23rd
There are some excellent accounts of making use of Bayes nets. Pennies starting to drop how these things can learn as you add more and more data. I found this tutorial from Norsys useful.
17th
OK. I've come to understand that so much of ML is based upon Bayesian stats. So back to class. I began with Kevin Binz's excellent intro to Bayes theorem. He points to a short film from the Khan academy by Brit Cruise which does the intro to trees really well. Then via YouTube's suggested related clips I came to Richard Carrier's excellent and much longer clip in which he points to the following books:
McGrayne, S. B. (2011). The theory that would not die: how Bayes' rule cracked the enigma code, hunted down Russian submarines, & emerged triumphant from two centuries of controversy. New Haven Conn.: Yale University Press.
This book is a gem, McGrayne's.
Paulos, J. A. (2001). Innumeracy : mathematical illiteracy and its consequences. New York: Hill and Wang.
and,
Seife, C. (2010). Proofiness : the dark arts of mathematical deception. New York: Viking.
16th
I've been collecting material, reading and doing some scribbling offline and this AM came across a piece by @DaveWiner which nudged my thinking back to this way of working.