Probabilistic Programming & Bayesian Methods for Hackers
For those who want a more solid take on machine learning, and who still remember their math and probability/statistics, (i.e. advanced undergrad or new grad student), the best texts seem to be:<p>The Elements of Statistical Learning by Hastie, Tibshirani and Friedman, available for free on line.<p>Pattern Recognition and Machine Learning by Chris Bishop.  Very Bayesian.<p>Machine Learning: A Probabilistic Perspective by Kevin Murphy.  Also Bayesian, although not as Bayesian as Bishop.  The most recent of the three, and therefore covers a few topics not covered elsewhere like deep learning and conditional random fields.  The first few printings are full of errors and confusing passages, should be better before too long.<p>Did I miss any?