# dair-ai/ML-Course-Notes

🎓 Sharing machine learning course / lecture notes.

Repository: https://github.com/dair-ai/ML-Course-Notes
Canonical: https://ross.abutalabs.com/products/ml-course-notes
License: NOASSERTION
License Family: other
Topics: machine-learning, deep-learning, ai, natural-language-processing, data-science
Last push: 2024-05-16T18:51:33+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1630, "days_push": 839, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6651, forks 888 (observed 2026-08-28T04:09:47.297711+00:00)

## What it is
A collaborative repository of machine learning, deep learning, and NLP lecture notes covering popular courses like Andrew Ng's ML Specialization and MIT 6.S191. It organizes notes with links to course videos and descriptions for self-learners.

## Use cases
- find lecture notes for machine learning courses
- study notes for Andrew Ng machine learning specialization
- deep learning course notes for MIT 6.S191
- learn NLP from lecture notes
- supplement online ML courses with written notes
- free machine learning study material

## When to choose
- you want free written notes accompanying well-known ML/DL courses
- you prefer reading summaries over watching full lecture videos
- you want a curated index of ML course materials

## When to avoid
- you need a complete, polished textbook with exercises
- you expect all courses to have finished notes since many are marked WIP
- you need interactive coding tutorials rather than notes

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, markdown
- domain: machine-learning, deep-learning, tutorials, artificial-intelligence, data-science
- platform: -
- tags: lecture-notes, education, study-guide, community-notes, natural-language-processing, web-server

## Member repositories
- dair-ai/ML-Course-Notes (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:47.297711+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 2026-08-29T17:43:07.513211+00:00, confidence not recorded.
  - readme: https://github.com/dair-ai/ML-Course-Notes (fetched 2026-08-28T04:09:47.297711+00:00, sha 21a068ff2d77)
- Data as of 2026-08-30T08:39:29.467469+00:00.