy." - }, - { - "Content URLs": "Presentatio", - "Description": "Today DASH streams are being used industry wide in Live media (Twitch, Facebook Live, Youtube Live) and would be soon incorporated in static media delivery. We would try to go through most of the use cases we as a consumer or developer would need to utilize these or serve our very own livestream. MPEG DASH (Dynamic Adaptive Streaming over HTTP) is an ISO standard employing adaptive bitrate streaming technique which works by breaking the content into a sequence of small HTTP-based file segments. Each segment contains a short interval of playback time of content, served in several bitrates/codecs, where all of this information is enclosed in a XML media presentation description (MPD). Unlike conventional streaming protocols, this works with standard HTTP servers over TCP, and can fully utilize the benefits of HTTP/2 if both client and server supports it. Naturally, most CDN's and servers can serve the dynamic stream as segmented static media files, with one dynamic entry point which delivers the MPD serving the current time. Due to lack of open libraries handling DASH media, we would be building a DASH utility toolkit. It would be carrying out activities of segmenting (generation), re-merging (consumption), and clipping out a specific period of clip, where the on-media tasks are carried out by ffmpeg. Special care will be taken for \"dynamic\" streams which are live streams. We will go through some production code behind https://esl.atx.sx which is specialized facebook streamer, and some challenges that came up serving its 1 million users", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Conventional streaming media basics asyncio Media descriptors - codecs, timestamps", - "Section": "Networking and Security", - "Speaker Info": "Arnav is currently working as a Developer at hedgehog lab , Hyderabad. He has presented technical talks at previous PyCons. He maintains several pet projects, his most recent https://esl.atx.sx serving the esports community. Having spent a decade behind the computer screen, he often gives valuable insight into Web Architecture, Network Infrastructure & Security and Hardware. When he is unable to find the most elegant and practical way to approach a solution, he is often found reading and outputting chunks of python code. He also takes out time and enjoys mentoring peers on good coding practices. Rest of the time he is deeply devoted leading his DotA team", - "Speaker Links": "arnav.at PyCon India 2017 Talk linkedin.com/in/arnav", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "_arnAV", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/handling-dash-streams-generation-consumption-clipping~dwv1b/", - "title": "Handling DASH streams - Generation, Consumption & Clipping" - }, - { - "Content URLs": "https://towardsdatascience.com/python-basics-for-data-science-6a6c987f2755 https://towardsdatascience.com/customizing-plots-with-python-matplotlib-bcf02691931f https://towardsdatascience.com/5-quick-and-easy-data-visualizations-in-python-with-code-a2284bae952", - "Description": "Data is a commodity, but without ways to process it, its value is questionable. Data science is a multidisciplinary field whose goal is to extract value from data in all its forms. Machine Learning is a field which is raised out of Artificial Intelligence(AI). It is about extracting knowledge from data and is an integral part of many commercial applications and research projects today, in areas ranging from medical diagnosis and treatment to finding your friends on social networks. My talk will show what data visualisation is, and how it is an essential component for data science. Data visualisation is the key to actionable insights, It allows us to take our complex findings and present them in a way that is informative and engaging to all stakeholders. Also, data visualisation helps us make sense of large amounts of data in quick, easy way in a universal manner. In the end, the consumer of the product of all artificial intelligence or machine learning endeavors will be people. We should ensure results are delivered as actionable, impactful insights to act upon in business and in life. By the time the conference is over, you will have a brief overview of data visualisation and started thinking of how to use data visualisation for your organisation or projects", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic knowledge of python. Knowledge of basic graphical representations like bar graphs, scatter plots etc.", - "Section": "Data science", - "Speaker Info": "Myself Saurabh Sunil Deshmukh, currently pursuing my B.E. (Computer Science and Engineering ) from Government college of Engineering Aurangabad, Maharashtra. I started with python three months before considering its scope and popularity in data science and machine learning. I have also studied Big Data analytics using Apache Spark and