List of Figures

 

Chapter 1. Probabilistic programming in a nutshell

Figure 1.1. Last year everyone loved my product, but what will happen next year?

Figure 1.2. How a probabilistic reasoning system predicts the outcome of a corner kick

Figure 1.3. The basic components of a probabilistic reasoning system

Figure 1.4. By altering the query and evidence, the system can now infer why a goal was scored.

Figure 1.5. By taking into account evidence from the outcome of the last corner kick, the probabilistic reasoning system can produce a better prediction of the next corner kick.

Figure 1.6. You can use a learning algorithm to learn a new model based on a set of experiences. This new model can then be used for future inferences.

Figure 1.7. A probabilistic programming system is a probabilistic reasoning system that uses a programming language to represent probabilistic models.

Figure 1.8. A probabilistic program defines a process of randomly generating outputs, given inputs.

Figure 1.9. How Figaro uses Scala to provide a probabilistic programming system

Chapter 2. A quick Figaro tutorial

Figure 2.1. Review of probabilistic reasoning essentials

Figure 2.2. The key concepts of Figaro and how they fit together

Figure 2.3. The relationship between Scala variables and values, and Figaro elements and possible values

Figure 2.4. Structure of the Hello World model as a graph. Each node in the graph is an element. Edges in the graph show when one element is used by another element.