Interesting links to Recurrent Neural Networks blog posts and papers:

Step-by-step explanation of LSTM networks

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

Blog post on applications of RNNs

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

Attention and other extensions of the basic RNN architecture

• http://distill.pub/2016/augmented-rnns/

Blog post on attention and memory in Deep Learning

• http://www.wildml.com/2016/01/attention-and-memory-in-deep-learning-and-nlp/

Implementation of RNN and LSTM in Python using Numpy and Theano Part 1 - 4

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

Presentation on Recurrent Neural Networks, the Vanishing Gradient Problem and LSTM/GRU

• https://www.nervanasys.com/recurrent-neural-networks/

Python implementation and tutorial on an RNN for sentiment analysis

• http://deeplearning.net/tutorial/lstm.html#lstm

Python character level language model with mxnet

• http://mxnet.io/tutorials/python/char_lstm.html

Generating text with an LSTM in R

• https://www.r-bloggers.com/new-chapters-for-50-shades-of-grey/

Googles Machine Translation using encoder-decoder deep LSTM networks

• https://arxiv.org/pdf/1611.04558v1.pdf
• https://arxiv.org/pdf/1609.08144v2.pdf

Effective Approaches to Attention-based Neural Machine Translation

• https://arxiv.org/pdf/1508.04025v5.pdf