Amazon SageMaker Components for Kubeflow Pipelines let you create and monitor training, tuning, endpoint deployment, and batch transform jobs in Amazon SageMaker. By running Kubeflow Pipeline jobs on Amazon SageMaker, you move data processing and training jobs from the Kubernetes cluster to Amazon SageMaker’s machine learning-optimized managed service. This workshop assumes prior knowledge of Kubernetes and Kubeflow.
In this workshop, you'll see how to use the SageMaker components for Kubeflow Pipelines to train, tune, and deploy a machine learning model, and get both batch and real-time inferences from the deployed model.
After completing the workshop, remember to complete the cleanup section to remove any unnecessary AWS resources.