References
It'd be good but not mandatory if you're familiar with neural networks, particularly RNN variations. Here is some great material for neural networks:
- Free online book: Neural Networks and Deep Learning (http://neuralnetworksanddeeplearning.com/)
- Video tutorial at https://www.youtube.com/watch?v=ob1yS9g-Zcs
RNN variations, especially LSTMs, have great tutorials too:
- RNN tutorial on the WildML blog: http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/
- RNN tutorial by the University of Toronto: https://www.cs.toronto.edu/~tingwuwang/rnn_tutorial.pdf
- Colah's blog: https://colah.github.io/posts/2015-08-Understanding-LSTMs/
- Blog post by Michael Phi: https://towardsdatascience.com/illustrated-guide-to-lstms-and-gru-s-a-step-by-step-explanation-44e9eb85bf21
- Video tutorial at https://www.youtube.com/watch?v=lWkFhVq9-nc
Although we have introduced neural networks in...
