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.
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
Scalable Bayesian Modelling: A comparison
Solutions to some of the problems in "Statistical Rethinking"
Tutorials for the synthetic control method for causal inference using PyMC
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