Course Links

• Linear Algebra Review from Andrew Ng's Machine Learning course
• Probability Theory Review from Andrew Ng's Machine Learning course
• Lagrange Multipliers without Permanent Scarring by Dan Klein

There are a number of links to tutorials on various NLP and machine learning topics on the UTCL reading list wiki page.

Relevant talks

• Tom Mitchell: Semisupervised Learning over Text
• Michael Jordan: Applied Nonparametric Bayes and Statistical Machine Learning

Relevant online courses

• Andrew Ng: CS229: Machine Learning (Online Stanford course)
• Chris Manning: CS224N: Natural Language Processing (Stanford)

Collections with relevant talks

• Videos of Machine Learning lectures
• Machine Learning and Cognitive Science 2007
• NIPS 2007 tutorials
• Graduate Summer School: Probabilistic Models of Cognition: The Mathematics of Mind (July 9 - 26, 2007) – slides and webcast links of all the talks. A lot of good introductory stuffs on graphical models, Bayesian learning, etc.
• Microsoft Research – Videos on Researchchannel.

• Andrew Ng (Stanford): Machine Learning. Great lecture notes. You can also check out the online version of course, with video lectures

• David Blei: Bayesian Nonparametrics.

• Peter Orbanz: Foundations of Nonparametric Bayesian Methods

• UT Compling Lab Programming tips and tricks
• The R Project

• NAACL09 Workshop on Semisupervised Learning for NLP
• NAACL09 Workshop on Active Learning for NLP