图书标签: 数据挖掘 python programming 机器学习 算法 intelligence Web2.0 datamining
发表于2025-01-22
Programming Collective Intelligence pdf epub mobi txt 电子书 下载 2025
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
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.
可惜很多人一辈子都用不上里面的算法,悲哀啊
评分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。。
评分just open your eyes in this area, not the best solutions from trench.
评分很好的书,简单的事例讲明白算法的原理。具体的python实现就不要学了,代码写的一般。
评分just open your eyes in this area, not the best solutions from trench.
来自guwendong的书评,贴上来供大家参考。 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。 ...
评分记得第一次读这本书的时候,是刚毕业在第一家小公司工作,虽然当时只是做Web,但是作为十人团队中少有的还有那么点数学基础的人,无可避免地把一些简单的非工程化的东西接了过来。当时有一个小任务是来做喜欢xxx的人也喜欢xxx,老大就把这本集体智慧编程扔给了我,说看这本书,...
评分这本书还不错的,很适合数学基础不算太好(当然也还是要一定的数学基础),又想了解数据挖掘这个领域的读者。或者有实际的项目需求,但又没有足够的时间去深入了解这个领域的实践者。 不过我每次看到有人说它把艰涩的数学讲的很通俗、进而认为那些写满数学公式的书是故弄玄虚...
评分 评分看了没几页,就有醍醐灌顶的感觉,一起很多迷茫的问题都清晰了不少。相信看完并理解好了之后一定会功力大增
Programming Collective Intelligence pdf epub mobi txt 电子书 下载 2025