Machine Learning Pipelines for Kubeflow
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Updated
May 20, 2024 - Python
Machine Learning Pipelines for Kubeflow
Standardized Serverless ML Inference Platform on Kubernetes
Elyra extends JupyterLab with an AI centric approach.
Kubeflow’s superfood for Data Scientists
Repository to hold code, instructions, demos and pointers to presentation assets for Kubeflow Dojo
This repository aims to develop a step-by-step tutorial on how to build a Kubeflow Pipeline from scratch in your local machine.
A notebook showing how to easily convert a current notebook you have to a notebook that can be run on Kubeflow Pipelines.
This repository is no longer maintained.
Kedro Plugin to support running workflows on Kubeflow Pipelines
Common pipeline-editor components used in different clients (e.g. Elyra application, Web browser extensions, etc)
☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.
Kubeflow for Poets: A Guide to Containerization of the Machine Learning Production Pipeline
A curated list of awesome projects and resources related to Kubeflow (a CNCF incubating project)
JupyterLab extension to provide a Kubeflow specific left area for Notebooks deployment
Orchestrate Spark Jobs from Kubeflow Pipelines and poll for the status.
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.
kubeflow example
Documentation for Kubeflow on Google Cloud
Argoflow-GCP has been superseded by deployKF
Kustomize manifest to deploy kubeflow pipelines in AWS
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