A Carnegie Mellon graduate course on statistical methods for natural language processing, covering the probabilistic and machine learning foundations needed to work with text. The commenter describes it as covering the prerequisite ML alongside text-focused material.

Commenters call it a great course for anyone who wants to work primarily with text, since it covers the prerequisite machine learning as well.

What commenters said (1)

1. Recommendskubrickslair2011in “Ask HN: How do I start with Machine Learning?”

   Yes, you are correct. Sorry for the confusion; I meant that courses like 10-702 should be the star course he should work at, to have some short at understanding and contributing to theory heavy side of ML.

   The first basic course for the latter approach can be 10-601, it's a machine learning course meant for senior undergrads. Look at schedule and assignments.

   http://www.cs.cmu.edu/~roni/10601-s10/

   Also since you have interest in text mining etc. and if you want to focus on that, you can skip a lot of courses, and go directly to language and statistics-1. It's a great course if you wish to work primarily with text, and it covers the prerequisite ML.

   http://www.cs.cmu.edu/~roni/11761/

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