Recurrent Neural Networks - EXPLAINED!
Channel: CodeEmporium
Date: 2018-11-24

Understand exactly how RNNs work on the inside and why they are so versatile (NLP applications, Time Series Analysis, etc). We are also going to construct a recurrent neural net from scratch using only numpy!

Follow me on M E D I U M: https://towardsdatascience.com/likelihood-probability-and-the-math-you-should-know-9bf66db5241b

Code: https://github.com/dennybritz/rnn-tutorial-rnnlm
(Give this dude a * for his hard work!)

Patreon: https://www.patreon.com/CodeEmporium
Quora: https://www.quora.com/profile/Ajay-Halthor

REFERENCES
[1] Slides from the Deep Learning book for RNNs: https://www.deeplearningbook.org/slides/10_rnn.pdf
[2] Andrej Karpathy’s Blog + Code (You can probably understand more from this now!): http://karpathy.github.io/2015/05/21/rnn-effectiveness/
[3] The Deep learning Book on Sequence Modeling: https://www.deeplearningbook.org/contents/rnn.html
[4] Colah’s blog on LSTMs: http://colah.github.io/posts/2015-08-Understanding-LSTMs/
[5] Wildml for Coding RNNs: http://www.wildml.com/2015/10/recurrent-neural-network-tutorial-part-4-implementing-a-grulstm-rnn-with-python-and-theano/