Apache Hadoop. I would love to share my (just started) journey into data science also eager to hear from everyone else", - "Speaker Links": "https://github.com/Saurabh2798/Python https://github.com/Saurabh2798/introduction_to_ml_with_pytho", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Saurabh Deshmukh (~saurabh15)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/introduction-to-machine-learning-and-importance-of-data-visualisation~egN3d/", - "title": "Introduction to machine learning and importance of data visualisation" - }, - { - "Description": "The Tor network is a group of volunteer-operated servers that allows people to improve their privacy and security on the Internet. Tor's users employ this network by connecting through a series of virtual tunnels rather than making a direct connection, thus allowing both organizations and individuals to share information over public networks without compromising their privacy. Along the same line, Tor is an effective censorship circumvention tool, allowing its users to reach otherwise blocked destinations or content. Tor can also be used as a building block for software developers to create new communication tools with built-in privacy features. It has become even more important as we kept hearing all the different stories about government surveillance and how the big companies are tracking everyone on Internet. In this talk, I will showcase a few ways any Python developer\ncan make use of the Tor Project inside of their code or infrastructure and provide solutions which thinks about the users' privacy from the beginning. Talk outline Introduction to the Tor Project Simple Python example to do HTTP calls using Tor network Using Stem to control the Tor process for your project Deploying any Python (or any otherone) web application and creating Onion service for the same Points to remember Nyx to monitor More upsteam usecases (onionshare, ooni). The audience will get a chance to learn about the various ways they can connect and use the Tor network using Python", - "Last Updated": "10 Jul, 2018", - "Section": "Networking and Security", - "Speaker Info": "Kushal Das is privacy advocate who is also part of the Tor community team and a CPython Core developer. He is working as SecureDrop developer in the Freedom of the Press Foundation ", - "Speaker Links": " https://kushaldas.in Tor community team", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Kushal Das (~kushal)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-tor-network-for-python-developers~ejNle/", - "title": "THe Tor Network for Python developers" - }, - { - "Description": "In this era of automation, AI and machine learning have conquered the hearts of Techno enthusiasts.\nAs for this very purpose,\nI would like to focus on training Machine Learning model from scratch . Dividing the session as into 3 groups of which part 2 will be extensively loaded with information. 1: A BIT LOOK-OVER (very precise): Synopsis of Pandas ,numpy,matplotlib,scikit-learn. 2: UNDERSTANDING (crux and to depths) : Understanding Machine Learning ,concepts of training a model ,Theory along with Mathematics ,roles of the above libraries to reach our motive. 3: APPLICATION ( Attention in part 1 and 2 would be enough): Training a model using Linear Regression as well as a model with Logistic Regression", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic Python,basics of mathematics", - "Section": "Data science", - "Speaker Info": "I am Devyani Sudhir Kulkarni ,\nThird year student and \npursuing B.E. from Government College of Engineering Aurangabad ,Maharashtra.\nAs user of Python I am new to Python community and so acquainted to few features of it .\nData science and field of Analysis has always been of my interests, so I managed to gain bit knowledge learning hadoop ,hive ,spark ,pig and currently using python", - "Speaker Links": "https://www.linkedin.com/in/devyani-kulkarni-a63717135", - "Target Audience": "Beginner", - "Type": "Workshops", - "author": "Devyani_Kulkarni", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/training-machine-learning-model-using-regression~bkNEa/", - "title": "Training Machine Learning model using Regression." - }, - { - "Content URLs": "Note: This talk is inspired by Armin Ronachar's (creator of Flask & a key-note speaker at this PyCon) blog post and a talk by a fellow Mozilla Tech Speaker - Vigneshwer. Armin Ronacher: A Python and Rust love story Dan Callahan - My Python's a little Rust-y - PyCon 2015 Extending Python with Rust (Samuel Cormier-Iijima) All you need to know about FFI", - "Description": "Python is a great language, we all know that. Although, sometimes Python\ncan be a bit of a slowcoach when it comes to performing certain tasks. That's where developers have\nbeen using C/C++, building extensions and integrating them with Python to speed up processes. However, writing C/C++ extensions with strict deadlines and