By Osvaldo Martin, Ravin Kumar and Junpeng Lao
Hands on approach with PyMC and ArviZ focusing on the practice of applied statistics.
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.
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.
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.
By Richard McElreath
A Bayesian Course with Examples in R and Stan.
By Michael Lee and Eric-Jan Wagenmakers
Focused on using Bayesian statistics in cognitive modeling.
By Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin
A comprehensive, standard, and wonderful textbook on Bayesian methods.