“This is a two-part meetup. The first is a more basic level. The second covers more advanced information.

This session introduces the fundamentals of Bayesian statistics, the concepts of probability for single and two events, prior, likelihood and posterior. We proof the Bayes’ Theorem and discuss its dyachronic interpretation (data vs hypothesis), then the concept of conjugate prior is illustrated. On the top of these notions, we introduce bayesian networks and (hyper-)parameters’ inference. The session is led by using Python notebooks which illustrate the practical implementations of the bayesians and the use of the PyMC3 module.”

Price: Free

Link: http://www.foocafe.org/malmoe/events/2008-bayesian-statistics-inference-bayesian-networks