You could read Gilbert Strang's Linear Algebra books, there are also video lectures available... Gelman's Bayesian Data Analysis is a good statistical intro wi

You could read Gilbert Strang's Linear Algebra books, there are also video lectures available... Gelman's Bayesian Data Analysis is a good statistical intro with a Bayesian bend, maybe Freedman's Statistical models, read some general machine learning intro book, such as Alpaydin or Bishop for a more probabilistic view. For NLP especially, you'll need some information theory. Maybe start with MacKay's Information Theory, Inference, etc. (it is freely available online), very entertaining and accessible book and you can follow the pointers there for more details. For general data mining and machine learning you need some basics of optimization, pick up any standard book on convex optimization to get an idea of the basic problems and methods. that's it at a first try :)