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Bookwise, Yoshua Bengio, Aaron Courville, and Ian Goodfellow are nearly finished with their MIT Press book on deep learning: http://www.iro.umontreal.ca/~bengio
by kastnerkyle 12y ago
Bookwise, Yoshua Bengio, Aaron Courville, and Ian Goodfellow are nearly finished with their MIT Press book on deep learning: http://www.iro.umontreal.ca/~bengioy/dlbook/ http://www.iro.umontreal.ca/~bengioy/dlbook/ . It is pretty strong on the true theory of what is going on in deep networks, and has fairly good intuition for how and why things work. Paired with the deep learning tutorials http://www.deeplearning.net/tutorial/ http://www.deeplearning.net/tutorial/, as well as the content from UFLDL it is a pretty strong foundation for advanced study.
Michael's book seems to target a more introductory level - a beginner might be better off to start with that, follow with Andrew Ng's ML course, which has a section on neural nets including an assignment implementing backpropagation, then continue with the deep learning book and the {deep learning, UFLDL} tutorials. This should be solid enough to at least read most of the cutting edge work and papers, if that is the aim.
Hugo Larochelle's youtube course https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7Tqgh... and Hinton's coursera course https://www.coursera.org/course/neuralnets https://www.coursera.org/course/neuralnets are also great references.
- brandonb 12y agoDidn't realize Yoshua & co had a book coming! That would definitely be the one to read. BTW, for anybody who wants to learn machine learning in general, Kyle's blog also seems to be packed full of clear explanations with working demo code: http://kastnerkyle.github.io/ http://kastnerkyle.github.io/ Very nice!
- kastnerkyle 12y agoThanks for checking it out! I am planning to add a few deep learning related posts during the holidays. The recent results for NLP, captioning and speech using encoder/decoder models are just too cool not to demo.