About
ML toolkit for Kubernetes. Build, train, deploy, and manage ML workflows on Kubernetes at scale.
Features
- Kubeflow Pipelines for defining and managing ML workflows
- Jupyter notebook server for interactive development
- Katib for automated hyperparameter tuning
- Multi-user isolation with namespaces and RBAC
- Model serving with KFServing (now KServe) for scalable inference
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