(Besides deciding whether to title the book AI, machine learning, data mining/science, applied/computational stats) There's a number of books that take the "sho

(Besides deciding whether to title the book AI, machine learning, data mining/science, applied/computational stats) There's a number of books that take the "short equation/inequality" only approach to presenting the author's subset of his/her appelation. Marsland's is pretty good. But I'm not sure they impart much intuition before you dive into the traditional texts (usually one chooses from the Big 6 of Murphy, Bishop, Barber, Mackay, Hastie/Tibshirani/ or Koller/Friedman). Note 3 of those have content freely available to read online, as well as free stats texts from otexts.com, UMass' Lavine and CMU's Shalizi and Kadane (2 separate books), and UCSD's Levy (specialized on stats for linguistics/CL). Note also the ESL guys (+ 1 additional author) have released Intro to Statistical Learning http://www.springer.com/statistics/statistical+theory+and+methods/book/978-1-4614-7137-0 http://www.springer.com/statistics/statistical+theory+and+me...