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Programming Collective Intelligence: Building Smart Web 2.0 Applications |  | Author: Toby Segaran
Publisher: O'Reilly Media
Category: Book
List Price: $39.99
Buy New: $18.59
as of 9/2/2010 23:35 CDT details
You Save: $21.40 (54%)
New (40) Used (18) from $13.92
Seller: alexhelder
Rating:  58 reviews
Sales Rank: 19095
Media: Paperback
Edition: 1
Pages: 368
Number Of Items: 1
Shipping Weight (lbs): 1.3
Dimensions (in): 9.1 x 7 x 0.7
ISBN: 0596529325
Dewey Decimal Number: 006.76
EAN: 9780596529321
ASIN: 0596529325
Publication Date: August 16, 2007
Availability: Usually ships in 1-2 business days
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Product Description
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 adataset
- 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
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| Customer Reviews:
Showing reviews 1-5 of 58
 Excellent Resource, Clear and Concise August 31, 2010
Will Gaggioli
Excellent resource for beginners and experts alike. I was impressed with the organization and the concise explanations that nonetheless explained what you need to know to understand the methods in practical statistical programming being used today. The fact that all examples are given in working code ensures that everything you need to start programming your own applications is provided for you.
The only minor fault in my mind is that it could have been easier to explain some of the hairier concepts with mathematical formulas (which the author avoids, for legitimate reason) in an appendix. An appendix is provided with seemingly similar purpose, but is underdeveloped. This is a minor issue, as all concepts can be supplemented with a simple web search.
Great sample code in Python July 1, 2010
Daniel Von Kohorn (Boston, MA USA)
A fun, fast read. Good depth, but still concise. The code is well written, broadly applicable, and easy to modify. This book is the opposite of A New Kind of Science.
Bold New Writing plus best O'reilly book ever March 29, 2010
Peter Harrington (Shanghai, The People's Rebpulic of China)
This book is spectacular, I love the way that the Author approaches a "new middle" ground of writing books. That is a book that is somewhere in between pure theory, and pure practice. That observation and follow through is simply genius. Python is an excellent choice for this as it can be easy to read. I had to study Python a little before I could totally digest the code. The book is around 300 pages but it is very dense, if someone else wrote it, it would be 600 pages.
Most O'reilly books are boring, useless documentation that you could find on the internet. This book is full of useful examples, showing you how to use "real" data, even how to get the "real" data. For that reason if you are not fond of O'reilly books, don't worry this one is different.
The downside: this book has over 1000 proposed errors and not 1 accepted errors on the O'reilly web site. Some of the code simply does not work as it's written in the book. You can download the code examples but even those do not work 100%. Check the O'reilly site to get the latest code updates. Also the book was published in 2007 and the internet has changed since then so the API's are a little out of date. By not updating this book they are doing the community and they author a huge disservice.
 Intuitive and motivating book January 4, 2010
Old Guy (Costa Rica)
0 out of 1 found this review helpful
I am not completely finished reading it but I already think it's a great introductory book which is strongly committed with transmitting intuition and comprehension of its material (machine learning) usually hard for regular people. It focuses mainly on implementation and application but some general coverage of the underlying theory is done to motivate inexpert readers. Examples are taken from the Web domain so this text can be very useful for people interested in combining BI and AI, among others. Personally, I approve using Python, which is not (yet) my favorite language, I consider it actually as a plus because it complements very well author's intention of simplicity which is all over behind the book design. This book seems to me like an excellent old school teacher among those ones who really take the right timing and words for carefully explaining you something probably difficult in an easy way so that you really will want to learn more about it.
Collective Intelligence, Smart Stuff December 30, 2009
G. van Staden (AU)
This book provides good coverage of areas essential to modern web sites. Some complex topics are covered in a manner that anyone can understand. I used this book to suppliment my college material and it helped me understand Gentic Algorithms, Path Finding and other algorithms by giving practicle examples of their use. A must have for any software professional.
Showing reviews 1-5 of 58
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