Programming Collective Intelligence: Building Smart Web 2.0 Applications

by Toby Segaran

Book Overview

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...

• Format: Paperback
• Language: English
• ISBN: 0596529325
• ISBN13: 9780596529321
• Release Date: September 2007
• Publisher: O'Reilly Media
• Length: 360 Pages
• Weight: 1.20 lbs.
• Dimensions: 0.9" x 7.0" x 9.2"

Customer Reviews

One of the BEST book I've read for last 10 years

I bought lots of books on the field of machine learning, but it was hard to understand when it goes deeper with lots of mathmatics. Even though I understand the concept, I had no idea how to implement it. After reading this book, all the theories that I've been struggling with became very clear. Toby did a great job to explain these tough topics with proper graphics and easy examples. This book is one of the best book I've ever read for last 10 years (in several hundreds books).

The most accessible book on machine learning I've found

I first learned of this book just a few weeks ago, shortly before it was available. I immediately read the sample chapter on the publisher's website and was certain I had to get a hold of a copy. I was not in the least bit disappointed with what I found. It has been quite a while since I've looked at any Python code (I'm more of a Ruby fan, personally), but the code is easy to follow and it's a simple matter to extract the basic concepts into any language. I have spent quite a few years now watching the field of machine intelligence from the sidelines, occasionally reading the odd technical write up or wikipedia article, trying to wrap my brain around the basic ideas. The thing is, it's not clear to me that in some regards, it's not that complex. It's just that most of the existing books and articles are written for those immersed in the field. This book is not like that. It explains things in clear language that is easy to follow, using simplified examples and making excellent use of graphics to "show" you how it works. If you really want to dig in deep, Segaran provides exercises at the end of each chapter and gives you an appendix full of mathematical formulas (the "pure" representation of the algorithms). Finally, I should mention that the last chapter does what so many other technical books should but don't: it clearly summarizes everything he has shown you. He does this in a straightforward way so that you won't have to go searching through the book, rereading everything again, to put these techniques into practice.

Accessible introduction to complex topics

Segaran has done an excellent job of explaining complex algorithms and mathematical concepts with clear examples and code that is both easy to read and useful. His coding style in Python often reads as clearly as pseudo-code in algorithm books. The examples give real-world grounding to abstract concepts like collaborative filtering and bayesian classification. My favorite part is how he shows us code (gives it to us!) that goes out into the world, grabs masses of data and does interesting things with it. The use of a hierarchical clustering algorithm to dig into people's intrinsic desires in life as expressed in zebo is worth the price of the book alone. The graph that shows a strong connection between "wife", "kids", and "home" but a different connection between "husband", "children", and "job" is IMHO just fascinating. Gems like that make this book worth reading cover to cover. After that it can happily hang out on your shelf as a reference anytime you need to build something to mine user data and extract the wisdom of crowds.

A "hands-on" approach to an otherwise abstract topic

"Programming Collective Intelligence" is a great book. I took a college course on data mining and this book really would have come in handy. From a "hands-on" programming perspective, the information on the useful libraries in python for crawling, parsing RSS feeds, python drawing, and accessing popular RESTful APIs are really valuable. The code samples are well documented and rather timely. I think Toby has done an amazingly cogent job of demonstrating the nuts and bolts of implementing the plethora of data mining and AI-related concepts pertinent to the field of Collective Intelligence. Additionally, I was new to Python and this book was a real eye opener. In fact, more than just a book on Collective Intelligence, this is a really useful Python book. I learned a lot about Python reading through the examples and trying to get them to work on my laptop. (I was new to Python before this book, but have since started using Python at my work). The author has demystified the abstract idea of Collective Intelligence and presented the concepts in an excellent programming language choice in Python. Most of the topics covered are things most developers just hear about. Taking a college course on Data Mining or Artificial Intelligence may expose one to the ideas, but I have never encountered a book that introduced the topics covered in "Programming Collective Intelligence" in a way so intuitive and familiar to the programmer. Distilling all of the topics into a set of very useful Python script really illustrated how practical and available these concepts really are in ones daily work. I will definitely make use of Toby's book.