What are some good books/papers for learning deep
Over the past ~10 months, I've gone from having no/very little knowledge of deep learning to working in a research group that primarily studies deep learning.
The two most useful resources for learning about the field were Ng's deep learning tutorial: UFLDL Tutorial - Ufldl and Hinton's "Neural Networks for Machine Learning" course on Coursera: https://class.coursera.org/neura... (which you can still watch the videos for).
Two other useful resources are the "Learning Deep Architectures for AI" and [1305.0445] Deep Learning of Representations: Looking Forward . These are both a bit more theoretical than Ng's wiki or Hinton's course, but they provide a great overview of the reasoning behind the field as well as open challenges. "Learning Deep Architectures for AI" is from 2009 while the other survey is very recent, so it is also interesting to notice the differences between these two papers.
Of course, besides these resources, you'll want to read papers. After going through these resources, you shouldn't have much trouble reading through deep learning papers. Personally, I occasionally just check arxiv to see if any papers have interesting titles.
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