遞歸神經網路（RNN）和長短期記憶模型（LSTM）的運作原理

這個網誌中的熱門文章

GAN 入門筆記

教電腦畫畫：初心者的生成式對抗網路(GAN)入門筆記（TensorFlow + Python3） https://medium.com/@gau820827/%E6%95%99%E9%9B%BB%E8%85%A6%E7%95%AB%E7%95%AB-%E5%88%9D%E5%BF%83%E8%80%85%E7%9A%84%E7%94%9F%E6%88%90%E5%BC%8F%E5%B0%8D%E6%8A%97%E7%B6%B2%E8%B7%AF-gan-%E5%85%A5%E9%96%80%E7%AD%86%E8%A8%98-tensorflow-python3-dfad71662952 這樣的解說還蠻有趣的
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ML Visualization (Grad-CAM)

Deep Visualization:可视化并理解CNN https://zhuanlan.zhihu.com/p/24833574 Github: keras-grad-cam https://github.com/jacobgil/keras-grad-cam 凭什么相信你，我的CNN模型？（篇一：CAM和Grad-CAM) http://bindog.github.io/blog/2018/02/10/model-explanation/ 凭什么相信你，我的CNN模型？（篇二：万金油LIME) http://bindog.github.io/blog/2018/02/11/model-explanation-2/ Grad-CAM 介紹 — Grad-CAM:Visual Explanations from Deep Networks via Gradient-based Localization https://medium.com/@xiaosean5408/grad-cam-%E4%BB%8B%E7%B4%B9-grad-cam-visual-explanations-from-deep-networks-via-gradient-based-localization-5a91dc6003b8 Visualizing Outputs of each layer of a CNN Model during Training Phase https://www.ir.com/blog/visualizing-outputs-cnn-model-training-phase
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