Version v0.2 of the documentation is no longer actively maintained. The site that you are currently viewing is an archived snapshot. For up-to-date documentation, see the latest version.

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.

The Kubeflow community is guided by our Code of Conduct, which we encourage everybody to read before participating.

Who should consider contributing to Kubeflow?

  • Folks who want to add support for other ML frameworks (e.g. PyTorch, XGBoost, scikit-learn, etc…)
  • Folks who want to bring more Kubernetes magic to ML (e.g. ISTIO integration for prediction)
  • Folks who want to make Kubeflow a richer ML platform (e.g. support for ML pipelines, hyperparameter tuning)
  • Folks who want to tune Kubeflow for their particular Kubernetes distribution or Cloud
  • Folks who want to write tutorials/blog posts showing how to use Kubeflow to solve ML problems

For more details on contributing please look at Contributing to Kubeflow.