集体智慧编程（影印版）
出版时间：2008年03月
页数：334
“好极了！我无法想象会有更好的方式来开始学习这些算法和方法，也没有更好的方式能让我（一个人工智能老家伙）头脑中关于它们的细节知识迅速复苏。”
—— Dan Russel，Uber Tech负责人，Google
“Toby的书非常成功地将复杂的机器学习算法问题分解为现实而易理解的例子，可直接用于分析当前Web上的社会化交互行为。如果我在两年前拥有这本书，一定会省下大把浪费在迷途歧路上的宝贵时间。”
—— Tim Wolters，CTO，Collective Intellect
想要探寻搜索排名、产品推荐、社会化书签和在线匹配背后的力量吗？这本颇具魅力的书籍向你展现如何创建Web 2.0应用程序，从参与性Internet应用程序产生的大量数据中挖掘金矿。运用本书中介绍的先进算法，你可以编写聪明的程序，以访问其他网站那些有趣的数据集，从自有应用程序的用户中收集数据，或者分析和理解你所发现的数据。
《集体智慧编程》将你带入机器学习和统计的世界，并且阐释了如何从你和他人每天收集的信息中获得关于用户体验、市场营销、个性品味及人类行为的结论。每个算法的描述都十分简明清晰，相关代码均可以立即用于你的网站、博客、Wiki或特定应用程序。本书讲解了下列主题：
* 可以让在线零售商推荐产品或媒体的协作过滤技术
* 用于在大数据集中发现同类项组的聚类方法
* 从数以百万计可能方案中选择问题最佳解决方案的最优化算法
* 贝叶斯过滤，用在基于单词类型和其他特征的垃圾信息过滤中
* 支持向量（support-vector）机器，用于在线交友网站中的速配
* 用于问题解决的演化智能——计算机如何通过多次玩同样的游戏，改进自身代码并获得技能提升
每一章都包含了相关练习，可通过扩展使算法变得更强大。超越简单的数据库支持应用程序模式，让 Internet数据财富为你所用。
—— Dan Russel，Uber Tech负责人，Google
“Toby的书非常成功地将复杂的机器学习算法问题分解为现实而易理解的例子，可直接用于分析当前Web上的社会化交互行为。如果我在两年前拥有这本书，一定会省下大把浪费在迷途歧路上的宝贵时间。”
—— Tim Wolters，CTO，Collective Intellect
想要探寻搜索排名、产品推荐、社会化书签和在线匹配背后的力量吗？这本颇具魅力的书籍向你展现如何创建Web 2.0应用程序，从参与性Internet应用程序产生的大量数据中挖掘金矿。运用本书中介绍的先进算法，你可以编写聪明的程序，以访问其他网站那些有趣的数据集，从自有应用程序的用户中收集数据，或者分析和理解你所发现的数据。
《集体智慧编程》将你带入机器学习和统计的世界，并且阐释了如何从你和他人每天收集的信息中获得关于用户体验、市场营销、个性品味及人类行为的结论。每个算法的描述都十分简明清晰，相关代码均可以立即用于你的网站、博客、Wiki或特定应用程序。本书讲解了下列主题：
* 可以让在线零售商推荐产品或媒体的协作过滤技术
* 用于在大数据集中发现同类项组的聚类方法
* 从数以百万计可能方案中选择问题最佳解决方案的最优化算法
* 贝叶斯过滤，用在基于单词类型和其他特征的垃圾信息过滤中
* 支持向量（support-vector）机器，用于在线交友网站中的速配
* 用于问题解决的演化智能——计算机如何通过多次玩同样的游戏，改进自身代码并获得技能提升
每一章都包含了相关练习，可通过扩展使算法变得更强大。超越简单的数据库支持应用程序模式，让 Internet数据财富为你所用。
- Foreword
- Preface
- 1. Introduction to Collective Intelligence
- What Is Collective Intelligence?
- What Is Machine Learning?
- Limits of Machine Learning
- Real-Life Examples
- Other Uses for Learning Algorithms
- 2. Making Recommendations
- Collaborative Filtering
- Collecting Preferences
- Finding Similar Users
- Recommending Items
- Matching Products
- Building a del.icio.us Link Recommender
- Item-Based Filtering
- Using the MovieLens Dataset
- User-Based or Item-Based Filtering?
- Exercises
- 3. Discovering Groups
- Supervised versus Unsupervised Learning
- Word Vectors
- Hierarchical Clustering
- Drawing the Dendrogram
- Column Clustering
- K-Means Clustering
- Clusters of Preferences
- Viewing Data in Two Dimensions
- Other Things to Cluster
- Exercises
- 4. Searching and Ranking
- What’s in a Search Engine?
