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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 to the cloud
You can deploy to the cloud using the Azure ML CLI or the Azure ML SDK.
- CLI example: https://aka.ms/azmlcli
- Notebook example: model-register-and-deploy.