This tutorial is excellent, and Richard Socher has been doing some really fascinating (though complicated) work with deep learning for NLP. I also have a few ot

This tutorial is excellent, and Richard Socher has been doing some really fascinating (though complicated) work with deep learning for NLP. I also have a few other good references for people who want to investigate this area. One of the most insightful comments I have seen about deep learning for NLP is a reddit r/machinelearning comment seen in this post [1]. As the poster in that thread mentioned, much of the theory about using neural networks for NLP tasks was laid out pretty clearly in a paper by Yoshua Bengio from 2003 [2]. At a high level, the basic learner is very similar to many of the other deep architectures for images and audio. There is also a pretty great blog post [3] by Radim Rehurek (author of gensim) about how he implemented word2vec (a "deep learning"-style model for text) in Python, while also getting a performance improvement over the C version! [1] http://www.reddit.com/r/MachineLearning/comments/2doi7e/what_should_i_know_before_taking_on_word2vec/ http://www.reddit.com/r/MachineLearning/comments/2doi7e/what... [2] http://jmlr.org/papers/v3/bengio03a.html http://jmlr.org/papers/v3/bengio03a.html [3] http://radimrehurek.com/2014/02/word2vec-tutorial/ http://radimrehurek.com/2014/02/word2vec-tutorial/