# google-deepmind/educational

Repository: https://github.com/google-deepmind/educational
Canonical: https://ross.abutalabs.com/products/educational
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Last push: 2022-09-16T17:11:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2115, "days_push": 1447, "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 1487, forks 202 (observed 2026-08-28T04:04:52.001576+00:00)

## What it is
A collection of educational Jupyter/Colab tutorials from DeepMind teaching machine learning basics to audiences with no ML background. Topics include reinforcement learning agents, language models, generative models, and protein folding.

## Use cases
- learn machine learning basics with no prior background
- teach an intro ML course with ready-made notebooks
- understand how language models predict text
- build a simple generative model that creates images
- learn how AI agents learn to play games
- explore ML approaches to protein structure prediction

## When to choose
- you want beginner-friendly, interactive Colab notebooks for ML education
- you need accessible teaching material for non-experts
- you want DeepMind-authored tutorials on language models, generative models, or RL

## When to avoid
- you need production ML libraries or frameworks
- you want advanced, research-grade implementations
- you need actively updated content, as the repo appears to be in maintenance

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, nlp, deep-learning
- domain: education, machine-learning, tutorials, artificial-intelligence
- platform: python
- tags: jupyter-notebooks, colab, educational-tutorials, reinforcement-learning, generative-models, beginner-friendly, web

## Member repositories
- google-deepmind/educational (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:52.001576+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 2026-08-30T04:33:47.899851+00:00, confidence not recorded.
  - readme: https://github.com/google-deepmind/educational (fetched 2026-08-28T04:04:52.001576+00:00, sha 0d29d3bc6127)
- Data as of 2026-08-30T08:39:29.467469+00:00.