Charmed Kubeflow Documentation
Charmed Kubeflow is an open-source, end-to-end, production-ready MLOps platform on top of cloud native technologies.
Charmed Kubeflow translates Machine Learning steps into complete workflows, enabling training, tuning, and shipping of Machine Learning (ML) models. It enables automation of workflows, increases quality of models, and simplifies deployment of ML workloads into production in a reliable way.
Charmed Kubeflow meets the need of building ML applications in a structured and consistent manner while contributing to higher productivity and better collaboration in Data Science teams.
For Data Scientists and Machine Learning Engineers Charmed Kubeflow provides an advanced toolkit to organise and scale their work.
In this documentation
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Tutorial Learn how to deploy, debug and explore Kubeflow in this exciting sequence of tutorials |
How-to guides Navigate essential Kubeflow procedures like EKS installation and COS integration |
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Explanation Deep-dive into the details of Kubeflow on topics like authorisation |
Reference Find technical information on things like authenticaiton with Dex and supported versions |
Project and community
Charmed Kubeflow is a member of the Ubuntu family. It’s an open-source project that welcomes community contributions, suggestions, fixes and constructive feedback.
- Read our Code of Conduct
- Try out some Charmed Kubeflow projects
- Join the Discourse forum
- Contribute and report bugs
- Contribute to the documentation
- Talk to us on Mattermost Chat
Thinking about using Charmed Kubeflow for your next project? Get in touch!
Last updated 19 hours ago.