The machine learning toolkit for Kubernetes.

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow.

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Technologies

  • python
  • jupyter notebook
  • tensorflow
  • kustomize
  • kubernetes

Topics

  • Cloud
  • machine learning
  • infrastructure
  • cloud
  • kubernetes
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Kubeflow 2020 Projects

  • Kostas Andriopoulos
    Build a UI to Deploy Managed Tensorboard Instances with Support for PVCs
    Many Data Scientists have their data saved in a PersistentVolumeClaim accessed by their Notebooks. So it would be helpful and greatly improve...
  • Yash Jakhotiya
    Create a sample for notebook to Kubeflow deployment using TensorFlow 2.0 Keras
    Kubernetes is already an industry-standard in managing cloud resources. Kubeflow is on its path to become an industry standard in managing machine...
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2020