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

posted @ 2017-04-01 10:02 一夜星辰 阅读(...) 评论(...) 编辑 收藏