Kubeflow Pipelines

Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning (ML) workflows based on Docker containers.

Quick Start Guide

You only have to decide if you want CPU support:

curl -sfL https://get.k3ai.in | bash -s -- --cpu --plugin_kfpipelines

or if you prefer GPU support:

curl -sfL https://get.k3ai.in | bash -s -- --gpu --plugin_kfpipelines

What is Kubeflow Pipelines?

The Kubeflow Pipelines platform consists of:

• 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 an SDK.

The following are the goals of Kubeflow Pipelines:

• End-to-end orchestration: enabling and simplifying the orchestration of 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 create end-to-end solutions without having to rebuild each time.

Learn more on the Kubeflow website: https://www.kubeflow.org/docs/pipelines/****