Share via

Manage a Machine Learning Studio (classic) workspace

APPLIES TO: Applies to.Machine Learning Studio (classic) Does not apply to.Azure Machine Learning


Support for Machine Learning Studio (classic) will end on 31 August 2024. We recommend you transition to Azure Machine Learning by that date.

Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources.

ML Studio (classic) documentation is being retired and may not be updated in the future.


For information on managing Web services in the Machine Learning Web Services portal, see Manage a Web service using the Machine Learning Web Services portal.

You can manage Machine Learning Studio (classic) workspaces in the Azure portal.

Use the Azure portal

To manage a Studio (classic) workspace in the Azure portal:

  1. Sign in to the Azure portal using an Azure subscription administrator account.
  2. In the search box at the top of the page, enter "machine learning Studio (classic) workspaces" and then select Machine Learning Studio (classic) workspaces.
  3. Click the workspace you want to manage.

In addition to the standard resource management information and options available, you can:

  • View Properties - This page displays the workspace and resource information, and you can change the subscription and resource group that this workspace is connected with.
  • Resync Storage Keys - The workspace maintains keys to the storage account. If the storage account changes keys, then you can click Resync keys to synchronize the keys with the workspace.

To manage the web services associated with this Studio (classic) workspace, use the Machine Learning Web Services portal. See Manage a Web service using the Machine Learning Web Services portal for complete information.


To deploy or manage New web services you must be assigned a contributor or administrator role on the subscription to which the web service is deployed. If you invite another user to a machine learning Studio (classic) workspace, you must assign them to a contributor or administrator role on the subscription before they can deploy or manage web services.

For more information on setting access permissions, see Assign Azure roles using the Azure portal.

Next steps