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Programming Collective Intelligence
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 a dataset
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
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