Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. A pipeline is a description of an ML workflow, including all of the components in the workflow and how they combine in the form of a graph. The pipeline includes the definition of the inputs (parameters) required to run the pipeline and the inputs and outputs of each component. A pipeline component is a self-contained set of user code, packaged as a Docker image, that performs one step in the pipeline. For example, a component can be responsible for data preprocessing, data transformation, model training, and so on.

Features

  • Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK
  • 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 available
  • Install Kubeflow Pipelines from choices described in Installation Options for Kubeflow Pipelines
  • Kubeflow Pipelines Slack Channel
  • Kubeflow Pipelines Community Meeting

Project Samples

Kubeflow pipelines Screenshot 1

Project Activity

See All Activity >

Categories

Machine Learning

License

Apache License V2.0

Follow Kubeflow pipelines

Kubeflow pipelines Web Site

Other Useful Business Software
Enterprise Job Scheduling Software Icon
Enterprise Job Scheduling Software

Unify Enterprise Job Scheduling for Scale, Visibility, and Control

Managing your sprawling data center and cloud with disparate native schedulers creates chaos. Achieve unparalleled control and efficiency over your entire IT environment with JAMS job orchestration tools. JAMS provides the singular, centralized platform required to overcome the complexities of disparate native schedulers. Automate, secure, and govern all your workloads, eliminating fragmented control, compliance risks, and operational bottlenecks. JAMS streamlines operations and ensures audit-ready history, transforming your enterprise automation with confidence and precision.
Learn More
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Kubeflow pipelines!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Machine Learning Software

Registered

2024-03-07
Report inappropriate content