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How to Contribute

We'd love to accept your patches and contributions to this project. There are just a few small guidelines you need to follow.

Contributor License Agreement

Contributions to this project must be accompanied by a Contributor License Agreement. You (or your employer) retain the copyright to your contribution; this simply gives us permission to use and redistribute your contributions as part of the project. Head over to https://cla.developers.google.com/ to see your current agreements on file or to sign a new one.

You generally only need to submit a CLA once, so if you've already submitted one (even if it was for a different project), you probably don't need to do it again.

Code reviews

All submissions, including submissions by project members, require review. We use GitHub pull requests for this purpose. Consult GitHub Help for more information on using pull requests.

Notebook contributions

To guarantee standardization for assets in Google repositories we have put together some recommendations which will help Google provide consistency and quality for the notebook assets:

Please make sure you follow the next steps when developing Notebooks:

  1. Clone and develop off of this notebook templates
  2. If notebook is meant as official documentation, work with techwriter on written content
  3. Ensure notebook requirements are met
  4. Ensure notebook runs from top to bottom without errors
  5. Place the notebook in correct location
  6. Run nbfmt.
  7. Create a pull request in a relevant repository
  8. Reviewers provide feedback and work with you to merge pull request

If Colab is required please provide compatibility with AI Platform Notebooks, to help you on this we have created a template for you! Template here

Notebook requirements

  1. Use AI Platform notebooks We highly recommend to guarantee that your Notebook runs in AI Platform Notebooks

  2. Use templates listed above.

  3. Provide novel and relevant content

  4. Provide Notebook documentation

  5. Use latest ML framework version

  6. Follow software engineering principles:

Notebook formatting

# Install the tensorflow-docs package:
$ python3 -m pip install -U git+https://github.com/tensorflow/docs

# Format individual notebooks:
$ python3 -m tensorflow_docs.tools.nbfmt ./path/to/notebook.ipynb [...]

# Or a directory of notebooks:
$ python3 -m tensorflow_docs.tools.nbfmt ./path/to/notebooks/

Notebooks location

Add your notebook to the following folder: ai-platform-samples > notebooks > samples:

  • AutoML Tables
  • BigQuery
  • BigQuery ML

For the following products, select the ML framework and place it accordingly:

  • AI Platform Training
  • AI Platform Prediction
  • AI Platform Explanations
  • AI Platform Notebooks

Directory structure:

     .
     ├── datasets
     └── notebooks
         └── samples
             ├── automl
             ├── bigquery
             ├── bqml
             ├── mxnet
             ├── pytorch
             ├── scikit-learn
             └── tensorflow
                 └── census
                       └── tensorflow_census_getting_started.ipynb

Community Guidelines

This project follows Google's Open Source Community Guidelines.