Some good blogs about RNN-lstm

Understanding LSTM Networks
http://colah.github.io/posts/2015-08-Understanding-LSTMs/

 

An overview of gradient descent optimization algorithms
http://sebastianruder.com/optimizing-gradient-descent/

The Unreasonable Effectiveness of Recurrent Neural Networks
http://karpathy.github.io/2015/05/21/rnn-effectiveness/

Recurrent Neural Networks Tutorial
http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/
http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-2-implementing-a-language-model-rnn-with-python-numpy-and-theano/
http://www.wildml.com/2015/10/recurrent-neural-networks-tutorial-part-3-backpropagation-through-time-and-vanishing-gradients/
http://www.wildml.com/2015/10/recurrent-neural-network-tutorial-part-4-implementing-a-grulstm-rnn-with-python-and-theano/

Recurrent Neural Network (RNN)
https://theneuralperspective.com/2016/10/04/05-recurrent-neural-networks-rnn-part-1-basic-rnn-char-rnn/
https://theneuralperspective.com/2016/10/06/recurrent-neural-networks-rnn-part-2-text-classification/
https://theneuralperspective.com/2016/11/20/recurrent-neural-networks-rnn-part-3-encoder-decoder/
https://theneuralperspective.com/2016/11/20/recurrent-neural-network-rnn-part-4-attentional-interfaces/
https://theneuralperspective.com/2016/11/17/recurrent-neural-network-rnn-part-4-custom-cells/

http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/

http://iamtrask.github.io/2015/11/15/anyone-can-code-lstm/

http://karpathy.github.io/2015/05/21/rnn-effectiveness/

https://github.com/dmnelson/sentiment-analysis-imdb

https://github.com/asampat3090/sentiment-dl

https://github.com/wenjiesha/sentiment_lstm

http://blog.csdn.net/zouxy09/article/details/8775518/

http://ir.hit.edu.cn/~dytang/

https://apaszke.github.io/lstm-explained.html

https://github.com/cjhutto/vaderSentiment

http://www.nltk.org/book/

http://deeplearning.net/software/theano/install_windows.html

Introduction to TensorFlow (5) Multi-layer LSTM Easy-to-understand version

https://blog.csdn.net/Jerr__y/article/details/61195257