timelines is a bit difficult and also, these low level languages tend to introduce bugs with respect to memory management, lead to segmentation faults and data races. How often have we all faced the dangling pointer error in C/C++ just because we forgot the de-reference a pointer somewhere? Enter Rust , a modern systems programming language that's much better in terms of memory safety, libraries and owing to it's amazing ownership & borrowing principles - keeps the bugs few. documentation up to date and a whole lot more! Bonus - it's completely a open sourced programming language, supported by Mozilla, the non-profit behind the Firefox browser. Basic outline of the talk Python's performance story and the need for native extensions [ 4-5 minutes ] Problems with C/C++ [ 4-5 minutes ] Rust and its success stories [ 8-10 minutes ] Why is Rust so cool!? [ 10-12 minutes ] Ownership & Borrowing, Garbage Collection, FFI (Foreign Function Interface) - along with code snippets Get started with Rust! - links to community & reach-out [ 2 minutes ] Q/A - [ 2 minutes ] Who is this talk for? Python developers who deal with performance issues on a daily basis The curious folk who want to know what Rust is, and why it's growing steadily C/C++ developers who'd like to check out a new systems level programming language Key takeaways A fresh perspective to improve performance metrics in python projects Preview of Rust code and samples Sample of Rust's FFI to ensure python developers can easily call Rust code Note: This talk is inspired by Armin Ronachar's (creator of Flask & a key-note speaker at this PyCon) blog post and a talk by a fellow Mozilla Tech Speaker, Vigneshwer", - "Last Updated": "10 Jul, 2018", - "Prerequisites": " Basic scripting in Python Coding experience in C / C++", - "Section": "Others", - "Speaker Info": "Abhiram has been a part of the open source world in Bangalore for over 3 years now. As a student volunteer in Bangalore, he started contributing to Mozilla as well as FSMK (Free Software Movement Karnataka). After becoming a Mozilla Rep, he has presented over 40 sessions and workshops on python scripting, web dev, Rust and git version control at various venues all over India. Being an internet activist, he was an integral part of the #SaveTheInternet campaign in India during the fight against net neutrality violations. In 2016, he was invited to Mozilla\u2019s Leadership Summit in Singapore to present a talk on running a successful campus club for ~3 years. Currently, he is a Mozilla Tech Speaker well versed in topics like full stack web development, decentralization, scalable infrastructure set up, open source contribution practices and mentoring web enthusiasts . For the past 2 years, he is working at SAP Labs in Bangalore as a full stack web developer and continues to contribute to Mozilla India on a voluntary basis. Recently, he was invited to record a programming course on Rust by the educational website Lynda.com at Los Angeles, California. The course is titled First Look: Rust went live last week", - "Speaker Links": "Events and speaking engagements Mozillians profile - endorsements Mozilla Reps profile - activities and speaking engagements LinkedIn - professional career GitHub - code base & projects Slides.com Speakerdeck.com - presentations and decks Blogs and social media Personal blog Twitter - @abhi12ravi", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Abhiram Ravikumar (~abhiram89)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/speed-up-your-python-modules-using-rust~elNrb/", - "title": "Speed up your Python modules using Rust" - }, - { - "Content URLs": "Will update this repository in a few days to include sample notebooks : https://github.com/mohdkashif93/PyCon-Graph-Analysis In the meantime you can checkout these repositories for reference Networkx example notebooks Quickstart using graph-tools", - "Description": "In this short tutorial we will be exploring graph networks from the ones mentioned below and work on analysing it various properties and features which will help us to analyse the various patterns that may exist in a network. We will exploring : Community detection in a network Identifying nodes of influence Graph properties like betweeness, centrality, transitivity, clustering coefficients, etc. and what information do they provide about the graph Path finding in a network ( If time permits, we will try to take an image of a maze and find the shortest path out of the maze, by using CV and networkx) Graph Databases in Python Analyzing graphs based on the no. of cliques, k-cliuqes, etc. Visualizing graphs in 2D and 3D space using Python We will be covering the following libraries in this tutorial Networkx graph-tools Neo4J (Graph Database usingPython) Visualization examples using graph-tools, networkx and plot.ly We will be using the following graph data for our analysis: Game of thrones network Marvel Universe Social Graph