Kubeflow brings composable, easier to use stacks with more control and portability for Kubernetes deployments for all ML, not just TensorFlow.
Introducing Kubeflow, the new project to make machine learning on Kubernetes easy, portable, and scalable. Kubeflow should be able to run in any environment where Kubernetes runs. Instead of recreating other services, Kubeflow distinguishes itself by spinning up the best solutions for Kubernetes users.
Why switch to Kubeflow?
Kubeflow is intended to make ML easier for Kubernetes users. How? By letting the system take care of the details (within reason) and support the kind of tooling ML practitioners want and need.
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