I got started when a colleague recommended this series of 3 hands-on blog posts with PyMC3: https://twiecki.io/blog/2013/08/12/bayesian-glms-1/ which build up from normal linear regression, to non-quadratic error terms, to hierarchical modeling.
(Disclosure: I use probabilistic programming at Triplebyte, and have previously written a bit about it here https://triplebyte.com/blog/bayesian-inference-for-hiring-en... , though this blog post is really just at the level of Naive Bayes to be easier to understand.)
(Disclosure: I use probabilistic programming at Triplebyte, and have previously written a bit about it here https://triplebyte.com/blog/bayesian-inference-for-hiring-en... , though this blog post is really just at the level of Naive Bayes to be easier to understand.)