#5353rd of 55 in Learning and cookbooks
pyprobml
Notebooks that reproduce figures from the Probabilistic Machine Learning books
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- Stars
- 7.2k
- License
- MIT
- Last commit
- Feb 2026
- Last release
- May 2022
- Language
- Jupyter Notebook
Missed the latest GitHub check; these facts may be older.
Overview
Python 3 Jupyter notebooks that regenerate the figures in "Probabilistic Machine Learning: An Introduction" (book 1) and "Advanced Topics" (book 2). Code uses numpy, scipy, matplotlib and sklearn, with JAX in much of book 2 and TensorFlow 2 or Torch in parts of book 1. The repo has been in maintenance mode since September 2022.
Who it is for: Students and readers working through the Probabilistic ML books
Strengths
- Notebooks organized by chapter for both book 1 and book 2
- Runs in Colab with free GPU/TPU; Colab intro notebook included
- Status dashboards show which figure notebooks currently run
- Shared plotting helpers live in the separate probml-utils package
Weaknesses
- Maintenance mode since September 2022; last release 2022-05-05
- Tied to the books; not a standalone library or course
- JAX, TensorFlow and Torch must be installed manually first
- No Docker setup; local install is a requirements.txt plus manual steps
What it needs
- GPU optional
- Needs JAX, TensorFlow 2, Torch, numpy, scipy, matplotlib, scikit-learn
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