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Practical Probabilistic Programming

Practical Probabilistic Programming: Forward Sampling

By Avi Pfeffer

This article was excerpted from the book Practical Probabilistic Programming.

Architecture of a Spam Filter Application

By Avi Pfeffer
A spam filter consists of two components. In this article, based on my book Practical Probabilistic Programming , first describe the architecture of the reasoning component and then the learning component architecture.

Architecture of a Spam Filter Application (PDF)

Practical Probabilistic Programming: Bayesian Networks

By Avi Pfeffer , author of Practical Probabilistic Programming
In this article, I’ll talk about Bayesian networks, which are the standard framework for encoding asymmetric relationships using directed dependencies.

Bayesian Networks (PDF)

Practical Probabilistic Programming: Your First Model

In this article, excerpted from Practical Probabilistic Programming by Avi Pfeffer, we’ll build the simplest Figaro model possible.

Your First Model (PDF)

Practical Probabilistic Programming: Open universe situations with unknown number of objects

By Avi Pfeffer
An open universe situation is where you don’t know how many objects there are. This article, excerpted from Practical Probabilistic Programming, focuses on number uncertainty, which is addressed by variable size arrays.

Open universe situations with unknown number of objects (PDF)

What Probabilistic Programming is and How to Use it

By Avi Pfeffer, author of Practical Probabilistic Programming
Probabilistic programming is a way to create systems that help us make decisions in the face of uncertainty. Probabilistic reasoning combines our knowledge of a situation with the laws of probability to determine those unobserved factors that are critical to the decision. Until recently, probabilistic reasoning systems have been limited in scope, and have been hard to apply to many real world situations. Probabilistic programming is a new approach that makes probabilistic reasoning systems easier to build and more widely applicable.

What Probabilistic Programming is and How to Use it (PDF)

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