AWS re:Invent 2022 - Deploy ML models for inference at high performance & low cost, ft AT&T (AIM302)

High-performance, cost-effective model deployment is critical to maximize the return on your ML investments. Amazon SageMaker provides the breadth and depth of fully managed deployment features to achieve optimal inference performance and cost, while reducing operational burden. In this session, learn how to use SageMaker inference capabilities to quickly deploy ML models in production at scale. Discover SageMaker deployment options including: infrastructure choices; real-time, serverless, asynchronous, and batch inference; single-model, multi-model, and multi-container endpoints; auto scaling; SageMaker Inference Recommender; model monitoring; and SageMaker MLOps integration. Learn how AT&T used Amazon SageMaker to optimize ML model deployment at scale.


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