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# Model Deployment with Azure ML service
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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).
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For more information please check out this article: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-deploy-and-where
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## Get Started
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To begin, you will need an ML workspace.
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For more information please check out this article: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-manage-workspace
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## Deploy locally
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You can deploy a model locally for testing & debugging using the Azure ML CLI or the Azure ML SDK.
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- CLI example: https://aka.ms/azmlcli
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- Notebook example: [register-model-deploy-local](./register-model-deploy-local.ipynb).
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