Paperback: 384 pages
Publisher: Manning Publications; 1 edition (April 19, 2012)
Product Dimensions: 7.4 x 1 x 9.2 inches
Shipping Weight: 1.4 pounds (View shipping rates and policies)
Average Customer Review: 3.7 out of 5 stars See all reviews (30 customer reviews)
Best Sellers Rank: #220,276 in Books (See Top 100 in Books) #49 in Books > Textbooks > Computer Science > Algorithms #69 in Books > Textbooks > Computer Science > Artificial Intelligence #121 in Books > Computers & Technology > Databases & Big Data > Data Mining
I agree with other reviewers' complaints on the repetitiveness and poor flow of this book, but I want to point out some other concerns and appreciations.In the preface Harrington emphasizes the importance of knowing the theory and being able to connect the theory to the algorithms and applications. I wholeheartedly agree with this statement, but it appears Harrington forgot this was his stated goal. The mathematics contained in the book is wishy-washy and vague, and its connections to the algorithms is at best tenuous. Harrington rarely explains why a particular formula is used, and when he does he's really explaining how it's used and not why it makes sense to use it (given, this is a common criticism of applied mathematics). He will often throw in mathematical jargon without a useable explanation. And for every paragraph spent on mathematical theory, five paragraphs are spent on how to use various third-party libraries for graphing, UI, and data collection (e.g., Tkinter, Matplotlib, Yahoo! PlaceFinder API, Google Shopping API, etc.). These are great, but they massively clutter the text. I'd much rather have a 200 page appendix than have circuitous detours sprinkled throughout the book.One big plus is in his treatment of support vector machines. He includes (unlike many texts which are solely about support vector machines) a complete python implementation of the Sequential Minimal Optimization algorithm. That being said, it's a horrendous piece of code clearly not written for legibility. This page (page 109) is littered with at least fifteen 1-3 letter variable names and pointless statements like "if L==H: print 'L==H'; continue".
Looking at many good reviews on , I decided to purchase this book. It's a decent book, but IMO it has been edited poorly and the code has not been tested properly.The introduction chapter got me really excited, just like other Manning's "in Action" books do. But once I started executing the code in chapter 2 "Classifying with k-nearest neighbors" I realized that the code had bugs. Though I could figure out what's wrong and fix the bugs, I did not expect this from Manning, after having read some of their excellent books like (The Quick Python Book, Second Edition, Spring in Action and Hadoop in Action).Moreover the book has some introduction to python and numpy in appendix A. I believe the author could have pointed the reader elsewhere for learning python and those pages could have been used to explain more of numpy and matplotlib, which the author uses freely without any explanation in the text. (Yup, be ready to read some online numpy and matplotlib tutorials and documentation.)If you don't know python, then you can do what I did: read The Quick Python Book, Second Edition and then attempt this book.
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