Bayesian Statistics for Hackers

In conjunction with my ongoing learning about implementing technologies related to the Semantic Web is the topic of Bayesian statistical analysis.  The big picture idea is to use semantically stored, ontologically structured  data feeding Bayesian networks for statistical analysis in all kinds of risk assessment use cases.   The topic of Bayesian statistics is fairly math intensive, and for someone who has been out of hard core math and statistics for a couple decades, the re-training is coming along slowly.  Today I came across the following resource that appears to have a learning objective that aligns with my current learning needs on the topic.  I have yet to delve into the depths of this site’s contents, but will make this post, these initial comments, and a link to the site as a placeholder for my own future reference, and to provide a useful link in case someone else with in a similar situation might someday read these words.

Probabilistic Programming and Bayesian Methods for Hackers

Update 12/18/2014:

I have barely started reading through the contents of the site and have already come across a fascinating find:

IPython

This is the learning environment used by the contents of the book.

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