# justmarkham/scikit-learn-videos

Jupyter notebooks from the scikit-learn video series

Repository: https://github.com/justmarkham/scikit-learn-videos
Canonical: https://ross.abutalabs.com/products/scikit-learn-videos
Homepage: https://courses.dataschool.io/introduction-to-machine-learning-with-scikit-learn
Language: Jupyter Notebook
License Family: other
Topics: scikit-learn, machine-learning, data-science, jupyter-notebook, tutorial, python
Last push: 2024-03-05T19:22:42+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": 4168, "days_push": 911, "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 3807, forks 2526 (observed 2026-08-28T04:08:20.421184+00:00)

## What it is
A collection of Jupyter notebooks accompanying a 10-part video tutorial series teaching machine learning with scikit-learn in Python. It is also available as a free online course with quizzes and a certificate.

## Use cases
- learn machine learning with scikit-learn
- find beginner scikit-learn tutorials
- learn how to train ML models in Python
- get started with Jupyter notebooks for data science
- understand classification and model training basics
- follow a structured intro ML course

## When to choose
- you are a beginner wanting a guided, video-based introduction to scikit-learn
- you prefer learning through runnable notebooks alongside video lessons
- you want a free structured course covering ML fundamentals

## When to avoid
- you need advanced or production-grade ML guidance
- you want actively maintained content for the latest scikit-learn versions
- you need a software tool or library rather than learning material

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science
- domain: machine-learning, data-science, tutorials, education
- platform: python
- tags: scikit-learn, jupyter-notebooks, video-series, tutorial, beginner-friendly

## Member repositories
- justmarkham/scikit-learn-videos (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:20.421184+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 2026-08-29T18:26:45.965192+00:00, confidence not recorded.
  - readme: https://github.com/justmarkham/scikit-learn-videos (fetched 2026-08-28T04:08:20.421184+00:00, sha 7be219bfa275)
  - homepage: https://courses.dataschool.io/introduction-to-machine-learning-with-scikit-learn (fetched 2026-08-29T09:21:39.822916+00:00, sha 3a4ad56cf7d3)
- Data as of 2026-08-30T08:39:29.467469+00:00.