Very helpful article. Note that this is for an implementation of a Naive Bayes model, sometimes called 'idiot' Bayes. It assumes independent observations and therefore can be overconfident. More complex Bayes net models are way harder to implement. Here's a good overview of general networks:
http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html
This is not naive bayes and does not assume independent observations on the exercises. The point of using a network is to model the joint distribution with dependencies.