StackOverflow tag Data Facebook Ego Networks Bonus : If time permits we will take up a random image of a maze and try finding the path out of it, something similar to this (we will be using scikit-image for skeletonizing and networkx for path finding)", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic knowledge for Python will suffic", - "Section": "Data science", - "Speaker Info": "Hi, I am a Python Developer at Qualcomm, who is super enthusiastic about comics and video games. Sometimes when I get bored I head over to Stackoverflow and solve other people's problems, which is my version of being the friendly neighbourhood spiderman (or Nagraj, since Python translates loosely to Naag or snake in Hindi, so you know... sorry that was a lame reference) :", - "Speaker Links": "Stackoverflow : https://stackoverflow.com/users/story/8160718 Github : https://github.com/mohdkashif93 LinkedIn : https://www.linkedin.com/in/mohdkashif93", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Mohammed Kashif (~mohdkashif93)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/network-analysis-using-python~bmgre/", - "title": "Network analysis using Python" - }, - { - "Content URLs": "Will Update Shortl", - "Description": "I swear by the Dutch, this is not an ML Workshop * If you are one of the Cool Kids doing Style Transfer , Visual Translation or lurking at arxiv-sanity for what is hot, but wondering how would you take the model beyond Jupyter notebooks? It is my impression that the world of deep learning research is starting to plateau.\nWhat's booming: deploying DL to real-world problems. Fran\u00e7ois Chollet I trod the same path when I started as a founding ML Engineer, over the past two years I have learned that solid engineering is essential for building ML Application at web scale. Productionizing ML model is the last mile journey, the most dreaded and less talked about topic, knowing the right toolchain to automate your build pipeline is essential for APIfiying your ML Models. Typical ML pipeline is accompanied by a big data infrastructure to de-normalize and preprocess the application data to prepare training data, then a microservice to expose the trained model artifact on a runtime component as a service. In this workshop, we will explore the DevOps toolchain to build, train, test, deploy and monitor an ML Model. The focus will be on the toolchain and how to automate the entire process from commit to deployment. To illustrate the whole process we would build a toy recommendation application for an on-demand streaming service provide Pyflix . Application Architecture: Here is the reference Application Architecture for our Pyflix Recommendation Engine. Tentative Agenda Introduction to DevOps Culture Quick Introduction to ML/Big Data tools used in the Application - PySpark, Scikit-Learn (if required) Introduction to Containers and Cloud Infrastructure (Docker and AWS) Introduction to Infrastructure as Code (Terraform and Ansible) Building CI/CD pipeline with Jenkins Building Data Pipeline with Airflow Building RESTful Service with Django Rest Framework Application Architecture Introduction - Pyflix Putting All Together to Build Recommendation Engine", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "The workshop will spin around DevOps tools to build ML Pipeline. We will implement a rudimentary recommendation engine so a basic understanding of ML is enough. We will start with an introduction to DevOps and tools used, however good understanding of DevOps culture will help participants get the most out of the workshop. The edx course on DevOps by Microsoft is a great resource, but not necessary for this workshop. The Demo could be set up either in local with Docker or in the cloud. Basic understanding of Containers Basic understanding of Cloud Infrastructure (AWS) Basic understanding of ML/BigData(PySpark) A little bit of googling on Jenkins and Airflow will help Required Tools For local demo A Linux PC with preferably 8GB Ram, Windows or Mac users needs to perform some additional steps to install Docker. Docker Docker Compose For AWS awscli with configured credentials Terraform", - "Section": "Developer tools and Automation", - "Speaker Info": "By profession, Prabakaran Kumaressha designs algorithms to score complex user interactions, classify use generated contents, derive insights and APIfying them to run at scale. He has been data wrangling for 5+ years, specialized in NLP, uses Jupyter to analyze data that fits his PC memory, PySpark for anything that doesn't, uses Django+DRF to create microservices embracing DevOps culture, mostly on AWS. Occasionally he gives talks at local meetups", - "Speaker Links": "@iPrabakaran Github LinkedI", - "Target Audience": "Intermediate", - "Type": "Workshops", - "author": "Prabakaran Kumaresshan (~prabakaran16)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/devops-for-machine-learning-deploying-ml-models-at-scale~enjEe/", - "title": "DevOps for Machine Learning: Deploying ML Models at Scale" - }, - { - "Content URLs": "http://slides.com/dascommunity/gnupg-for-developers#", - "Description": "\u201cArguing that you don't care about the right to privacy because you have nothing to hide is no different from saying you don't care about free speech because you have nothing to say.