收藏
Programming Collective Intelligence - Toby Segaran

Programming Collective Intelligence

Toby Segaran

出版社

O'Reilly Media

出版时间

2007-08-26

ISBN

9780596529321

评分

★★★★★

标签

数据挖掘pythonprogramming机器学习

书籍介绍
这本书最难得之处，在于它把看似高深的机器学习与数据挖掘，拆解成读者亲手就能跑通的算法实例。它不堆砌理论，而是从推荐系统、协同过滤、聚类分析、神经网络到优化算法，每一步都给出可运行的代码与真实数据集——从评分数据到股票行情，从文章矩阵到网页抓取。正因如此，它成为众多读者眼中'想学却怕看不懂'时的救星。不过也有读者指出，内容偏浅、个别代码存在小错误，更适合当作入门与实践的桥梁，而非深入研究的权威。如果你希望理解推荐、搜索、评分背后的算法逻辑，并自己动手实现，这本书值得一试；若已具备基础，或许会觉得它只是搭了个框架。
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.
AI导读
核心看点
  • 以Python代码实战解析机器学习算法
  • 涵盖协同过滤、聚类、分类等核心技术
  • 结合Web 2.0场景挖掘用户行为数据
读者共识
  • 实例丰富直观，非常适合入门学习
  • 数学公式讲解通俗，降低理解门槛
  • 代码质量一般，重在理解算法思想
精彩摘录
  • "Next, get a list of random people to make up the dataset. Fortunately, Hot or Not provides an API call that returns a list of people with specified criteria. In this exam- ple, the only criteria will be that the people have “meet me” profiles, since only from these profiles can you get other informa"
  • "What Does This Have to Do with the Articles Matrix? So far, what you have is a matrix of articles with word counts. The goal is to factorize this matrix, which means finding two smaller matrices that can be multiplied together to reconstruct this one. The two smaller matrices are: The features matri"
  • "Another feature that applies more evenly to a couple of companies is this one: Feature 2 (46151801.813632453, 'GOOG') (24298994.720555616, 'YHOO') (10606419.91092159, 'PG') (7711296.6887903402, 'CVX') (4711899.0067871698, 'BIIB') (4423180.7694432881, 'XOM') (3430492.5096612777, 'DNA') (2882726.88776"
  • "Because new connections are only created when necessary, this method has to return a default value if there are no connections. For links from words to the hidden layer, the default value will be –0.2 so that, by default, extra words will have a slightly negative effect on the activation level of a "
  • "Pearson Correlation Score A slightly more sophisticated way to determine the similarity between people’s inter- ests is to use a Pearson correlation coefficient. The correlation coefficient is a mea- sure of how well two sets of data fit on a straight line. The formula for this is more complicated t"
  • "Simulated annealing is an optimization method inspired by physics. Annealing is the process of heating up an alloy and then cooling it down slowly. Because the atoms are first made to jump around a lot and then gradually settle into a low energy state, the atoms can find a low energy configuration."
  • "The flight scheduling example works because moving a person from the second to the third flight of the day would probably change the overall cost by a smaller amount than moving that person to the eighth flight of the day would. If the flights were in random order, the optimization methods would wor"
  • "Squaring the numbers is common practice because it makes large differences count for even more. This means an algorithm that is very close most of the time but far off occasionally will fare worse than an algorithm that is always somewhat close. This is often desired behavior, but there are situatio"
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
你可能会关注的书籍

O'Reilly Media的其他书籍查看全部

下载
收藏