| - AIMA by Russel and Norvig is a classic but I would say is more of overview of the field and for most topic areas isn't quite deep enough imo. - For deep learning specifically, a more applied text that is beautifully written and chock full of examples is Francois Chollet's Deep Learning with Python (there a new second edition out with up to date examples using modern versions of Tensorflow). The first 3 chapters I would give as required reading for anyone interested in understanding some deep learning fundamentals. - Deep Learning - goodfellow and bengio - seems like it would be hard to get through without a reading group not exactly a APUE or K&R type reading experience but I haven't spent enough time with it. If you haven't taken a Linear Algebra or Differential Equations class its useful stuff to know for ML/DL theory but not fully necessary to do applied work with modern high level libraries, but definitely having a strong understanding of basic matrix math is useful. If you have interests in natural language processing theres a couple good books: - Natural Language Processing with Python - Bird Klein, Loper, is a great intro to NLP concepts and working with NLTK which may be a bit dated to some but I would definitely recommend, and its online for free. Great examples.(https://www.nltk.org/book/) - Speech and Language Processing - Dan Jurafsky and James H. Martin - is good, though I have only spent much time with the pre-print And then theres a lot of papers that are good reads. Let me know if you have any questions or want a list of good papers. If you just want to get off the ground and start playing with stuff and building things I'd recommend fast.ai's free online course - its pretty high level and a lot is abstracted away but its a great start and can enable you to build lots of cool things pretty rapidly. Andrew Ng's online course also is quite requitable and will probably give you a bit more background and fundamentals. If I were to choose one book from the bunch it would be Chollet it gives you pretty much all the building blocks you need to be able to read some papers and try to implement things yourself and I find building things a much more satisfying way to learn than sitting down and writing proofs or just taking notes but thats just my preference. |
And the new things he cover are covered in a better manner and better depth in other sources.
I read this book like a novel. Good for a basic overview, but the RoI is very low.