Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. 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've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types 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 Non-negative matrix factorization to find the independent features in adataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I 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 matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect
Customer Reviews:
Avg. Customer Rating: 4.5 / 5.0
This was a great book!:
This was a great book! I highly recommend it! Have fun!
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Merry Christmas!!!
A visionary book that illuminates the Internet:
This is a visionary book because it predicts a lot of what will happen to the Internet soon. How do we process information in the Internet age? Instead of reading magazines and newspapers we use blogs as our source of news. This is because blogs offer much more customized news feed. In a typical newspaper, how much of its content is of interest to a reader? I guess half is a big value but typically it is less than that. I start my working day with consuming two sweet drinks. One drink is a cup of... more info
Not worth the money:
In short: this book isn't worth its price. The major part of the volume of the book is code and corresponding explanations. If the reader is a decent programmer, he can actually figure it all out by himself given algorithms. Otherwise it makes more sense to get a book on data structures, or Python, or general algorithm construction and learn the basics there. The algorithms/methods presented in this book are not really specific to "collaborative intelligence" (with a couple of exceptions). The... more info
An Eye Openning Inspiring Book:
I got more from this book than I have from any other book I read in the past couple of years!
It covers in a streamlined form a huge array of algorithms powering the contemporary web - from recomendation engines to a search engine that includes as one of its features the Google PageRank algorithm, to some quite recent AI innovations.
Just about the only area that was not covered was statistical machine translation. I wish he had done that, since that is my favourite subject.
It helps you... more info
