Deploying machine learning models for inference- AWS Virtual Workshop

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Maximizing inference performance while reducing cost is critical to delivering great customer experiences through ML. Amazon SageMaker provides a breadth and depth of fully managed deployment features to achieve optimal inference performance and cost at scale without the operational burden. In this episode, learn how to use SageMaker inference capabilities to quickly deploy ML models in production for any use case, including hyper-personalization, Generative AI, and Large Language Models (LLMs).

Learning Objectives:
* Objective 1: Learn about how to deploy ML models on Amazon SageMaker for inference.
* Objective 2: Discover the SageMaker inference endpoint options that fit your use case.
* Objective 3: Learn how to deploy Large Language Models (LLMs) for inference.

***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/sagemaker/deploy/
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#AWS
Category
AWS Developers
Tags
Amazon SageMaker, Machine Learning, SageMaker Inference
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