Think Bayes Paperback – 4 Oct 2013
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Bayesian Statistics in Python
About the Author
Allen Downey is a Professor of Computer Science at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master’s and Bachelor’s degrees from MIT.
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Top Customer Reviews
Whilst I understand that printing in colour would have been more expensive, syntax highlighting (even if just in the PDF) would have been greatly appreciated. The code samples could have, regardless, have been better typeset to differentiate them from the prose.
The book disposes of Bayes in the first chapter and the rest of the book is examples which are well thought out.
However the difficulty is with the python examples - the code is all in Python 2 so if you run it in the latest version of Python 3 you will gets lots of silly errors which are a pain to debug, also you need to download lots of modules if you are running the code on windows - the go to site is Christoph Gohlke's Unofficial Windows Binaries for Python Extension Packages.
It takes three or four downloads per example to get things working.
Having said that this is my first go with Python and I quite liked it.
So overall the examples need to be reworked, but otherwise quite entertaining.
Most Helpful Customer Reviews on Amazon.com (beta)
This is a great book and a good introduction to the application of Bayes's Theorem in a number of scenarios. The theoretical aspects are well accessible and the Python code is sufficiently clear. This is not an introduction to Python and readers should be relatively familiar with Python or other high level languages to make the most out of this book.
The PDF for the book is freely available from Green Tea Press. If you are concerned about the lack of a table of contents in the mobi version, get the paper copy until this is resolved... I would highly recommend it.
Overall the book is super interesting, although explanation style could be better.
On the other hand, if you do relate well to math notation, you might find the computer code a distraction.
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