From the course: AWS Certified Machine Learning Engineer Associate (MLA-C01) Cert Prep

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Hands-on learning: SageMaker Model Monitor

Hands-on learning: SageMaker Model Monitor

From the course: AWS Certified Machine Learning Engineer Associate (MLA-C01) Cert Prep

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Hands-on learning: SageMaker Model Monitor

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(light music) - [Lecturer] Hello, guys, and welcome again. In today's hands-on lab, we're going to talk about the SageMaker Model Monitor. We're going to first host a machine learning model in Amazon SageMaker, and we're going to capture the inference requests, the results, and the metadata. We're going to capture this information to compare the baseline constraints that we will make against the data that we're going to infer. So we are going to generate first a baseline constraints from our training dataset, and then we're going to monitor a live endpoint for violations against these constraints. So in this lab we're going to work on a Jupyter notebook and we're going to upload this Jupyter notebook on a SageMaker notebook instance. So let's go for SageMaker AI, search for SageMaker, and then click on Amazon SageMaker AI. Then on the left hand side, under the applications and IDs, we're going to click on notebooks, which are the SageMaker notebooks, and we're going to create a new…

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