Python Machine Learning

+1 to Python Machine Learning, I feel like some of artificial intelligence is understanding a lot of finer (but critical) mathematical nuances, but some of it is just getting your hands dirty, and the second is definitely more accessible for somebody who is starting to learn.

Some on this thread have recommended Norvig's PAIP, but that's kind of an old school AI book in that it focuses on heuristic search and logic (implementing prolog in lisp at one point, very impressive stuff actually); but is lacking any coverage of statistical machine learning, which is the approach that underlies most of the cool stuff these days. It's still a great book, but I'd instead recommend a path that focuses on machine learning: - The Master Algorithm: made for a general audience, gives you a lay of the land - Python Machine Learning by Sebastian Raschka: gives you practical skills using python, scikit-learn, numpy, jupyter notebooks, pandas etc. From zero to kaggle in 4 chapters, goes deeper after that. Also goes into enough theory you aren't flying completely blind.…