# tensorflow/docs

TensorFlow documentation

Repository: https://github.com/tensorflow/docs
Canonical: https://ross.abutalabs.com/products/tensorflow-docs
Homepage: https://www.tensorflow.org
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: tensorflow, tensorflow-tutorials, tensorflow-examples, documentation, machine-learning, deep-learning, deep-neural-networks
Last push: 2026-07-09T13:46:32+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 8, longevity 100
- inputs: {"age_days": 3065, "days_push": 55, "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 6328, forks 5311 (observed 2026-08-28T04:09:41.796183+00:00)

## What it is
The source repository for TensorFlow's official guides, tutorials, and API documentation published on tensorflow.org. It contains Jupyter notebook tutorials and Markdown docs maintained by the TensorFlow team and community contributors.

## Use cases
- learn tensorflow with official tutorials
- find tensorflow example notebooks
- contribute to tensorflow documentation
- look up tensorflow api guides
- learn deep learning with keras
- run tensorflow tutorials in colab

## When to choose
- you want official, up-to-date TensorFlow tutorials and guides
- you want to contribute docs or translations to the TensorFlow project
- you need runnable Jupyter notebook examples for learning ML

## When to avoid
- you need the TensorFlow library itself (use tensorflow/tensorflow)
- you need community translations (use tensorflow/docs-l10n)
- you want runnable application code rather than documentation

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, machine-learning, deep-learning
- domain: machine-learning, deep-learning, tutorials, documentation
- platform: python, cross-platform
- tags: tensorflow, jupyter-notebooks, tutorials, docs-source, google, web

## Member repositories
- tensorflow/docs (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:41.796183+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 2026-08-29T17:46:10.068225+00:00, confidence not recorded.
  - readme: https://github.com/tensorflow/docs (fetched 2026-08-28T04:09:41.796183+00:00, sha 45ea9f0624b4)
  - homepage: https://www.tensorflow.org (fetched 2026-08-29T08:42:42.665096+00:00, sha 5242f53e811a)
  - site_page: https://www.tensorflow.org/install (fetched 2026-08-29T08:42:42.668747+00:00, sha 584a762da891)
  - site_page: https://www.tensorflow.org/tfx/api_docs (fetched 2026-08-29T08:42:42.672003+00:00, sha 6977825696fe)
  - site_page: https://www.tensorflow.org/about (fetched 2026-08-29T08:42:42.675346+00:00, sha 817250744d91)
  - site_page: https://www.tensorflow.org/about/case-studies (fetched 2026-08-29T08:42:42.677190+00:00, sha e6701029eec0)
  - site_page: https://www.tensorflow.org/about/bib (fetched 2026-08-29T08:42:42.681148+00:00, sha 5ca8943386b9)
  - site_page: https://www.tensorflow.org/community/contribute (fetched 2026-08-29T08:42:42.673563+00:00, sha 77d394fa76e7)
  - site_page: https://blog.tensorflow.org/2024/02/graph-neural-networks-in-tensorflow.html (fetched 2026-08-29T08:42:42.679005+00:00, sha fd6c6556fa89)
- Data as of 2026-08-30T08:39:29.467469+00:00.