Now in beta, the open source Kubeflow project aims to help deploy a machine learning stack on the Kubernetes container orchestration system.

The Kubeflow machine learning toolkit project is intended to help deploy machine learning workloads across multiple nodes but where breaking up and distributing a workload can add computational overhead and complexity. Kubernetes itself is tasked with making it easier to manage distributed workloads, while Kubeflow centers on making the running of these workloads portable, scalable, and simple. Scripts and configuration files are part of the project. Users can customize their configuration and run scripts to deploy containers to a chosen environment.

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