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Machine Learning Engineering on AWS
book

Machine Learning Engineering on AWS

by Joshua Arvin Lat
October 2022
Intermediate to advanced content levelIntermediate to advanced
530 pages
11h 57m
English
Packt Publishing
Content preview from Machine Learning Engineering on AWS

11

Machine Learning Pipelines with SageMaker Pipelines

In Chapter 10, Machine Learning Pipelines with Kubeflow on Amazon EKS, we used Kubeflow, Kubernetes, and Amazon EKS to build and run an end-to-end machine learning (ML) pipeline. Here, we were able to automate several steps in the ML process inside a running Kubernetes cluster. If you are wondering whether we can also build ML pipelines using the different features and capabilities of SageMaker, then the quick answer to that would be YES!

In this chapter, we will use SageMaker Pipelines to build and run automated ML workflows. In addition to this, we will demonstrate how we can utilize AWS Lambda functions to deploy trained models to new (or existing) ML inference endpoints during pipeline ...

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Publisher Resources

ISBN: 9781803247595Supplemental Content