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In this document, you learn how to configure a private endpoint for your Azure Machine Learning workspace. For information on creating a virtual network for Azure Machine Learning, see [Virtual network isolation and privacy overview](how-to-network-security-overview.md).
In this document, you learn how to configure a private endpoint for your Azure Machine Learning workspace. For information on creating a virtual network for Azure Machine Learning, see [Virtual network isolation and privacy overview](how-to-network-security-overview.md).
If you're using the Azure CLI [extension 1.0 for machine learning](reference-azure-machine-learning-cli.md), use the [az ml workspace create](/cli/azure/ml/workspace#az-ml-workspace-create) command. The following parameters for this command can be used to create a workspace with a private network, but it requires an existing virtual network:
For more information on the classes and methods used in this example, see [PrivateEndpointConfig](/python/api/azureml-core/azureml.core.privateendpointconfig) and [Workspace.add_private_endpoint](/python/api/azureml-core/azureml.core.workspace(class)#add-private-endpoint-private-endpoint-config--private-endpoint-auto-approval-true--location-none--show-output-true--tags-none-).
The Azure CLI [extension 1.0 for machine learning](reference-azure-machine-learning-cli.md) provides the [az ml workspace private-endpoint add](/cli/azure/ml(v1)/workspace/private-endpoint#az-ml-workspace-private-endpoint-add) command.
The Azure CLI [extension 1.0 for machine learning](reference-azure-machine-learning-cli.md) provides the [az ml workspace private-endpoint delete](/cli/azure/ml(v1)/workspace/private-endpoint#az-ml-workspace-private-endpoint-delete) command.
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