Contribute a correction or improvement to TensorFlow's official documentation by editing a Markdown or notebook file here.
Download and run the official TensorFlow tutorial notebooks locally instead of relying on the web-hosted version.
Use a tensorflow.org guide's source notebook as a starting template for your own machine learning project.
Check the source of a tensorflow.org tutorial when the rendered page is unclear, the notebooks here show the full runnable code.
| tensorflow/docs | crewaiinc/crewai-examples | ed-donner/llm_engineering | |
|---|---|---|---|
| Stars | 6,317 | 5,944 | 5,943 |
| Language | Jupyter Notebook | Jupyter Notebook | Jupyter Notebook |
| Setup difficulty | easy | moderate | easy |
| Complexity | 1/5 | 3/5 | 2/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
This repository holds the source files for the official TensorFlow guides and tutorials that appear on tensorflow.org. TensorFlow is a widely used open-source library for building and running machine learning models, and this repository is where the written documentation for it lives. The files here are not the TensorFlow software itself. They are the text, code examples, and Jupyter notebooks that explain how to use TensorFlow. When the website is updated with new or revised documentation, the changes come from this repository. Anyone who wants to improve the documentation can contribute by following the contributor guide and style guide linked in the README. Bugs or errors in the documentation should be reported as issues in the main TensorFlow code repository rather than here. Community-contributed translations of the documentation into other languages are maintained in a separate companion repository called tensorflow/docs-l10n. The project is released under the Apache 2.0 license.
The source files behind tensorflow.org's official guides and tutorials, if you want to contribute a correction, run a tutorial notebook locally, or trace exactly what a guide's code does, this is where they live.
Mainly Jupyter Notebook. The stack also includes Jupyter Notebook, Python, Markdown.
Apache 2.0, use freely for any purpose including commercial, just keep the copyright notice and license file.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.