I’ve been reading a fantastic book written by Toby Segaran called Programming Collective Intelligence: Building Smart Web 2.0 Applications. I’m about two thirds of the way through, but it’s so good that I’m not going to wait until I finish reading it before blogging it. Essentially, it’s a recipe book for machine learning algorithms that you’re likely to find under the hood of many successful modern web sites: clustering, support vector machines, decision trees, simulated annealing, Bayesian classification and so on. The AI course at uni was a bit light on in terms of statistical machine learning techniques, but this book makes up for it. All the code in the book is written in Python and can be downloaded from the author’s website. The algorithms in the book may prove to be highly useful for my work in ubiquitous computing, too.
Coincidentally, according to the most recent entry in his blog, Toby will be giving a talk on a topic sort of related to one I’ve been thinking about as a possible project at NICTA: Creating Semantic mashups: Bridging Web 2.0 and the Semantic Web.
It turns out that Toby is also a fan of GTD, and he’s written his own web based GTD tool. It doesn’t look much, but it’s gained some favourable reviews.
