If you have already brushed up on linear algebra and calculus (which you're gonna need if you want to do any serious ML) take a look at Hastie et al's Elements of Statistical Learning.
The PDF is free, and the book is both extremely well written and super comprehensive.
http://www-stat.stanford.edu/~tibs/ElemStatLearn/
You might also want to check out R, as its an amazing statistics language which has hundreds of packages available for ML. There's a large user community, and the really obscure error messages you get will teach you a lot about statistics. http://cran.r-project.org/
Also, a lot of machine learning is getting the data into a usable form, so learn how to use Unix command line tools such as sed, awk, grep et al. They are absolute lifesavers.
You might also want to check out R, as its an amazing statistics language which has hundreds of packages available for ML. There's a large user community, and the really obscure error messages you get will teach you a lot about statistics. http://cran.r-project.org/
Also, a lot of machine learning is getting the data into a usable form, so learn how to use Unix command line tools such as sed, awk, grep et al. They are absolute lifesavers.