From the course: Machine Learning with SageMaker by Pearson
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Module introduction - Amazon SageMaker Tutorial
From the course: Machine Learning with SageMaker by Pearson
Module introduction
Welcome to Module 3, Deployment and Orchestration of ML Workflows. In this module, we'll shift our focus from building models to deploying them efficiently and orchestrating machine learning workflows. You'll learn how to use AWS SageMaker and other tools to deploy models for real-time and batch inference, automate complex pipelines, and integrate data processing, training and monitoring steps. This module is all about bringing your ML solutions to life in a scalable, reliable, and cost-effective way.
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Module introduction35s
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Learning objectives34s
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Real-time inference with SageMaker endpoints9m 58s
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Real-time inference demonstration8m 51s
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Batch inference and asynchronous inference6m 29s
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Batch and asynchronous inference demonstration14m 50s
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Using SageMaker Neo for edge deployment7m 32s
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SageMaker edge deployment demonstration12m 13s
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