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
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Welcome to Lesson 7, where we will explore how to automate machine learning workflows with SageMaker Pipelines. This lesson begins with building and managing ML pipelines focusing on creating repeatable and scalable workflows. Next, we'll dive into integrating data processing and training steps to streamline the ML lifecycle. Finally, we'll look at triggering pipelines with an AWS EventBridge, enabling real-time updates and automated retraining.
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Learning objectives31s
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Building and automating ML pipelines in SageMaker6m 40s
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SageMaker pipeline demonstration34m 3s
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Integrating data processing and training steps6m 56s
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Training and data processing in SageMaker pipelines demonstration10m 17s
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Triggering pipelines with EventBridge for retraining7m 15s
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Triggering SageMaker pipelines via EventBridge demonstration9m 51s
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