Ernest Chan has written a straightforward introduction to quantitative trading for the home trader; while this book is a great blueprint for someone who has never traded and is thinking about to doing his own trading, it’s too shallow for anyone who has been exposed to any sort of trading.

He does a good job of covering the most common trading pitfalls and he does an adequate job of discussing data gathering and backdating, nevertheless, he spends four chapters covering common sense concepts and techniques. I found his Matlab and Excel code to be of little use and I wish he used an open source package such as R instead of Matlab, in-fact, I wish he had devoted a chapter to the use of open source software packages in trading.

I only recommend this book for people who have never traded, if you have some experience in trading then skip the book and follow his blog instead.

I’ve only read 6 chapters of Programming Collective Intelligence and I’ve learned more from it than two AI courses at the University of Houston.  The way the subject matter is presented in university courses is dreadful and obfuscated, filled with mathematical theory without any practical examples to make understanding AI more tractable.

This book covers a broad range of topics: optimization, searching, classification and decision trees, all which the author, Toby Segaran, explains in plain English, with very readable code examples that illustrate the application of these concepts to real world problems. 

Toby has done a great job explaining the source code included in this book, they’re very easy to understand.  I’ve never programmed in Python before, but I find myself learning Python using his examples.

In all, I highly recommend this book to all developers interested in machine learning or data mining.

My copy of Patterns of Enterprise Application Architecture came in today– I’m reading it at 4:30 in the morning thinking, "see! I’m not crazy!"