Bayesian Analysis with Python

Bayesian Analysis with Python, 2nd Edition, is a textbook that introduces applied Bayesian inference and probabilistic programming in Python. The text presents a computational approach to statistical modeling built around PyMC3 and the exploratory analysis library ArviZ.

The volume uses synthetic and real-world datasets to guide readers through practical modeling workflows. Coverage addresses generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes.

Structured as a tutorial with sample problems and practice exercises, the book serves students, data scientists, researchers, and developers. Prior experience with Python and NumPy is assumed, but no previous background in statistics is required.