aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A python tutorial on bayesian modeling techniques (PyMC3)

A Python package for causal inference in quasi-experimental settings

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

How to do Bayesian statistical modelling using numpy and PyMC3

A fast and easy to use, moddable, Python based Minecraft server!

Solve ODEs fast, with support for PyMC

Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.

LLM-based, self-correcting transpiler. Supports JAX, PyTorch, Rust, PyMC, Stan.

Code that implements Factor Analysis of Information Risk (FAIR) in combination with MITRE ATT&CK using Markov Chain Monte Carlo (via PyMC) to determine the frequency of successful attacks.

An experimental deep learning & genotype network-based system for predicting new influenza protein sequences.

Toolbox for non-linear calibration modeling.

Website: Data Umbrella & PyMC open source sessions

프로그래머를 위한 베이지안 with 파이썬

Mastering Gaussian Processes with PyMC

Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference

PriorDB aims to make choosing a prior for a Bayesian model easier

Baker Project: Dockerfile for Bayesian Analysis

GPs in PyTensor

Simba — Bayesian Marketing Mix Modeling (MMM) platform. Media attribution, budget optimization, incrementality measurement, and scenario planning. Built on PyMC-Marketing. No-code, fully transparent, enterprise-ready.