DBDA-python

DBDA-python provides a collection of Jupyter Notebooks that implement Bayesian data analysis models using Python and the PyMC3 library, following content from the book "Doing Bayesian Data Analysis." The primary use case is to facilitate learning and application of Bayesian modeling techniques for various data types, including hierarchical models and metric-predicted variables. Notable features include updated code compatible with PyMC3 v3.5, visualizations of models in plate notation, and multiple example notebooks covering a range of analysis scenarios.