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Programming Collective Intelligence: Building Smart Web 2.0 Applications [Paperback]

Toby Segaran
4.1 out of 5 stars  See all reviews (17 customer reviews)
RRP: 25.99
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Book Description

26 Aug 2007

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 a dataset
  • 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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Programming Collective Intelligence: Building Smart Web 2.0 Applications + Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
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Product details

  • Paperback: 362 pages
  • Publisher: O'Reilly Media; 1 edition (26 Aug 2007)
  • Language: English
  • ISBN-10: 0596529325
  • ISBN-13: 978-0596529321
  • Product Dimensions: 23.4 x 17.8 x 2.3 cm
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (17 customer reviews)
  • Amazon Bestsellers Rank: 45,457 in Books (See Top 100 in Books)
  • See Complete Table of Contents

More About the Author

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Product Description

Review should buy this book.... It's well written manual that'll handily expand your repetoire.
-- London Perl M(ou)ngers,, December 2007

About the Author

Toby Segaran is the author of Programming Collective Intelligence, a very popular O'Reilly title. He was the founder of Incellico, a biotech software company later acquired by Genstruct. He currently holds the title of Data Magnate at Metaweb Technologies and is a frequent speaker at technology conferences.

Inside This Book (Learn More)
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews

Most Helpful Customer Reviews
32 of 33 people found the following review helpful
5.0 out of 5 stars excellent - accessible machine learning 4 Dec 2007
This is excellent - forget the marketing rubbish about making better web 2.0 apps: It is all about machine learning - the science of how Amazon and others can make recommendations based on the ordering patterns of others.

The difference between it and other texts on this machine learning, is how accessible it is, and how apt the data sets it chooses are. Machine learning is an active area of research, and I was surprised that this book even covers kernel methods.

It generates a real appetite to learn more about the theory of machine learning: Which you will need, as most machine learning text books are mathematically tough going and dry.

I only wish I could skip the day job for a week and study this book from cover to cover.
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4 of 4 people found the following review helpful
5.0 out of 5 stars Very Useful 22 Oct 2008
I was a beginner in both python and general programming when I got this book together with a book on how to use Python in general.

I actually found this book more useful than the general Python book as the use of examples is a much better way of learning (in my opinion). The examples introduced get more and more complex through the book which then forces you to learn about those programs in order to understand what they've done.

The fact that it exposes you to live web based data from the beginning is very useful indeed. My only wish would be that the formatting would be a bit clear. Python seems to thrive on using indentation rather than brackets and it can be difficult to see exactly which level of indentation is being used.

You need a ruler to use it!
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3 of 3 people found the following review helpful
5.0 out of 5 stars Fascinating and inspiring 13 Mar 2011
Format:Paperback|Verified Purchase
This book covers algorithms that elsewhere are treated as artificial intelligence, but here are dealt with very rapidly and in a programmer's mindset. It's great to see ideas that have been considered "academic", such as neural networks, treated as no more frightening than other algorithms such as sorting. The description of how to use live web site APIs is also a great feature of this book.
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22 of 25 people found the following review helpful
5.0 out of 5 stars A truly outstanding book 29 Mar 2008
This book is definitely worth having on your bookshelf. It breaks down one of the most complex and demanding subjects into delightful, succinct and digestible pieces.

Having dredged my way through similar books in the past, I wasn't expecting too much, but Programming Collective Intelligence is remarkable. I found this book gripping; completing each example was very rewarding, and has now got me hooked on learning more.

I ended up working my way through the entire book, and really feel that it was time well spent. I now feel that I actually understand the concepts and algorithms surrounding machine learning/AI/data mining, and as a bonus have become familiar with a huge number of web 2.0 APIs.

The source code is almost impeccable. Most programming books falter on sloppy and/or incomplete code, but Programming Collective Intelligence is well explained and has the complete Python code written in the book, as well as being available for download. I was able to do every example without any major problems, despite having never used the Python language before.

Well written & diagrammed, with good examples and wonderful explanations: this a fantastic book, and to be highly recommended.
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1 of 1 people found the following review helpful
5.0 out of 5 stars very good introduction 11 Sep 2008
This book really does an awesome job at guiding you through the process of using collective intelligence in your own applications. For me, a bit more explanation on the math would be nice, but if i just pay attention it still seems to stick, so it's not crucial.
just, well, get it! it's good

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4 of 5 people found the following review helpful
By J.H.
Format:Paperback|Verified Purchase
This book is essentially a brief introduction to the topic of machine learning from a practical and non-mathematical perspective using code examples written in Python.

The intended audience for this book are developers with no background in machine learning but wanting to use machine learning techniques in their projects. Newcomers to the topic of machine learning may find the book useful but those with a background in maths or machine learning will likely find the book to have a somewhat limited appeal.
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5.0 out of 5 stars Great introduction to machine learning 17 Dec 2013
Format:Paperback|Verified Purchase
Was one of the first books I read related to Machine Learning - was a lucky guess - it has helped bring me up to speed and made the other books a lot easier to comprehend. Very practical and comprehensive, giving you (the reader) a good grounding in the subject (as a practitioner)
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1.0 out of 5 stars Lots of mistakes! 10 Jun 2013
Format:Paperback|Verified Purchase
The book is very short, concise, cryptic sometimes and it contains lots of mistakes (in the code and typos in the text content).
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Most Recent Customer Reviews
4.0 out of 5 stars Great Foundation
For AI idiots like myself this was a great and non condescending introduction.

Although Python based I found the algorithms clear enough to translate into Erlang without... Read more
Published on 10 Feb 2012 by Dr. Edward Austin
5.0 out of 5 stars Machine Learning explained
A few people complained about there beeing too little maths in the book, and I would agree. Instead the author explains or at least tries to explain by example and uses python code... Read more
Published on 24 July 2011 by Md Sykora
5.0 out of 5 stars Very clear tutorial to machine learning related things
Most of the similar material on the web is difficult to read and learn with heavy mathematic bias but not this one. Very nice examples with complete Python-implementation. Read more
Published on 13 Sep 2010 by J.Makelainen
3.0 out of 5 stars Provides background into algos and sample code
It is useful for providing insight into various algo's and does include a lot of sample code. The sample code is just that and not something you could copy and paste, tweak and use... Read more
Published on 24 Aug 2010 by richardyeo
5.0 out of 5 stars read this book!
I have read quite a few books on AI and this is by far the best. It is incredibly well written and makes what others have made difficult very accessible - no matter what your... Read more
Published on 3 Aug 2010 by Mr. Emmett Miller
1.0 out of 5 stars Poor attempt
Whilst the book starts out positively enough (hence the 1 review star), it quickly degenerates into a rambling disorganised text that neither adequately covers collective... Read more
Published on 7 Aug 2009 by Zac
5.0 out of 5 stars great book !
This is a very interesting book. Even though it contains code written in python and I don't know that language, it's clear enough to understand the concepts. Read more
Published on 29 April 2009 by Tom De Bruyne
3.0 out of 5 stars Good overview of topic, but assumes you must learn Python
This book provides an good collection of the various algorithms that can be used in this brave new world of Web 2.0. Read more
Published on 30 Nov 2008 by John Smith
5.0 out of 5 stars Keeps coming back, again and again
This is an excellent book that I keep coming back to again and again. It explains a variety of complex machine learning algorithms with easy to follow, clear, concise code. Read more
Published on 5 Nov 2008 by R. Young
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