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Expand Up @@ -302,7 +302,7 @@ You may choose to either start from the basics of NLP and gradually move to deep

1. [Natural Language Processing](http://www.cs.jhu.edu/~jason/465/) by Jason Eisner, Johns Hopkins University. While video lectures aren't available for the course, you should definitely go solve all the assignments. They are very tough and will strengthen your NLP foundations. You can go through the suggested readings (on the course page) if you need help with homework. (Strongly recommended)
2. [Natural Language Processing](https://www.youtube.com/playlist?list=PLQiyVNMpDLKnZYBTUOlSI9mi9wAErFtFm) by Dan Jurafsky and Christopher Manning, Stanford University. Both the professors have written two separate text books on NLP. This was a coursera course but it is no longer offered. Sadly, there are no assignments available for the course. You could choose to watch these videos and solve the homework from the first course.
3. [Deep Learning for NLP](https://www.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6) by Richard Socher and Christopher Manning, Stanford University. It is a great deep learning course even if you aren't interested in NLP. The course provides an introduction to deep learning and how to apply it for text data. Make sure you do the [course assignments](http://web.stanford.edu/class/cs224n/assignments.html). Also as mentioned earlier, if you decide to start with the course and like NLP, you should most definitely do at least one of course 1 and 2.
3. [Deep Learning for NLP](https://www.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6) by Richard Socher and Christopher Manning, Stanford University. It is a great deep learning course even if you aren't interested in NLP. The course provides an introduction to deep learning and how to apply it for text data. Make sure you do the [course assignments](http://web.stanford.edu/class/cs224n/#coursework). Also as mentioned earlier, if you decide to start with the course and like NLP, you should most definitely do at least one of course 1 and 2.

#### Books

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