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Programming Collective Intelligence: Building Smart Web 2.0 Applications :: 0596529325
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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 IntellectEditorial Descriptions are usually submitted by the manufacturers, publishers and authors. Contact us if you are one of them, and wish to change the above description. |
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Author: Guest
Segaran has done an excellent job of explaining complex algorithms and mathematical concepts with clear examples and code that is both easy to read and useful. His coding style in Python often reads as clearly as pseudo-code in algorithm books. The examples give real-world grounding to abstract concepts like collaborative filtering and bayesian classification.
My favorite part is how he shows us code (gives it to us!) that goes out into the world, grabs masses of data and does interesting things with it. The use of a hierarchical clustering algorithm to dig into people's intrinsic desires in life as expressed in zebo is worth the price of the book alone. The graph that shows a strong connection between "wife", "kids", and "home" but a different connection between "husband", "children", and "job" is IMHO just fascinating.
Gems like that make this book worth reading cover to cover. After that it can happily hang out on your shelf as a reference anytime you need to build something to mine user data and extract the wisdom of crowds.
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Author: Guest
"Programming Collective Intelligence" is a great book. I took a college course on data mining and this book really would have come in handy.
From a "hands-on" programming perspective, the information on the useful libraries in python for crawling, parsing RSS feeds, python drawing, and accessing popular RESTful APIs are really valuable. The code samples are well documented and rather timely. I think Toby has done an amazingly cogent job of demonstrating the nuts and bolts of implementing the plethora of data mining and AI-related concepts pertinent to the field of Collective Intelligence. Additionally, I was new to Python and this book was a real eye opener.
In fact, more than just a book on Collective Intelligence, this is a really useful Python book. I learned a lot about Python reading through the examples and trying to get them to work on my laptop. (I was new to Python before this book, but have since started using Python at my work).
The author has demystified the abstract idea of Collective Intelligence and presented the concepts in an excellent programming language choice in Python. Most of the topics covered are things most developers just hear about. Taking a college course on Data Mining or Artificial Intelligence may expose one to the ideas, but I have never encountered a book that introduced the topics covered in "Programming Collective Intelligence" in a way so intuitive and familiar to the programmer. Distilling all of the topics into a set of very useful Python script really illustrated how practical and available these concepts really are in ones daily work. I will definitely make use of Toby's book.
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