- A Simple Crawler
- Building the Index
- Querying
- Content-Based Ranking
- Using Inbound Links
- Learning from Clicks
- Exercises
- 5. Optimization
- Group Travel
- Representing Solutions
- The Cost Function
- Random Searching
- Hill Climbing
- Simulated Annealing
- Genetic Algorithms
- Real Flight Searches
- Optimizing for Preferences
- Network Visualization
- Other Possibilities
- Exercises
- 6. Document Filtering
- Filtering Spam
- Documents and Words
- Training the Classifier
- Calculating Probabilities
- A Nai?Nve Classifier
- The Fisher Method
- Persisting the Trained Classifiers
- Filtering Blog Feeds
- Improving Feature Detection
- Using Akismet
- Alternative Methods
- Exercises
- 7. Modeling with Decision Trees
- Predicting Signups
- Introducing Decision Trees
- Training the Tree
- Choosing the Best Split
- Recursive Tree Building
- Displaying the Tree
- Classifying New Observations
- Pruning the Tree
- Dealing with Missing Data
- Dealing with Numerical Outcomes
- Modeling Home Prices
- Modeling “Hotness”
- When to Use Decision Trees
- Exercises
- 8. Building Price Models
- Building a Sample Dataset
- k-Nearest Neighbors
- Weighted Neighbors
- Cross-Validation
- Heterogeneous Variables
- Optimizing the Scale
- Uneven Distributions
- Using Real Data—the eBay API
- When to Use k-Nearest Neighbors
- Exercises
- 9. Advanced Classification: Kernel Methods and SVMs
- Matchmaker Dataset
- Difficulties with the Data
- Basic Linear Classification
- Categorical Features
- Scaling the Data
- Understanding Kernel Methods
- Support-Vector Machines
- Using LIBSVM
- Matching on Facebook
- Exercises
- 10. Finding Independent Features
- A Corpus of News
- Previous Approaches
- Non-Negative Matrix Factorization
- Displaying the Results
- Using Stock Market Data
- Exercises
- 11. Evolving Intelligence
- What Is Genetic Programming?
- Programs As Trees
- Creating the Initial Population
- Testing a Solution
- Mutating Programs
- Crossover
- Building the Environment
- A Simple Game
- Further Possibilities
- Exercises
- 12. Algorithm Summary
- Bayesian Classifier
- Decision Tree Classifier
- Neural Networks
- Support-Vector Machines
- k-Nearest Neighbors
- Clustering
- Multidimensional Scaling
- Non-Negative Matrix Factorization
- Optimization
- A. Third-Party Libraries
- B. Mathematical Formulas
- Index
书名：集体智慧编程（影印版）
作者：Toby Segaran 著
国内出版社：东南大学出版社
出版时间：2008年03月
页数：334
书号：978-7-5641-1139-7
原版书出版商：O'Reilly Media
The animals on the cover of Programming Collective Intelligence are King penguins
(Aptenodytes patagonicus). Although named for the Patagonia region, King Penguins
no longer breed in South America; the last colony there was wiped out by 19thcentury
sealers. Today, these penguins are found on sub-Antarctic islands such as
Prince Edward, Crozet, Macquarie, and Falkland Islands. They live on beaches and
flat glacial lands near the sea. King penguins are extremely social birds; they breed in
colonies of as many as 10,000 and raise their young in crèches.
Standing 30 inches tall and weighing up to 30 pounds, the King is one of the largest
types of penguin—second only to its close relative the Emperor penguin. Apart from
size, the major identifying feature of the King penguin is the bright orange patches on
its head that extend down to its silvery breast plumage. These penguins have a sleek
body frame and can run on land, instead of hopping like Emperor penguins. They are
well adapted to the sea, eating a diet of fish and squid, and can dive down 700 feet,
far deeper than most other penguins go. Because males and females are similar in size
and appearance, they are distinguished by behavioral clues such as mating rituals.
King penguins do not build nests; instead, they tuck their single egg under their
bellies and rest it on their feet. No other bird has a longer breeding cycle than these
penguins, who breed twice every three years and fledge a single chick. The chicks are
round, brown, and so fluffy that early explorers thought they were an entirely
different species of penguin, calling them “woolly penguins.” With a world population
of two million breeding pairs, King penguins are not a threatened species, and
the World Conservation Union has assigned them to the Least Concern category.
(Aptenodytes patagonicus). Although named for the Patagonia region, King Penguins
no longer breed in South America; the last colony there was wiped out by 19thcentury
sealers. Today, these penguins are found on sub-Antarctic islands such as
Prince Edward, Crozet, Macquarie, and Falkland Islands. They live on beaches and
flat glacial lands near the sea. King penguins are extremely social birds; they breed in
colonies of as many as 10,000 and raise their young in crèches.
Standing 30 inches tall and weighing up to 30 pounds, the King is one of the largest
types of penguin—second only to its close relative the Emperor penguin. Apart from
size, the major identifying feature of the King penguin is the bright orange patches on
its head that extend down to its silvery breast plumage. These penguins have a sleek
body frame and can run on land, instead of hopping like Emperor penguins. They are
well adapted to the sea, eating a diet of fish and squid, and can dive down 700 feet,
far deeper than most other penguins go. Because males and females are similar in size
and appearance, they are distinguished by behavioral clues such as mating rituals.
King penguins do not build nests; instead, they tuck their single egg under their
bellies and rest it on their feet. No other bird has a longer breeding cycle than these
penguins, who breed twice every three years and fledge a single chick. The chicks are
round, brown, and so fluffy that early explorers thought they were an entirely
different species of penguin, calling them “woolly penguins.” With a world population
of two million breeding pairs, King penguins are not a threatened species, and
the World Conservation Union has assigned them to the Least Concern category.
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