Cyclic neural network theory to Practice (1)

1. Reading

The

Recurrent neural Network (NN) is the most commonly used neural network structure in NLP (Natural language Processing), and the convolution neural network is similar in the field of image recognition. Before we introduced CNN in detail in 4 blog posts, it is now necessary to introduce RNN before using CNN for a variety of purposes. Then it will be better to integrate practice.
Some valuable links:
http://www.cnblogs.com/neopenx/p/4623328.html
https://yjango.gitbooks.io/superorganism/ content/%e9%80%92%e5%bd%92%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c.html
https://wugh.github.io/posts/2016/03/ Cs224d-notes4-recurrent-neural-networks/?utm_source=tuicool&utm_medium=referral
https://wugh.github.io/ posts/2016/05/cs224d-notes5-recusive-neural-networks/
https://www.zhihu.com/question/36824148
https:// zhuanlan.zhihu.com/p/22266022
http://www.wildml.com/2015/09/ recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/
https://www.tensorflow.org/tutorials/ Recurrent
http://blog.csdn.net/heyongluoyao8/article/details/48636251
https://clyyuanzi.gitbooks.io/ julymlnotes/content/dl_rnn.html
https://zybuluo.com/hanbingtao/note/541458
http://www.cnblogs.com/ neopenx/p/4623328.html