The upcoming book Model-Based Machine Learning by John Winn and Chris Bishop presents machine learning in a model based, probabilistic framework.
The book contains in detail several examples (skill ranking, email filtering, time series modeling) in a Bayesian probabilistic framework.
All the examples are solved using message passing or belief propagation inference with Infer.NET
Could this be done with Edward? I think it would be very strong to extend the examples folder following the MBML book.