kubeflow-pipelines

Machine Learning Pipelines for Kubeflow

Elyra extends JupyterLab with an AI centric approach.

Kubeflow’s superfood for Data Scientists

A curated list of awesome projects and resources related to Kubeflow (a CNCF incubating project)

Repository to hold code, instructions, demos and pointers to presentation assets for Kubeflow Dojo

K3ai is a lightweight, fully automated, AI infrastructure-in-a-box solution that allows anyone to experiment quickly with Kubeflow pipelines. K3ai is perfect for anything from Edge to laptops.

Cloud Pipelines Editor is a web app that allows the users to build and run Machine Learning pipelines without having to set up development environment.

Orchestrate Spark Jobs from Kubeflow Pipelines and poll for the status.

Kedro Plugin to support running workflows on Kubeflow Pipelines

☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.

This repository aims to develop a step-by-step tutorial on how to build a Kubeflow Pipeline from scratch in your local machine.

Common pipeline-editor components used in different clients (e.g. Elyra application, Web browser extensions, etc)

This repository is no longer maintained.

Kustomize manifest to deploy kubeflow pipelines in AWS

This repository holds files and scripts for incorporating simple CI/CD practices for model training in ML.

kubeflow example

JupyterLab extension to provide a Kubeflow specific left area for Notebooks deployment

🦖 Streamlined Recommender Systems with TensorFlow and KubeFlow

A notebook showing how to easily convert a current notebook you have to a notebook that can be run on Kubeflow Pipelines.

Analyzing flight delay and weather data using Elyra, IBM Data Asset Exchange, Kubeflow Pipelines and KFServing