\" -Edward Snowden. One\u2019s data is the extension of the person, the digital self. It should be treated as the part of our body. In the present age of massive digital surveillance, it is very difficult to protect the right to privacy. While the developers code or communicate in the digital sphere, she needs to safeguard the privacy rights of the users and the person she is communicating with, respectively. Encryption makes our life easy by protecting the digital self, whereas it makes life difficult for different surveillance agencies. GnuPG is the most trusted tool on that front. GnuPG is the free software version of the OpenPGP cryptographic software suite. This command line application permits one to encrypt and put the signature on your data and communication. There are Python modules which allow easy access to GnuPG\u2019s key management, encryption and signature functionality from Python programs. In the talk, we will learn how to use the same in your Python application, which will in turn help to protect the privacy of the users for your application. Why does this talk matter in current times? Keeping the users safe, keeping their right to privacy protected is one of the major concern for the modern application developers. Using the GnuPG tool with Python binding makes it easier for the application developers to protect the information. This talk will help new Python programmers to use GnuPG to jumpstart using GnuPG in their application safeguarding the users. This talk will also throw some light on the general usage of the GnuPG for the community at large. \u201cPower of community, which is at the heart of the GPG encryption,\u201d says Thenmozhi Soundararajan the Executive Director of Equality Labs", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic Python knowledg", - "Section": "Networking and Security", - "Speaker Info": "Anwesha Das, an Advocate, a PyLady and a core believer of Free and Open Source Software ideology. She provides consultation regarding legal, policy-making and community-related issues in the Free Software and Open Source Software world. She is the Organiser of PyLadies Pune and also leads the PyLadies efforts in India. Privacy and Freedom in the software space are the two of her very close to heart topics. She maintains her personal blog at https://anweshadas.in/. She currently blogs for PSF", - "Speaker Links": "Blogs at https://anweshadas.in/ Previous talk experiences: Keynote at PyCon UK 2017, [Communities and education - exploring together ] (https://www.youtube.com/watch?v=89Kc9ap0h6o&t=8s) PyCon US 2017, [The trends in choosing licenses in Python ecosystem PyCon 2017] (https://www.youtube.com/watch?v=ikT2i4I2LYY) ", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anwesha Sarkar (~anwesha)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/gnupg-for-the-python-application-developers~eplNe/", - "title": "GNUPG for the Python Application Developers" - }, - { - "Content URLs": "Content url will be provided after the session in the form of github repo", - "Description": "The human visual system is one of the wonders of the world. The difficulty of visual pattern recognition becomes apparent if you attempt to write a computer program to recognize digits. Neural networks approach the problem in a different way. The idea is to take a large number of handwritten digits, known as training examples, and then develop a system which can learn from those training examples. In other words, the neural network uses the examples to automatically infer rules for recognizing handwritten digits. Furthermore, by increasing the number of training examples, the network can learn more about handwriting, and so improve its accuracy", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Basic python programming. Certain basic knowledge about neural networks. Curiosity and enthusiasm", - "Section": "Core python and Standard library", - "Speaker Info": "The speaker is Aditya Patil who is pursuing his carrier in Computer Science Engineering at Government Engineering College Aurangabad,Maharashtra.