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- Explore how to select appropriate models from the model catalog using benchmarks, deploy them to endpoints, and evaluate their performance using manual and automated approaches in Microsoft Foundry portal.
By the end of this module, you'll be able to:
- Explore and filter models in the model catalog
- Compare models using benchmark metrics for quality, safety, cost, and performance
- Deploy a model to an endpoint and test it in the playground
- Evaluate model performance using manual and automated approaches
- Understand different evaluation metrics and when to use them
- Get an introduction to what you need to know about monitoring Azure Machine Learning deployments.
After you complete this module, you'll be able to:
- Set up monitoring for Azure Machine Learning resources and workflows.
- Manage metrics and logs for Azure Machine Learning resources.
- Describe how monitoring for Azure Machine Learning models works.
