Programming Collective Intelligence - Toby Segaran

Programming Collective Intelligence

Toby Segaran

出版时间

2007-08-26

ISBN

9780596529321

评分

★★★★★
书籍介绍
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
用户评论
第一次看用代码表示数学公式的书,有一种码农造反的感觉。。
pdf, 读的不算太仔细. 不过入门应该没问题了.
机器学习入门好书,实践导向
觉得应该给三星半。结构内容是不错,只是API各种过期,例如geocoding的那个。书上代码有问题的地方也不少。
实例教程,可作工具书,经常查阅。在线阅读地址:http://www.docin.com/p-47422429.html
开拓视野
分析到位,内容有点旧。
涵盖了一些常见的数据挖掘算法,和内容对比书名似乎有点容易误导,除非说只要是数据集都算collective。各种算法蜻蜓点水,这次算是借本书为索引,再去搜索、巩固一些基本知识。一些应用试用场景及细节讲得不错,但是没有对应上专有术语也没有引用,导致入门者难以深入。代码和实验没怎么看得进去(genetic programming那章实现除外)。随机优化那一章收获蛮多的:cost function, representation of constrained problem, similar solutions yield similar results。
原理讲得非常清楚明白,但是书中很多例子和代码都已经过时了
这种蠢书评价这么高,看来真的是阿猫阿狗也说自己在搞机器学习
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