From the course: Machine Learning with SageMaker by Pearson

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Managing model versions with SageMaker Model Registry

Managing model versions with SageMaker Model Registry - Amazon SageMaker Tutorial

From the course: Machine Learning with SageMaker by Pearson

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Managing model versions with SageMaker Model Registry

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Once you start using machine learning models in some sort of production environment, you're going to reach a point where you create a new version of a model and you need to track that version over time, as well as maybe have approvals for deploying that version into production. And maybe you have SageMaker pipelines that are actually monitoring for new source data to train a new model. SageMaker is a great way to do that. It's a great way to do that. for new source data to train a new model. SageMaker Model Registry makes it easy to store and track those versions of your machine learning models to ensure that you can, one, comply with regulatory compliance requirements for your model, be able to reproduce them, store them, easily access them, approve them, et cetera, et cetera. So let's take a look at SageMaker Model Registry. Tracks model versions, metadata, and lineage versions are like 1, 2, 3, 4, metadatas, key value pairs, and lineage can include information like what…

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