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<p>In Chapter 2, we introduce a linear binary classifier — Perceptron. It takes linearly separable samples as input and output +1/-1 to represent positive and negative. I’ll summarize Perceptron in the following ways.</p>
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<p>安利一篇发表在13年ICLR的经典著作——《Network in Network》，其中提到的几个经典结构被后来所广泛应用。<br><a href="https://arxiv.org/pdf/1312.4400.pdf" target="_blank" rel="noopener">https://arxiv.org/pdf/1312.4400.pdf</a></p>
<h4 id="Spotlight"><a href="#Spotlight" class="headerlink" title="Spotlight"></a>Spotlight</h4><ul>
<li>小网络嵌入大网络的思想</li>
<li>1 * 1 卷积</li>
<li>全局平均池化（Global Average Pooling）</li>
<li>在当时的Cifar-10,Cifar-100上取得了SOTA</li>
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<p>前段时间头条面试的时候被问了一个问题——如何高效的测定程序中每个模块的运行时间，并且不用对代码进行很多修改。没答出来…<br>答案是装饰器，装饰器decorator顾名思义就是在利用函数为对象的性质在函数外套一个函数外壳以实现一些基础操作，通过在被装饰函数上方添加@decorator_func_name实现，例如打印日志、测试运行时间等。</p>
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<p>感觉身边用torch的人还是很多的，趁机会蹭蹭热度~<br>以下是用torch实现线性回归的例子学习 y = k <em> x + b 中的 k 和 b<br>loss = (1/2) </em> sigma((y[i] - (k * x[i] + b)) ^ 2), 通过链式手动求梯度更新参数，更一般地利用autograd自动求导</p>
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<p>前两天去看了《阿飞正传》，作为一个不经常看电影，更不经常看王家卫导演的电影的我，纯粹是冲着张国荣的盛世美颜去的。影片讲述了张国荣扮演的阿飞在寻找亲生母亲的过程中和刘嘉玲、张曼玉以及养母之间发生的一系列故事。</p>
<p>平心而论，文艺片从故事情节几乎很难打动观众，这部片子亦是如此，但是依然能够从哥哥的身上读出不少的内容。哥哥身上的两条线一同发展————爱情与亲情。</p>
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<p>借着Github搭了个小的Blog, 其实也只是想找一个平台写写平时心里的想法。时间无言、如此这般，只希望未来的几年学习生活能对得起自己曾经许下的诺言吧。</p>
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