# 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](./model-register-and-deploy.ipynb).

![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/MachineLearningNotebooks/how-to-use-azureml/deployment/deploy-multi-model/README.png)