《Collective Intelligence in Action》PDF电子书下载
《Collective Intelligence in Action》内容简介
Satnam Alag / Manning Publications / 2008-11-7 / USD 44.99 -
"The first chapter is free (http://www.manning-source.com/books/alag/alag_meapch1.pdf) and so is the source code used in the book (http://www.manning-source.com/books/alag/CIiA-src.zip).
The book is for Java developers who want to implement “Collective Intelligence” applications in Java. It tells us about extracting and applying data from blogs, wikis and social network applications. People who read this blog know that I am not one to praise, but this book succeeds brilliantly. If you are a Java engineer and work with Web technologies, you must get this book. It covers topics such as computing similarity measures using vector models, Naïve Bayes Classifiers, inverse document frequency (idf), Machine Learning (using the Weka API), building a crawler with regular expressions, collaborative filtering (with links to open source tools), and so on.
Even if you do not work with Java, if you care for high-end Web applications, this book is for you. It reminds me of Lyon’s Java Digital Signal Processing book. It offers the gist of what academia knows, but focuses on what people (engineers and researchers) do in practice.
The book is not meant for academia however. There are references, but no theorem."
-- by Daniel Lemire http://feeds.feedburner.com/~r/daniel-lemire/atom/~3/304207263/
"The first chapter is free (http://www.manning-source.com/books/alag/alag_meapch1.pdf) and so is the source code used in the book (http://www.manning-source.com/books/alag/CIiA-src.zip).
The book is for Java developers who want to implement “Collective Intelligence” applications in Java. It tells us about extracting and applying data from blogs, wikis and social network applications. People who read this blog know that I am not one to praise, but this book succeeds brilliantly. If you are a Java engineer and work with Web technologies, you must get this book. It covers topics such as computing similarity measures using vector models, Naïve Bayes Classifiers, inverse document frequency (idf), Machine Learning (using the Weka API), building a crawler with regular expressions, collaborative filtering (with links to open source tools), and so on.
Even if you do not work with Java, if you care for high-end Web applications, this book is for you. It reminds me of Lyon’s Java Digital Signal Processing book. It offers the gist of what academia knows, but focuses on what people (engineers and researchers) do in practice.
The book is not meant for academia however. There are references, but no theorem."
-- by Daniel Lemire http://feeds.feedburner.com/~r/daniel-lemire/atom/~3/304207263/
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