Programming Collective Intelligence

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