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Build well-architected IDP solutions with a custom lens – Part 5: Cost optimization

AWS Machine Learning Blog

If you’re not actively using the endpoint for an extended period, you should set up an auto scaling policy to reduce your costs. SageMaker provides different options for model inferences , and you can delete endpoints that aren’t being used or set up an auto scaling policy to reduce your costs on model endpoints.

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How to Build ML Model Training Pipeline

The MLOps Blog

A typical pipeline may include: Data Ingestion: The process begins with ingesting raw data from different sources, such as databases, files, or APIs. The preprocessing stage involves cleaning, transforming, and encoding the data, making it suitable for machine learning algorithms. Let’s get started!

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