Bayesian Modeling and Computation in Python

By Osvaldo Martin, Ravin Kumar and Junpeng Lao

Hands on approach with PyMC and ArviZ focusing on the practice of applied statistics.

Website + code

Bayesian Methods for Hackers

By Cameron Davidson-Pilon

The “hacker” in the title means learn-as-you-code. This hands-on introduction teaches intuitive definitions of the Bayesian approach to statistics, worklflow and decision-making by applying them using PyMC.

Github repo

Project homepage

Bayesian Analysis with Python

By Osvaldo Martin

A great introductory book written by a maintainer of PyMC. It provides a hands-on introduction to the main concepts of Bayesian statistics using synthetic and real data sets. Mastering the concepts in this book is a great foundation to pursue more advanced knowledge.

Book website

Code and errata in PyMC 3.x

Doing Bayesian Data Analysis

By John K. Kruschke

Principled introduction to Bayesian data analysis, with practical exercises. The book’s original examples are coded in R, but notebooks with a PyMC port of the code are available through the links below.

Book website

PyMC port of the second edition’s code

Statistical Rethinking

By Richard McElreath

A Bayesian Course with Examples in R and Stan.

Book website

PyMC 3.x port of the code

Bayesian Cognitive Modeling: A Practical Course

By Michael Lee and Eric-Jan Wagenmakers

Focused on using Bayesian statistics in cognitive modeling.

Book website

PyMC 3.x implementations

Bayesian Data Analysis

By Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin

A comprehensive, standard, and wonderful textbook on Bayesian methods.

Book website

Examples and exercises implemented in PyMC 3.x