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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December 19th, 2018 | 1:00 PM PT
Developing Deep Learning Models for Computer Vision with
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