\nHe is a coding enthusiast familiar with python and java and has major interest in Data science especially Spark, also have background knowledge of hadoop ", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Aditya Patil (~aditya89)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/fun-with-visual-pattern-recognition~bqmGb/", - "title": "Fun with visual pattern recognition!" - }, - { - "Description": "tes", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "tes", - "Section": "Data science", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "bhanu546", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/attention-networks~ernKe/", - "title": "Attention networks." - }, - { - "Content URLs": "https://pypi.org/project/pbr", - "Description": "Python is a great language to get started quickly, it's very easy to learn and it has a huge number of libraries available. One of the biggest challenges I found was how do you package is your code for distribution. Building and packaging is kind of a black box for me when I started with it. How to package your code/library in python and publish to PyPI? What's the difference between wheels and eggs? Do I use setuptools or pbr? What is pbr? Why should I use twine? Should define dependencies in setup.py or requirements? How to push my package in PyPI? History of python packaging. Do I use setuptools or distutils? What is pbr and history or pbr? What is setup.py and what goes in it Features of pbr How to manage versions using pbr ? Demo.", - "Last Updated": "10 Jul, 2018", - "Section": "Developer tools and Automation", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "Vamsi (~code-R)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/building-and-shipping-python-packages-with-reasonableness~avrXa/", - "title": "Building and shipping python packages with Reasonableness" - }, - { - "Description": "At Genpact we built product recommendation category engine which helped our client to avoid practical challenges in current product recommendation algorithms as either consumers ignore their recommendations or the sales team sees no value due to familiarity with the customer\u2019s\nrequirements and preferences from past experience.Our system intelligently categorises the recommendation generated by existing recommendations into three types of opportunities, viz. \u2018Default\u2019, \u2018Linked\u2019, and \u2018Hidden\u2019.\u2018Default\u2019 opportunities are generic recommendations that are independent of customer\u2019s past purchases.\u2018Linked\u2019 opportunities are obvious recommendations that are easy to identify from past experience of the\ndomain. \u2018Hidden\u2019 opportunities go beyond the \u2018Default\u2019 and \u2018Linked\u2019 opportunities, which even the sales team may not be aware of", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Python,Recommendation Engine,Market Basket Analysis", - "Section": "Data science", - "Speaker Info": "Ladle Patel has 6+ years of experience with a focus in Machine learning, Big data and Deep Learning", - "Speaker Links": "https://www.linkedin.com/in/ladlepatel", - "Target Audience": "Advanced", - "Type": "Talks", - "author": "Ladle Patel (~ladle)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/intelligent-categorization-of-product-recommendations-for-enhanced-customer-experience~dwvMb/", - "title": "INTELLIGENT CATEGORIZATION OF PRODUCT RECOMMENDATIONS FOR ENHANCED CUSTOMER EXPERIENCE" - }, - { - "Description": "The rapid rise of Artificial Intelligence (AI) poses fundamental challenges for the creative industry. Although AI technologies are being adopted at an ever faster pace, Design as an academic discipline has so far failed to provide a convincing answer to the opportunities and challenges of AI. As the number of interfaces between humans and information multiplies, so do the amount of design frameworks that are required to support this technology. When it comes to the Internet of Things (IoT), it\u2019s easy to focus on technological aspects. You can talk about different platforms or discuss which IoT solution might be the best to solve a specific problem. Looking below this layer of technology, it quickly becomes apparent that there are many more aspects that determine the success of the IoT. Not the least of which is the matter of how today\u2019s connected products are designed. Artificial Intelligence (AI), which was designed initially to replace highly repetitive, manual work, has exceeded expectations to complete tasks involving emotional creativity. A limiting factor of IoT is it adds devices and buttons which makes your life more complicated. Now with AI, you\u2019re able to say things like \u2018turn on the lights\u2019 instead of pushing buttons, and it makes life simpler. It is the AI layer of natural language processing that helps IoT improve our lives. In tapping into technology\u2019s potential, it\u2019s important to remember the end user \u2014 us humans. But as more and more experiences are built with ML, it\u2019s clear that UXers still have a lot to learn about how to make users feel in control of the technology, and not the other way round. How do we create experiences that are user friendly and human-centric, while taking advantage of technology? This talk will discuss some of the guidelines focusing on human-centered approach and can be used as reference by any UX designer to help navigate the new terrain