|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Bda_py_demos||851||2 years ago||gpl-3.0||Jupyter Notebook|
|Bayesian Data Analysis demos for Python|
|Learningmachinelearning||9||7 years ago|
|Resources I am using to learn machine learning|
|Bda Exercises||6||7 years ago||Jupyter Notebook|
|My answer and codes for some exercises in Bayesian Data Analysis (3rd Ed), in IPython Notebook format|
|Kalman And Bayesian Filters In Python Zh_cn||1||4 years ago||other||Jupyter Notebook|
|Kalman and Bayesian Filters in Python的中文翻译|
|Deep Rl Bo||1||6 years ago||Jupyter Notebook|
|Bayesian Optimization for Deep Reinforcement Learning|
This repository contains some Python demos for the book Bayesian Data Analysis, 3rd ed by Gelman, Carlin, Stern, Dunson, Vehtari, and Rubin (BDA3). See also Bayesian Data Analysis course material.
Currently there are demos for BDA3 Chapters 2, 3, 4, 5, 6, 10 and 11. Furthermore, PyStan is also demoed.
Demos are in jupyter notebook (.ipynb) format. These can be directly previewed in github without need to install or run anything.
Corresponding demos were originally written for Matlab/Octave by Aki Vehtari and translated to Python by Tuomas Sivula. Some improvements were contributed by Pellervo Ruponen and Lassi Meronen. There are also corresponding R demos.