This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, securit

Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural a

This book unifies a broad range of programming language concepts under the framework of type systems and structural operational semantics.

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This boo

Summary Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you'll learn how to use the PP paradigm to mo