作者: Toby Segaran
副标题: Building Smart Web 2.0 Applications
ISBN: 9780596529321
页数: 304
定价: USD 39.99
出版社: O'Reilly Media, Inc.
装帧: Paperback
出版年: 2007-08-16
ISBN: 9780596529321
页数: 304
定价: USD 39.99
出版社: O'Reilly Media, Inc.
装帧: Paperback
出版年: 2007-08-16
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简介 · · · · · ·
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 w... (展开全部)
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
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
作者简介 · · · · · ·
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.
豆瓣成员常用的标签(共107个) · · · · · ·
数据挖掘(104) programming(60) python(54) Web2.0(54) collective(40) intelligence(37) datamining(31) O'Reilly(28)
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| 我有电子书 | 来自kergee | 5 回应 | 2009-06-24 |
| 这里有下载地址 | 来自xyb | 12 回应 | 2009-04-10 |
| 不错的一本书 | 来自leo | 2008-10-26 | |
| 看着看着, 越来越有意思了~~~ | 来自Иıɔʞ | 2 回应 | 2008-10-21 |
| 怎么能买到这本书? | 来自Иıɔʞ | 3 回应 | 2008-10-20 |
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豆瓣成员最受欢迎的书评 (4条) · · · · · ·
实战性极强
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- clickstone(i'm back) 中国有句老话,叫做“知易行难”。 作算法的朋友应该更有体会,想把 paper 上的公式转变为可以运行的代码,这是件考验功力的事情。 Toby Segaran 写的这本《Programming Collective Intelligence》,是修炼此种功力的武林秘笈之一。 这本书最显著的特点是,实战性极强! ...... (5回应)
2008-08-25 9/10人推荐
感觉离实际应用还有点距离
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- j.L@enjoy Life(纪念512) 1个问题有N个方案,如果单靠某个方案去解决该问题,感觉有点不靠谱。 随便举个例子:书中的Filtering Spam,算法本身没什么问题,但是其有个前提,数据越多准确性越高,但是一般公司项目上的数据不会很多,于是准确性就会低了。 要保证准确性,就要上大量数据,可能1亿的数据只为保证100万的真实数据的准确性......
2008-11-17
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