Skip to content

Latest commit

 

History

History
22 lines (13 loc) · 1.38 KB

README.md

File metadata and controls

22 lines (13 loc) · 1.38 KB
Raw

Build Status Coverage Status

Overview of the Kubeflow pipelines service

Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable.

Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK.

The Kubeflow pipelines service has the following goals:

  • End to end orchestration: enabling and simplifying the orchestration of end to end machine learning pipelines
  • Easy experimentation: making it easy for you to try numerous ideas and techniques, and manage your various trials/experiments.
  • Easy re-use: enabling you to re-use components and pipelines to quickly cobble together end to end solutions, without having to re-build each time.

Documentation

Get started with your first pipeline and read further information in the documentation.

Acknowledgments

Kubeflow pipelines uses Argo under the hood to orchestrate Kubernetes resources. The Argo community has been very supportive and we are very grateful.