# ermongroup/cs228-notes

Course notes for CS228: Probabilistic Graphical Models.

Repository: https://github.com/ermongroup/cs228-notes
Canonical: https://ross.abutalabs.com/products/cs228-notes
Language: SCSS
License: MIT
License Family: permissive
Last push: 2025-06-24T21:53:16+00:00

## Health v2 (maintenance only)
Score: 45/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 28, release rhythm 35, longevity 100
- inputs: {"age_days": 3522, "days_push": 435, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2013, forks 476 (observed 2026-08-28T04:06:05.347771+00:00)

## What it is
Course notes for Stanford CS228 on probabilistic graphical models, written in Markdown and published as a static website via Jekyll and GitHub Pages. The material covers graphical models from basics through variational auto-encoders.

## Use cases
- learn probabilistic graphical models
- study Bayesian networks and Markov random fields
- understand variational inference and VAEs from first principles
- find a free alternative to a PGM textbook
- prepare for a course on graphical models
- reference material for probabilistic machine learning

## When to choose
- you want a concise, free introduction to probabilistic graphical models
- you are self-studying Stanford CS228 material
- you need readable notes bridging basics to variational auto-encoders

## When to avoid
- you need runnable code or exercises with solutions
- you want an exhaustive textbook-level treatment
- you need interactive notebooks rather than static notes

## Facets
- artifact type: learning-resource
- maturity: stable
- function: documentation, machine-learning
- domain: machine-learning, tutorials, education
- platform: python
- tags: probabilistic-graphical-models, course-notes, stanford-cs228, jekyll, variational-inference, bayesian-networks, web-server

## Member repositories
- ermongroup/cs228-notes (main) score 45

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:05.347771+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:00:54.902518+00:00, confidence not recorded.
  - readme: https://github.com/ermongroup/cs228-notes (fetched 2026-08-28T04:06:05.347771+00:00, sha ba65de7f122b)
- Data as of 2026-08-30T08:39:29.467469+00:00.