Resource | Haobin Tan

Resource | Haobin Tanhttps://haobin-tan.netlify.app/tags/resource/ResourceHugo Blox Builder (https://hugoblox.com)en-usWed, 19 Aug 2020 00:00:00 +0000https://haobin-tan.netlify.app/media/icon_hu7d15bc7db65c8eaf7a4f66f5447d0b42_15095_512x512_fill_lanczos_center_3.pngResourcehttps://haobin-tan.netlify.app/tags/resource/CNN Resourceshttps://haobin-tan.netlify.app/docs/ai/deep-learning/cnn/cnn-resources/Wed, 19 Aug 2020 00:00:00 +0000https://haobin-tan.netlify.app/docs/ai/deep-learning/cnn/cnn-resources/<h2 id="tutorials">Tutorials</h2> <ul> <li><a href="https://e2eml.school/how_convolutional_neural_networks_work.html">How do Convolutional Neural Networks work?</a></li> <li><a href="https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/">An Intuitive Explanation of Convolutional Neural Networks</a></li> </ul> <h2 id="visualization">Visualization</h2> <ul> <li><a href="https://poloclub.github.io/cnn-explainer/#article-convolution">CNN Explainer</a></li> <li><a href="https://www.cs.ryerson.ca/~aharley/vis/conv/flat.html">MINST playground</a></li> </ul> <h2 id="plotting">Plotting</h2> <ul> <li><a href="http://alexlenail.me/NN-SVG/">NN-SVG</a></li> </ul> <h2 id="papers-overview">Papers Overview</h2> <ul> <li><a href="https://adeshpande3.github.io/The-9-Deep-Learning-Papers-You-Need-To-Know-About.html">The 9 Deep Learning Papers You Need To Know About (Understanding CNNs Part 3)</a></li> </ul>RNN Resourcehttps://haobin-tan.netlify.app/docs/ai/deep-learning/rnn/resource/Mon, 03 Aug 2020 00:00:00 +0000https://haobin-tan.netlify.app/docs/ai/deep-learning/rnn/resource/<h2 id="rnn">RNN</h2> <ul> <li>Tutorials <ul> <li><a href="https://towardsdatascience.com/illustrated-guide-to-recurrent-neural-networks-79e5eb8049c9">Illustrated Guide to Recurrent Neural Networks</a> 🔥👍 <ul> <li>Video Tutorial: <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="allowfullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube.com/embed/LHXXI4-IEns?autoplay=0&controls=1&end=0&loop=0&mute=0&start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video" ></iframe> </div> </li> </ul> </li> </ul> </li> </ul> </br> <ul> <li> <p>Implementation</p> <ul> <li><a href="https://gist.github.com/karpathy/d4dee566867f8291f086">min-char-rnn</a></li> </ul> </li> <li> <p>Application of RNN:</p> <ul> <li><a href="http://karpathy.github.io/2015/05/21/rnn-effectiveness/">The Unreasonable Effectiveness of Recurrent Neural Networks</a></li> </ul> </li> </ul> <h2 id="lstm">LSTM</h2> <ul> <li> <p>Tutorials</p> <ul> <li><a href="https://colah.github.io/posts/2015-08-Understanding-LSTMs/">Understanding LSTM Networks</a> 🔥👍</li> <li><a href="https://towardsdatascience.com/illustrated-guide-to-lstms-and-gru-s-a-step-by-step-explanation-44e9eb85bf21">Illustrated Guide to LSTM’s and GRU’s: A step by step explanation</a> 🔥👍 <ul> <li>Video Tutorial: <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="allowfullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube.com/embed/8HyCNIVRbSU?autoplay=0&controls=1&end=0&loop=0&mute=0&start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video" ></iframe> </div> </li> </ul> </li> </ul> </br> <ul> <li> <p><a href="https://blog.csdn.net/v_JULY_v/article/details/89894058">如何从RNN起步，一步一步通俗理解LSTM</a></p> </li> <li> <p><a href="https://www.zhihu.com/question/314002073/answer/613515841">通俗有趣地解释RNN和LSTM</a> 🔥👍</p> </li> </ul> </li> <li> <p>Implementation</p> <ul> <li><a href="https://wiseodd.github.io/techblog/2016/08/12/lstm-backprop/">Deriving LSTM Gradient for Backpropagation</a></li> </ul> </li> <li> <p>Deeper understanding</p> <ul> <li><a href="https://weberna.github.io/blog/2017/11/15/LSTM-Vanishing-Gradients.html">Why LSTMs Stop Your Gradients From Vanishing: A View from the Backwards Pass</a></li> </ul> </li> </ul>