零.大神小结

知乎大神的小结（读完豁然开朗）

https://zhuanlan.zhihu.com/p/46816007

【深度学习之美28】LSTM该如何通俗理解？

https://zhuanlan.zhihu.com/p/49834993

Understanding LSTM Networks

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

神经网络资源

There are more resources for learning about neural networks that are more in depth and detailed. Here are some following resources:

The seminal paper describing back propagation is Efficient Back Prop by Yann LeCun et. al. The PDF is located here: http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf

CS231, Convolutional Neural Networks for Visual Recognition, by Stanford University, class resources available here: http://cs231n.stanford.edu/

CS224d, Deep Learning for Natural Language Processing, by Stanford University, class resources available here: http://cs224d.stanford.edu/

Deep Learning, a book by the MIT Press. Goodfellow, et. al. 2016. Located: http://www.deeplearningbook.org

There is an online book called Neural Networks and Deep Learning by Michael Nielsen, located here: http://neuralnetworksanddeeplearning.com/

For a more pragmatic approach and introduction to neural networks, Andrej Karpathy has written a great summary and JavaScript examples called A Hacker's Guide to Neural Networks. The write up is located here: http://karpathy.github.io/neuralnets/

Another site that summarizes some good notes on deep learning is called Deep Learning for Beginners by Ian Goodfellow, Yoshua Bengio, and Aaron Courville. This web page can be found here: http://randomekek.github.io/deep/deeplearning.html