of designing ML-driven products. As ML starts to power more and more products and experiences, let\u2019s step up to our responsibility to stay human-centered, find the unique value for people, and make every experience great", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Non", - "Section": "Data science", - "Speaker Info": "I am currently working as an Ecosystem Engagement Manager at Beahead Private Limited. I am an Intel Software Innovator and Organizer for Google Cloud Developer Community, New Delhi. I have been involved in delivering trainings on topics like: Internet of Things, Artificial Intelligence, Machine Learning, Deep Learning, Scratch and App Inventor at various national as well as international platforms. I also execute Google Design Sprints \u2013 a Design Thinking and Agile Development Methodology focused workshop series to improve the UX of applications by focusing on Unified User Experience. In addition to my professional pursuits, I am a volunteer at Headstart Network Foundation, India's largest grass-roots level organization that supports entrepreneurship and start-ups where he helps support and mentor various early stage start-ups and aspiring entrepreneurs. I am also an Oracle Certified Java Professional, Google AdWords Certified Professional and recipient of Google India Challenge Scholarship 2018", - "Speaker Links": "LinkedIn : https://www.linkedin.com/in/sidagarwal04/ Article : https://software.intel.com/en-us/blogs/2018/06/03/bringing-artificial-intelligence-to-the-edge Github : https://github.com/sidagarwal04 Mentions : https://medium.com/@jap.jolly/international-womens-day-celebration-gdg-and-wtm-new-delhi-a2067ae44714, https://pydelhi.org/blog/pydelhi-meetup-31-march-2018.html, https://software.intel.com/en-us/blogs/2018/03/19/intel-black-belt-software-developers-intel-software-innovators-intel-studen", - "Target Audience": "Beginner", - "Type": "Talks", - "author": "sidaxy", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/the-design-of-things-designing-for-ai-iot-conversations-and-the-future~axxqa/", - "title": "The Design of Things: Designing for AI, IoT, Conversations, and The Future" - }, - { - "Content URLs": "TB", - "Description": "The Problem As technology becomes cheaper and more available, we start taking it for granted. Nowhere is this more true than in\nmachine learning. As machines become cheaper and data becomes more and more voluminous, our approach to specific\nmachine learning problems often, and understandably, becomes haphazard. Since GPUs are much cheaper and more widely\navailable than ever before, we implicitly believe that throwing enough artificial neurons at a problem will eventually\nsolve it. While this by itself may be true, it is not uncommon for ML practitioners to realize - unfortunately only in\nhindsight - that most of the iterations required to build a successful predictive model were unnecessary. Ironically,\nthese 'missteps' are often what lead us to the correct answer. Solving a machine learning problem is like traversing a\nminefield, where the safest path can only be determined by blowing up a significantly large number of mines. You can\nonly figure out the right approach after making a bunch of mistakes. Since there is no general rule for determining a\n'best model', most things in deep learning can only be solved with trial and error. To a large extent, this 'see what\nsticks' approach cannot be avoided. However it can be curbed significantly, with a structured approach to running\nmachine learning experiments. This structured approach is what this talk is about. The Solution The building blocks of neural networks and the science behind them, including that of their efficiency and\ntrainability, are already very well understood [1]. The heuristics required to ascertain reasonable convergence and\npredictive accuracy have also been studied in detail [2]. On a very high level, these best practices are simply a\nresult of studying and understanding the underlying mathematics of neural networks. However, the lack of a structured\napproach prevents us from fully utilizing these best practices. The ideal way of managing machine learning experiments is\nwith a lab journal. Each machine learning experiment can be reasonably characterized by a hypothesis, a procedure and\nfinally drawing inferences from it's results. A well kept journal would help practitioners from repeating mistakes,\nand narrowing down to the right approach. The Tools This talk will introduce a lab journal powered by Python, and optimized for deep learning experiments. It will allow\nusers to log experiments carried out on sklearn estimators and keras models. The journal also behaves like a\nhyperparameter grid manager, which also alerts the user if the user accidentally re-runs the same experiment on the\nsame data with the same parameters. It will have some meta-learning features which allow for an end-to-end