Level: 300

Machine learning operations (MLOps) tools help you automate and standardize the ML lifecycle to productionize ML models faster without compromising model performance. Amazon SageMaker provides a breadth of mission-ready MLOps tools to experiment, train, test, deploy, and govern ML models at scale. In this session, learn how to use SageMaker to implement an end-to-end MLOps solution for your organization.

Learning Objectives

  • Learn about MLOps best practices
  • Explore Amazon SageMaker MLOps tools
  • Deep dive into an interactive demo

Who Should Attend?

ML Engineers, Data Scientists, Data Engineers, ML practitioners

Speaker(s)

Pranav Murthy, Senior ML Services SA, AWS; Paul Hargis, Sr AI/ML Specialist SA, AWS


Learn More

To learn more about the services featured in this talk, please visit:
https://aws.amazon.com/sagemaker/mlops

Intro body copy here about 2018 re:Invent launches.

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