Part 2. Writing probabilistic programs

Part 2 is all about writing probabilistic programs to represent whatever situation you’re interested in. The goal of this part of the book is not only to give you the tools to write programs but also to make sure you understand what these programs mean and why you might choose to use a certain programming technique. Chapter 4 provides an introduction to probabilistic modeling and the basic concepts of probabilistic programming; although there’s little programming in this chapter, it will help you approach the task of writing a probabilistic program in a well-grounded, principled way. Chapter 5 presents the two main modeling paradigms that are at the center of probabilistic programming: Bayesian networks and Markov networks. Chapters 6 through 8 build on the material of chapters 4 and 5 with more-advanced modeling techniques, including using collections, object-oriented programming, and modeling dynamic systems.