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In this session, learn more about Amazon SageMaker Edge Manager, a new capability of Amazon SageMaker that helps developers operate machine learning (ML) models on a fleet of edge devices and solve challenges with constraints and maintenance of ML models on edge devices. Find out how you can use Amazon SageMaker Edge Manager to build an MLOps pipeline from the cloud to the edge and back by preparing multiple variants of a model, including deployment on different edge devices, monitoring models deployed across a fleet, capturing data samples from each model instance on each device, and sending data securely from the fleet to the cloud for labeling and retraining with SageMaker.

Amazon SageMaker Edge Manager makes it easy to optimize, secure, monitor, and maintain machine learning (ML) models across fleets of edge devices such as smart cameras, smart speakers, and robots.

Learn more about Amazon SageMaker Edge Manager at – https://amzn.to/2VTEoIY


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