Programming Collective Intelligence

Anathem, by Neal Stephenson Consider Phlebas, by Iain M. Banks Selfish Gene, by Richard Dawkins Business Stripped Bare, by Richard Branson Programming Collective Intelligence, by Toby Segaran Zen and Art of Motorcycle Maintenance, by Robert Pirsig

Since it's a vacation, here's a novel with lots of interesting ideas about ubiquitous computing, augmented reality, etc.: http://en.wikipedia.org/wiki/Rainbows_End Fun with Python: http://www.amazon.com/Programming-Collective-Intelligence-Bu... (http://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325)

Huh! Currently I have Programming Collective Intelligence and Art of the start on mine. Just started reading Prog Coll Intell. So far, I am impressed.

Programming Collective Intelligence - O'Reilly Media Toby Segaran Art of the start - Guy Kawasaki The art of war - Sun Tzu

This is a great book, but it's definitely not introductory. I think Segaran's "Programming Collective Intelligence", mentioned above, is the best first bet, primarily because it's fun. And the code is good.

I've seen the Norvig book recommended by others on this site for ML, but I don't understand why: the Norvig book is an AI book, not an ML book. It only has a few chapters on learning, and IIRC much of that is on reinforcement learning. Obviously the Norvig book is very well-written and is good background for learning about ML, but I don't think it is a sufficient ML book as such. As far as ML goes, I found the "Programming Collective Intelligence" book to very readable and practical, but very light on the theoretical foundations (which is intentional, of course). I've got a copy of the Witten ML book ("Data Mining: Practical Machine Learning Tools and Techniques"), but to be honest I haven't gotten much from it yet, either: it doesn't seem to discuss SVMs in any detail, nor random forests or neural networks. But I haven't really dug into it yet.

The "Programming Collective Intelligence" book is pretty good in terms of a practical introduction to a variety of techniques.

books about machine learning applications/tools: - "Programming Collective Intelligence" - http://www.oreilly.com/catalog/9780596529321/ - "Data Mining: Practical Machine Learning Tools and Technique" - http://www.cs.waikato.ac.nz/~ml/weka/book.html books about machine learning background/theory: - "machine learning" - http://www.cs.cmu.edu/~tom/mlbook.html - "learning and soft computing" - http://cognet.mit.edu/library/books/view?isbn=0262112558 For a simple-to-use (Python-based) machine learning tool/API check out Orange: http://magix.fri.uni-lj.si/orange/

Machine Learning by Tom Mitchell for a serious academic book. Programming Collective Intelligence by Toby Segaran for a practical approach in Python.