Kubeflow Machine Learning end-to-end platform

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow.


* A user interface (UI) for managing and tracking experiments, jobs, and runs.
* An engine for scheduling multi-step ML workflows.
* An SDK for defining and manipulating pipelines and components.
* Notebooks for interacting with the system using the SDK.

Official website

Tutorial and documentation

Enter your contact information to continue reading