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.
An experimental deep learning & genotype network-based system for predicting new influenza protein sequences.
Website: Data Umbrella & PyMC open source sessions
프로그래머를 위한 베이지안 with 파이썬
Toolbox for non-linear calibration modeling.
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
Physiological signals recorded with a Microsoft Band 2 are processed and modeled with a basic bayesian model to infer exaltation and relaxation states of mind
Distributed differentiable graph computation using PyTensor
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