From the course: Machine Learning with SageMaker by Pearson
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Learning objectives - Amazon SageMaker Tutorial
From the course: Machine Learning with SageMaker by Pearson
Learning objectives
Welcome to Lesson 6, where we will explore how to deploy machine learning models using AWS SageMaker. This lesson begins with real-time inference, learning how to set up SageMaker endpoints for immediate predictions. We'll then dive into batch and asynchronous inference, ideal for handling large data sets and unpredictable workloads. Finally, we will introduce SageMaker Neo for edge deployment, optimizing models for low-latency offline use on devices like IoT sensors and cameras.
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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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