I have read with interest the Elements of Statistical Learning and Murphy's Machine Learning - a Probabilistic Perspective. The latter touches upon deep learning and deep / recurrent neural networks in the last chapter, but I was wondering if new books / sources have come out that go into more depth on these topics?
There's a work-in-progress book on Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville. It's not finished yet, but you can view the draft online, it has a chapter on recurrent networks.
There are more resources available. I have listed a few below (no affiliation with any of them).
For a collection of information on Recurrent Neural Networks look here.
For a collection of information on deep learning look here
Check the deep learning part of the website of H2O
I don't think there's any book better than http://neuralnetworksanddeeplearning.com/
I think the book is the best because:
- It's easy to read and not much mathematics
- There's a Github source code for the book
- The book talks about advanced concepts such as dropout and gradient vanishing
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