{"id":16520864,"url":"https://github.com/jhrcook/bayesian-analysis-with-python_e2","last_synced_at":"2025-04-09T20:32:30.687Z","repository":{"id":115869849,"uuid":"286271716","full_name":"jhrcook/bayesian-analysis-with-python_e2","owner":"jhrcook","description":"My notes on \"Bayesian Analysis with Python\" (edition 2) by Osvaldo Martin.","archived":false,"fork":false,"pushed_at":"2021-01-08T20:37:40.000Z","size":35436,"stargazers_count":4,"open_issues_count":0,"forks_count":3,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-23T22:25:31.916Z","etag":null,"topics":["bayesian","bayesian-analysis","bayesian-analysis-with-python","bayesian-data-analysis","bayesian-data-science","bayesian-statistics","data-science","linear-regression","pymc3","python","python3"],"latest_commit_sha":null,"homepage":"https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition","language":"Jupyter 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Notebook","readme":"# Notes on *Bayesian Analysis with Python* (2e)\n\n[![python](https://img.shields.io/badge/Python-3.9.1-3776AB.svg?style=flat\u0026logo=python\u0026logoColor=FFDB4D)](https://www.python.org)\n[![jupyter](https://img.shields.io/badge/Jupyter-Lab-F37626.svg?style=flat\u0026logo=Jupyter)](https://jupyterlab.readthedocs.io/en/stable)\n[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit\u0026logoColor=white)](https://github.com/pre-commit/pre-commit) \u003cbr\u003e\n[![jhc github](https://img.shields.io/badge/GitHub-jhrcook-181717.svg?style=flat\u0026logo=github)](https://github.com/jhrcook)\n[![jhc twitter](https://img.shields.io/badge/Twitter-@JoshDoesA-00aced.svg?style=flat\u0026logo=twitter)](https://twitter.com/JoshDoesa)\n[![jhc website](https://img.shields.io/badge/Website-Joshua_Cook-5087B2.svg?style=flat\u0026logo=telegram)](https://joshuacook.netlify.com)\n\nThis repository contains by notes on the book [*Bayesian Analysis with Python* (2e)](https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition) by Osvaldo Martin.\nI have a good understanding of the basics of Bayesian analysis after working through Richard McElreath's [*Statistical Rethinking*](https://xcelab.net/rm/statistical-rethinking/) (my [notes](https://github.com/jhrcook/statistical-rethinking)), and I want to get more practice using Python and Bayesian analysis techniques.\nThis book should serve as a strong introduction to the [PyMC3](https://docs.pymc.io) library and provide another perspective on conducting Bayesian data analysis.\n\n## Notes\n\n[Ch 2. Programming Probabilistically](02_programming-probabilistically.md)  \n[Ch 3. Modeling with Linear Regression](03_modeling-with-linear-regression.md)  \n[Ch 4. Generalized Linear Models](04_generalized-linear-models.md)  \n[Ch 5. Model Comparison](05_model-comparison.md)  \n[Ch 6. Mixture Models](06_mixture-models.md)  \n[Ch 7. Gaussian Processes](07_gaussian-processes.md)  \n[Ch 8. Inference Engines](08_inference-engines.md)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjhrcook%2Fbayesian-analysis-with-python_e2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjhrcook%2Fbayesian-analysis-with-python_e2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjhrcook%2Fbayesian-analysis-with-python_e2/lists"}