程序猿 tensorflow 入门开发及人工智能实战

1. tensorflow 中文文档：

   http://www.tensorfly.cn
   
   http://wiki.jikexueyuan.com/project/tensorflow-zh/

2. tensorflow 实用例子

   https://github.com/aymericdamien/TensorFlow-Examples

3. 神经网络及深度学习了解

   入门了解 http://neuralnetworksanddeeplearning.com
   
   BP推导 http://neuralnetworksanddeeplearning.com/chap2.html
   
   中文资料 http://wiki.jikexueyuan.com/project/neural-networks-and-deep-learning-zh-cn/
   
   https://www.gitbook.com/read/book/hit-scir/neural-networks-and-deep-learning-zh_cn

4. cnn 了解

   结构 https://www.zybuluo.com/hanxiaoyang/note/442868
   
   推导 https://grzegorzgwardys.wordpress.com/2016/04/22/8/
   
   实现 http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/
   
   例子 http://yerevann.github.io/2015/10/11/spoken-language-identification-with-deep-convolutional-networks/

5. rnn_lstm 了解

   结构及推导 http://r2rt.com/written-memories-understanding-deriving-and-extending-the-lstm.html
   
   rnn 推导 http://www.wildml.com/2015/10/recurrent-neural-networks-tutorial-part-3-backpropagation-through-time-and-vanishing-gradients/
   
   实现1 http://r2rt.com/recurrent-neural-networks-in-tensorflow-i.html
   
   实现2 http://r2rt.com/recurrent-neural-networks-in-tensorflow-ii.html
   
   lstm 推导 http://arunmallya.github.io/writeups/nn/lstm/index.html#/

6. 重要博客阅读推荐

   YerevaNN 系列： https://github.com/YerevaNN
   
   > http://yerevann.com/a-guide-to-deep-learning/
   
   > https://github.com/YerevaNN/Deep-Learning-Papers-Reading-Roadmap
   
   > https://github.com/YerevaNN/Spoken-language-identification
   
   > http://yerevann.github.io/2015/10/11/spoken-language-identification-with-deep-convolutional-networks/
   
   > http://yerevann.github.io/2016/06/26/combining-cnn-and-rnn-for-spoken-language-identification/
   
   寒小阳博客系列 http://blog.csdn.net/han_xiaoyang/article/details/50542880
   
   > 如何知道一份深度学习的工作 http://blog.csdn.net/han_xiaoyang/article/details/52777661