approach to\nmachine learning experiments. [1]. Efficient BackProp [2]. Improving Deep Neural Network", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "An understanding of basic neural network optimization techniques", - "Section": "Data science", - "Speaker Info": "I'm a data scientist based in New Delhi, India. I build data-driven products and the tooling around them for a living. My research interests are in signal processing and computational harmonic analysis. I'm obsessed with applications of machine learning in personal productivity and recommendation systems. I blog about these here ", - "Speaker Links": "https://twitter.com/jaidevd https://github.com/jaidevd https://jaidevd.github.i", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Jaidev Deshpande (~jaidev)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/deep-learning-with-the-scientific-method~dyyPd/", - "title": "Deep Learning with the Scientific Method" - }, - { - "Description": "Data quality is a common concern. This talk is about common patterns of data quality errors, how these can be automatically detected in Python, and how they can be fixed (automatically where possible", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Prior experience in data sourcing and transformation, no matter how simpl", - "Section": "Data science", - "Speaker Info": "Anand is a co-founder of Gramener, a data science company, and an aspiring data storytelle", - "Speaker Links": "https://YouTube.com/sanand", - "Target Audience": "Intermediate", - "Type": "Talks", - "author": "Anand S (~anand40)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/cleaning-data-with-python~azzma/", - "title": "Cleaning data with Python" - }, - { - "Description": "Hands training for developers ,data scientists ,researchers in deep learning using TensorFlow and Keras. Approach: Instructor led hands-on bootcamp to implement deep learning based applications for Computer Vision and Natural language processing. Topics covered . 1.Deep learning concepts\n a)Neurons\n b)Neural newtork\n c)Activation functions\n d)Back propagation algorithm\n e)Stochastic gradient descent\n f)Adaptive learning\n g)Momentum\n2.Installation and setup of GPU server on aws/gcloud 3.Deep learning for computer vision\n a)Image classification\n b)Object detection\n c)Image segmentation\n4.Deep learning for Natural language processing\n a)Word Embedding\n b)LSTMs Packaging Deep Learning models\n6.Case Studies", - "Last Updated": "10 Jul, 2018", - "Prerequisites": "Python,Basics of linear algebra, Basics of calculu", - "Section": "Data science", - "Speaker Info": "Ladle Patel has 6+ years of experience in Machine learning, Big data and Deep Learning", - "Speaker Links": "https://www.linkedin.com/in/ladlepatel", - "Target Audience": "Advanced", - "Type": "Workshops", - "author": "Ladle Patel (~ladle)", - "created_on": "10 Jul, 2018", - "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/hands-on-deep-learning-using-tensorflow-and-keras~aAlPe/", - "title": "Hands on Deep learning using TensorFlow and Keras" - }, { "Description": "Vyper is a recently launched python based smart contract programming language. The talk will focus on the features and benefits of Vyper and compare it to Solidity which is similar to Javascript and will include brief demos comparing smart contract implementations.\nTopics to be covered: Features of Vyper and their comparisons to solidity Design pattern of smart contracts Creating smart contracts : demos in both languages", "Last Updated": "10 Jul, 2018", @@ -4907,4 +13,4 @@ "link_to_proposal": "https://in.pycon.org/cfp/2018/proposals/vyper-vs-solidity-smart-contracts-in-the-python-ecosystem~bok3b/", "title": "Vyper vs Solidity: Smart contracts in the Python ecosystem" } -] \ No newline at end of file +] From f2cf34267701ea684fe4878aaca5ba1c557a7561 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Sun, 22 Jul 2018 12:15:15 +0530 Subject: [PATCH 16/17] Create .gitignore --- cfp_crawler/.gitignore | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 cfp_crawler/.gitignore diff --git a/cfp_crawler/.gitignore b/cfp_crawler/.gitignore new file mode 100644 index 0000000..34ea61c --- /dev/null +++ b/cfp_crawler/.gitignore @@ -0,0 +1,5 @@ + +*.pyc +*.log + + From e4d2f60831c6e7b63e1cc3f1051e7b80df1c90b9 Mon Sep 17 00:00:00 2001 From: Nivesh Krishna Date: Sun, 22 Jul 2018 20:44:26 +0530 Subject: [PATCH 17/17] closed proposal.json file --- cfp_crawler/proposal/spiders/crawler.py | 1 + 1 file changed, 1 insertion(+) diff --git a/cfp_crawler/proposal/spiders/crawler.py b/cfp_crawler/proposal/spiders/crawler.py index fce8661..c4a2d89 100644 --- a/cfp_crawler/proposal/spiders/crawler.py +++ b/cfp_crawler/proposal/spiders/crawler.py @@ -59,6 +59,7 @@ def from_crawler(cls, crawler, *args, **kwargs): def spider_closed(self, spider): print("Closing spider") json.dump(self.proposals, self.file, indent = 2, sort_keys = True) + self.file.close()