pymc3 开源项目推荐（141 个）

probml /pyprobml

Python code for "Probabilistic Machine learning" book by Kevin Murphy

github /covid19-dashboard

A site that displays up to date COVID-19 stats, powered by fastpages.

JWarmenhoven /DBDA-python

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

aloctavodia /BAP

Bayesian Analysis with Python (Second Edition)

exoplanet-dev /exoplanet

Fast & scalable MCMC for all your exoplanet needs!

pymc-learn /pymc-learn

pymc-learn: Practical probabilistic machine learning in Python

junpenglao /GLMM-in-Python

Python 中的广义线性混合效应模型

jonsedar /pymc3_vs_pystan

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

AlexIoannides /pymc-example-project

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

junpenglao /Bayesian-Cognitive-Modeling-in-Pymc3

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

AmpersandTV /pymc3-hmm

Hidden Markov models in PyMC3

Priesemann-Group /covid19_inference

Bayesian python toolbox for inference and forecast of the spread of the Coronavirus

jgoerner /distribution-cheatsheet

📈📄👀A lookup repo for a variety of discrete and continuous distributions (incl. Beta, Binomial, Cauchy, Chi-squared, Geometric, Hypergeometric, Normal & Poisson)

junpenglao /Planet_Sakaar_Data_Science

A colourful collection of codes and notebooks, like Planet Sakaar

CamDavidsonPilon /lifestyles

Work-In-Progress: conjoint analysis in Python

AlexIoannides /pymc-stochastic-process

Bayesian Inference and parameter estimation in quant finance.

pollsposition /models

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

suriyadeepan /pm-pyro

PyMC3-like Interface for Pyro

MikeS96 /bayes_statististics

Bayesian Statistics MOOC by Coursera - Solutions in Python

elizavetasemenova /EmbracingUncertainty

Material for AMLD 2020 workshop "Bayesian Inference: embracing uncertainty"