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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?

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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.

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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

You can also look at the journal of machine learning research if there are any articles available. Or look at arXiv. Even SSRN has some articles about this.

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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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  • $\begingroup$ Thank you. Great book. Does it cover recurrent neural networks? $\endgroup$
    – caveman
    Apr 3, 2016 at 1:21

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