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Programming Collective Intelligence: Building Smart Web 2.0 Applications
 
 
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Programming Collective Intelligence: Building Smart Web 2.0 Applications (Paperback)

by Toby Segaran (Author)
4.5 out of 5 stars See all reviews (8 customer reviews)
RRP: £30.99
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Programming Collective Intelligence: Building Smart Web 2.0 Applications + High Performance Web Sites: Essential Knowledge for Front-End Engineers + Building Scalable Web Sites: Building, scaling, and optimizing the next generation of web applications
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Product details

  • Paperback: 360 pages
  • Publisher: O'Reilly Media, Inc.; illustrated edition edition (16 Aug 2007)
  • Language English
  • ISBN-10: 0596529325
  • ISBN-13: 978-0596529321
  • Product Dimensions: 23.2 x 17.8 x 1.8 cm
  • Average Customer Review: 4.5 out of 5 stars See all reviews (8 customer reviews)
  • Amazon.co.uk Sales Rank: 15,094 in Books (See Bestsellers in Books)

    Popular in these categories:

    #1 in  Books > Computing & Internet > Computer Science > Artificial Intelligence > Machine Learning
    #1 in  Books > Computing & Internet > Computer Science > Algorithms > Machine Learning
    #2 in  Books > Computing & Internet > Computer Science > Algorithms > Artificial Intelligence

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Product Description

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


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 a dataset; and, 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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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

8 Reviews
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 (6)
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Average Customer Review
4.5 out of 5 stars (8 customer reviews)
 
 
 
 
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22 of 22 people found the following review helpful:
5.0 out of 5 stars excellent - accessible machine learning, 4 Dec 2007
By B. OSullivan - See all my reviews
(REAL NAME)   
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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11 of 12 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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4 of 13 people found the following review helpful:
3.0 out of 5 stars Good overview of topic, but assumes you must learn Python, 30 Nov 2008
This book provides an good collection of the various algorithms that can be used in this brave new world of Web 2.0. However, I have found it difficult to use as it has all its code written in Python, a language I know little about. It seems to me that if the algorithms were explained in detail beforehand, rather than having to be worked out from the code, this would be a superb book.

Given the type of analysis this book uses, the language could be either Java (as that pervades everywhere), PHP (the language of server scripting), or (even better) Lisp, which Python attempts to emulate.

It talks about making use of the various APIs that are now available, letting you access data that can be manipulated. But it does not show how the data looks before the programs modify them, so if you want (as I do) to use a different language, you cannot see from what you need to modify, only the result.

Don't get me wrong, this is a good book, but the Python code is poorly laid out (never heard of spaces? And if you have to use spaces to indent, try three spaces), and for those like me who don't read Python it was difficult to see what is going on. I don't want to learn Python just to learn the algorithms. I would, perhaps perversely, be prepared to plough through Lisp code, and it would be good to see the Python code converted to Lisp (and Java for that matter).

So yes, this is an interesting book as it describes areas of interest, given the new types of data that are widely available, but I only give it three stars because it seems to be written for Python users, not the general programming audience.
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Most Recent Customer Reviews

3.0 out of 5 stars Brief introduction to machine learning from a practical and non-mathematical perspective
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... Read more
Published 1 month ago by J.H.

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 2 months ago by Tom De Bruyne

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 8 months ago by R. Young

5.0 out of 5 stars Very Useful
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. Read more
Published 8 months ago by M. Murdoch

5.0 out of 5 stars very good introduction
This book really does an awesome job at guiding you through the process of using collective intelligence in your own applications. Read more
Published 9 months ago by Peter Martin Hartwig

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