Machine Learning
Automating ML Workflows with SageMaker Pipelines
Supercharge your ML projects by building automated pipelines with SageMaker Pipelines. Connect data processing, training, evaluation, and deployment into robust, repeatable workflows. You’ll learn to monitor pipeline runs, add evaluation steps, and automate model registration and deployment—making your machine learning solutions faster, smarter, and easier to maintain.
Amazon SageMaker
AWS
Python
5 lessons
24 practices
3 hours
Model Deployment Processes
Course details
Building Your First SageMaker Pipeline
Preparing Data for Pipeline Automation
Setting Up the Data Processor
Building Your First Processing Step
Completing SageMaker Processing Script Paths
Creating and Executing Your First Pipeline
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