Book Review- Machine Learning for Hackers by Ajay Ohri.
From the post:
This is review of the fashionably named book Machine Learning for Hackers by Drew Conway and John Myles White (O’Reilly ). The book is about hacking code in R.
The preface introduces the reader to the authors conception of what machine learning and hacking is all about. If the name of the book was machine learning for business analytsts or data miners, I am sure the content would have been unchanged though the popularity (and ambiguity) of the word hacker can often substitute for its usefulness. Indeed the many wise and learned Professors of statistics departments through out the civilized world would be mildly surprised and bemused by their day to day activities as hacking or teaching hackers. The book follows a case study and example based approach and uses the GGPLOT2 package within R programming almost to the point of ignoring any other native graphics system based in R. It can be quite useful for the aspiring reader who wishes to understand and join the booming market for skilled talent in statistical computing.
A chapter by chapter review that highlights a number of improvements that one hopes will appear in a second (2nd) edition. Mostly editorial, clarity type improvements that should be been caught in editorial review.
The complete source code for examples can be downloaded here. It is a little over 100 MB in zip format. I checked and the data files for various exercises are included. Which explains the size of the source code file.