So we have to face it, Machine Learning is the buzzword of the year (multiple years?).  But where does one start learning?  Well assuming you’ve taking some stats classes in the past and words like regression don’t scare you off, you may be able to jump right in to some of the applicable textbooks out there.  In fact several of the “go to” books in Machine Learning (also sometimes called Statistical Learning) are available free!  I would recommend you start with “An Introduction to Statistical Learning: With Applications in R” by James, Witten, Hastie, and Tibshirani.  Once you’ve gone through that book, an excellent followup (by the same authors) is available in “The Elements of Statistical Learning: Data Mining, Inference, and Prediction”.  Before you get upset, yes, the second book was published first.

Now if you’re thinking to yourself “reading takes a lot of time, where can I take a class to learn all of this?!”, then you’re also in luck.  There is an in-depth introduction with over 15 hours of videos available here, which follows the Intro book.  And since we live in the age where everyone wants to enroll in multiple courses simultaneously to get more perspectives, you can also see slides and videos for another course using this link.

Finally, if you’re hoping to get even more theoretical background (read: math), then I highly recommend the Andrew Ng course from Stanford as well, available free online both here and through iTunesU (among others).