# girafe-ai/ml-course

Open Machine Learning course

Repository: https://github.com/girafe-ai/ml-course
Canonical: https://ross.abutalabs.com/products/ml-course
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: machine-learning, python, course, deep-learning, pytorch, natural-language-processing, reinforcement-learning, computer-vision, materials, seminars
Last push: 2026-05-04T20:44:21+00:00

## Health v2 (maintenance only)
Score: 59/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 80, release rhythm 8, longevity 100
- inputs: {"age_days": 2770, "days_push": 121, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3539, forks 1311 (observed 2026-08-28T04:08:09.168184+00:00)

## What it is
An open machine learning course (girafe-ai) with lecture videos, slides, seminars, and homework assignments in Jupyter Notebooks. It covers classical ML, deep learning with PyTorch, NLP, computer vision, and reinforcement learning.

## Use cases
- learn machine learning from scratch
- find machine learning course with homework assignments
- study deep learning with pytorch notebooks
- self-study curriculum for ML and NLP
- practice ML assignments with deadlines and solutions
- learn computer vision and reinforcement learning basics

## When to choose
- you want a structured, semester-long ML curriculum with lectures and graded-style homework
- you prefer hands-on Jupyter Notebook assignments alongside theory
- you want free MIT-licensed course materials covering classical ML through deep learning

## When to avoid
- you need production ML tooling or a library to import into your code
- you want a short crash course rather than a full semester of study
- you cannot work with Russian-language lecture recordings and slides

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, nlp, computer-vision, reinforcement-learning
- domain: machine-learning, deep-learning, education, tutorials
- platform: python
- tags: jupyter-notebooks, course-materials, lectures, homework-assignments, pytorch, open-courseware

## Member repositories
- girafe-ai/ml-course (main) score 59

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:09.168184+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 2026-08-29T18:34:36.654562+00:00, confidence not recorded.
  - readme: https://github.com/girafe-ai/ml-course (fetched 2026-08-28T04:08:09.168184+00:00, sha e6d5d0e6b1e2)
- Data as of 2026-08-30T08:39:29.467469+00:00.