With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you find it. This book explains: collaborative filtering techniques that enable online retailers to recommend products or media Clustering method to detect groups of similar items in large datasets Features search engine - crawlers, indexers, query engines and PageRank algorithm Optimization algorithms that search millions of possible solutions to problems and choose the best Bayesian filtering, used in spam filters for classifying documents according to type words and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites of non-negative matrix factorization to find the independent features in adataset Developing intelligence for problem solving - how to develop computer skills by increasing own code increasingly play a game Each chapter includes exercises for extending the algorithm to make them more powerful. "Bravo I do not! Could think of a better way for the developer to first learn these algorithms and methods, I was not able to think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." - Dan Russell, Google "Toby's book does a great job of breaking down the complex subject of machine-learning algorithms into practical, easy to understand examples that can be directly applied to analysis of current social interaction across the Web.