Shared Resources and Components

Hubs where you can find reusable components, shared Jupyter notebooks, and other ML resources

This page links to websites where you can find machine learning (ML) resources shared by various communities and organizations.

Check the provider of any resource that you use

Pipelines, components, and other resources contain executable code. Before downloading and using a resource, make sure that you trust the provider of the resource.

AI Hub

AI Hub is a platform for discovering and deploying ML products.

AI Hub includes the following shared resources that you can use within your Kubeflow deployment:

• Pipelines and components that you can use with Kubeflow Pipelines.
• Jupyter notebooks that you can upload to the notebooks server in your Kubeflow cluster.

Reusable components for Kubeflow Pipelines

A Kubeflow Pipelines component is a self-contained set of code that performs one step in the pipeline, such as data preprocessing, data transformation, model training, and so on. Each component is packaged as a Docker image. You can add existing components to your pipeline. These may be components that you create yourself, or that someone else has created and made available.

The Kubeflow Pipelines repository on GitHub includes a number of reusable components that you can add to your pipeline.

Last modified 12.10.2020: Removed out of date notifications - KFP Overview, Examples section, Google Cloud Fairing docs (#2276) (97dc7469)