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Programming Collective Intelligence: Building Smart Web 2.0 Applications Paperback – August 23, 2007


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Product Details

  • Paperback: 362 pages
  • Publisher: O'Reilly Media; 1st edition (August 23, 2007)
  • Language: English
  • ISBN-10: 0596529325
  • ISBN-13: 978-0596529321
  • Product Dimensions: 9.2 x 7 x 0.9 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (106 customer reviews)
  • Amazon Best Sellers Rank: #48,244 in Books (See Top 100 in Books)

Editorial Reviews

About the Author

Toby Segaran is a software developer and manager at Genstruct, a computational systems biology company. He has written free web applications for his own use and put them online for others to try, including: tasktoy, a task management system; Lazybase, an online application that lets users design, create and share databases of anything they like; and Rosetta Blog, an online tool for practicing Spanish and French by reading blogs along with their translations and lists of common words. Each of these has several hundred regular users.

More About the Author

Toby Segaran is the author of "Programming Collective Intelligence," one of Amazon's top-selling AI books of all time. His latest titles, "Programming the Semantic Web" and "Beautiful Data" were released in July. He speaks on the subjects of machine learning, collective intelligence and freedom of data at conferences worldwide.

He currently holds the title of Data Magnate at Metaweb Technologies, where he works on large-scale data reconciliation problems. He is also a cofounder of freerisk.org, a non-profit aimed at creating more financial transparency.

Prior to Metaweb he founded Incellico, a biotechbology software company acquired in 2003. He holds a B.Sc. in Computer Science from MIT and US Government deems him a "Person of Exceptional Ability."

Customer Reviews

This book is one of the best book I've ever read for last 10 years (in several hundreds books).
MJ
This book introduces you to a lot of useful math for web 2.0 or social based applications and brings it all the way down to code you can write and run in Python.
Mark Jones
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.
Leo Dirac

Most Helpful Customer Reviews

164 of 170 people found the following review helpful By Syd Logan on December 18, 2007
Format: Paperback Verified Purchase
This book is probably best for those of you who have read the theory, but are not quite sure how to turn that theory into something useful. Or for those who simply hunger for a survey of how machine learning can be applied to the web, and need a non-mathematical introduction.

My area of strength happens to be neural networks (my MS thesis topic was in the subject), so I will focus on that. In a few pages of the book, the author describes how the most popular of all neural networks, backpropagation, can be used to map a set of search terms to a URL. One might do this, for example, to try and find the page best matching the search terms. Instead of doing what nearly all other authors will do, prove the math behind the backprop training algorithm, he instead mentions what it does, and goes on to present python code that implements the stated goal.

The upside of the approach is clear -- if you know the theory of neural networks, and are not sure how to apply it (or want to see an example of how it can be applied), then this book is great for that. His example of adaptively training a backprop net using only a subset of the nodes in the network was interesting, and I learned from it. Given all the reading I have done over the years on the subject, that was a bit of a surprise for me.

However, don't take this book as being the "end all, be all" for understanding neural networks and their applications. If you need that, you will want to augment this book with writings that cover some of the other network architectures (SOM, hopfield, etc) that are out there. The same goes for the other topics that it covers.
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83 of 85 people found the following review helpful By Leo Dirac on August 17, 2007
Format: Paperback Verified Purchase
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.
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67 of 70 people found the following review helpful By Thomas Duff HALL OF FAMETOP 1000 REVIEWERVINE VOICE on October 20, 2007
Format: Paperback
Have you ever wondered how some of those "collective intelligence" sites work? How Amazon can suggest books that you'll like based on your browsing history? How a search engine can rank and filter results? Toby Segaran does a very good job in revealing and teaching those types of algorithms in his book Programming Collective Intelligence: Building Smart Web 2.0 Applications. While I'm not ready to run out and build my own version of Facebook now, at least I can start to understand how sites like that are designed.

Contents:
Introduction to Collective Intelligence; Making Recommendations; Discovering Groups; Searching and Ranking; Optimization; Document Filtering; Modeling with Decision Trees; Building Price Models; Advanced Classification - Kernel Methods and SVMs; Finding Independent Features; Evolving Intelligence; Algorithm Summary; Third-Party Libraries; Mathematical Formulas; Index

In each of the chapters, Segaran takes a type of capability, be it decision-making or filtering, and shows how a programming language can be used to build that feature. His examples are all in Python, so it helps if you are already familiar with that language if you want to actually work with the code. But even if you don't know Python, the examples are clear and detailed enough that you can follow along and get the gist of what's happening. I personally think that it would help immensely if you had a background in mathematics and statistics. You can use the code here without having a detailed understanding of math, but I'm sure much of this would be more deeply appreciated if you already know about such things as Tanimoto similarity scores, Euclidean distances, or Pearson coefficients.
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18 of 18 people found the following review helpful By Thomas Lockney on September 5, 2007
Format: Paperback
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.
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