Kubernetes has quickly become the hybrid solution for deploying complicated workloads anywhere. One of the fastest growing use cases is to use Kubernetes as the deployment platform of choice for machine learning. However, connecting and managing the services needed for production-ready machine learning (ML) systems introduces huge barriers of complexity in adopting ML.
That’s where Kubeflow comes in – a composable, portable, scalable ML stack built for Kubernetes. Join our session to find out how Kubeflow can make using ML stacks on Kubernetes easy, fast and extensible.
Publisher: Google Cloud
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