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-# Model Deployment with Azure ML service
-You can use Azure Machine Learning to package, debug, validate and deploy inference containers to a variety of compute targets. This process is known as "MLOps" (ML operationalization).
-For more information please check out this article: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-deploy-and-where
-
-## Get Started
-To begin, you will need an ML workspace.
-For more information please check out this article: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-manage-workspace
-
-## Deploy locally
-You can deploy a model locally for testing & debugging using the Azure ML CLI or the Azure ML SDK.
-- CLI example: https://aka.ms/azmlcli
-- Notebook example: [register-model-deploy-local](./register-model-deploy-local.ipynb).
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