Kubeflow, Your ML Tools on Kubernetes
summary
Kubeflow is presented as a way to run and deploy machine-learning tools on a Kubernetes cluster to simplify data scientists’ workflows. The talk explains using Kubeflow to take advantage of Kubernetes’ portability and diverse hardware to train and serve models easily and quickly.
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chapters (8)
- 0:00Introduction
- 3:34What is Kubeflow
- 7:08Distributed TensorFlow training
- 15:19Local setup and run
- 19:18Deploy with KFServing
- 23:57Serving models with TF Serving
- 27:52Demo: Dinosaur game
- 28:55Resources and community
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