Automated Intent classification using Deep Learning

[RohitRathore1]

Here is our plan of action:

• We will classify text using Deep Learning
• We will practice by building a classification model trained in news articles from the BBC.
• We will test the model on news headlines we will scrape from Google Trends.
• We will build a similar model but we will train it on a different dataset with questions grouped by their intention.
• We will use Google Data Studio to pull potential questions from Google Search Console.
• We will use the model to classify the questions we export from Data Studio.
• We will group the questions by their intention and extract actionable insights we can use to prioritize content development efforts.
• We will go over the underlying concepts that make this possible: word vectors, embeddings, and encoders/decoders.
• We will build a sophisticated model that can parse not just intent but also specific actions like the ones we give to Siri and Alexa.

[SubhradeepSS]

@TeAmP0is0N sorry for the late reply.Was occupied a bit with something.
Can we proceed now?
I read the above points and wanted to ask you whether you have already any model built or do we have to build now right from the scratch?

[RohitRathore1]

@SubhradeepSS I have already provided you details in the issue #58 . And I have mentioned there about dataset. First, we will work on BBC dataset. So use that dataset. Further conversation we will have in this thread:
https://gssoc20.slack.com/archives/CUEGD0D8X/p1585462629005400