Programming Collective Intelligence: Building Smart Web 2.0 Applications by Toby Segaran Summary and Reviews
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Book Reviews of Programming Collective Intelligence: Building Smart Web 2.0 Applications
Book Review: Programming Collective Intelligence: Building Smart Web 2.0 Applications
Summary: 5 Stars
Excellent book. Most interesting to me was the amount of data
available for free download. Housing prices from zillow. Historical
stock information from Yahoo. etc. This book shows you how easy it
is to download the data and analyse it.
Book Review: Putting Theory into Practice
Summary: 4 Stars
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.
In the end, this book is a great introduction to what is available for those new to machine learning, and shows better than any other book how it applies to Web 2.0. Major strengths of this book are its broad coverage, and the practicality of its contents. It is a great book for those who are struggling with the theory, and/or those who need to see an example of how the theory can be applied in a concise, practical way.
To the author: I expect this book will get a second edition, as the premise behind the book is such a good one. If that happens, perhaps beef up the equations a bit in the appendix, and cite some references or a bibliography for those readers interested in some more in depth reading about the theory behind all these wonderful techniques. (The lack of a bibliography is why I gave it 4 stars out of 5, I really think that those who are new to the subject would benefit greatly from knowing what sits on your bookshelf.)
Book Review: Great roundup of machine learning techniques
Summary: 5 Stars
This book has great examples that make the machine learning algorithms come alive.
Most chapters have instructions on how to hook up the code to web based APIs so you can get some real data to play with.
I hope there's more books like this.
Book Review: Excellent
Summary: 5 Stars
I do application/systems program and this was a great introduction to a lot of new concepts and new technologies including python and graphing/analyzing data. Excellent and timely examples, flows from one topic to the next very smoothly. Very well-written and organized.Book Review: Collective Intelligence Review
Summary: 5 Stars
The book was great, it arrived on time for class. And it was great that the instructor let us borrow his book, to see exactly which book to purchase.
Thanks,
Lynette