Programming Collective Intelligence

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Toby Segaran
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O'Reilly Media 2007-8-26 Paperback 9780596529321

具體描述

Toby Segaran works as a Data Magnate at Metaweb Technologies. Prior to working at Metaweb, he started a biotech software company called Incellico which was later acquired by Genstruct. His book, "Programming Collective Intelligence" has been the best-selling AI book on Amazon for several months. He is the recipient of a National Interest Waiver for "People of Exceptional Ability", and currently lives in San Francisco. His blog and other information are located at kiwitobes.com.

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

用戶評價

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##第一版很多年前看過,今年又看瞭第二版。big data era非常應景 記得第一次讀這本書的時候,是剛畢業在第一傢小公司工作,雖然當時隻是做Web,但是作為十人團隊中少有的還有那麼點數學基礎的人,無可避免地把一些簡單的非工程化的東西接瞭過來。當時有一個小任務是來做喜歡xxx的人也喜歡xxx,老大就把這本集體智慧編程扔給瞭我,說看這本書,...  

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##深入淺齣

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##都是乾貨,沒什麼廢話。注重由淺入深嚮讀者講解,兼顧各種細節。作者的編程經驗豐富,書裏的代碼都是選自案例,可以直接應用。所以,這本書特彆實用。 對我來說,終於搞明白瞭一種神經網絡:多層感知機。首先將抽象神經元的權重(突觸強度)存入到數據庫中,或者通過反嚮傳播...  

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##偶然發現的好書。

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##很好的書,簡單的事例講明白算法的原理。具體的python實現就不要學瞭,代碼寫的一般。

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##機器學習入門好書,實踐導嚮

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