Manage an Azure Machine Learning Studio workspace
For information on managing Web services in the Machine Learning Web Services portal, see Manage a Web service using the Azure Machine Learning Web Services portal.
You can manage Machine Learning Studio workspaces in the Azure portal.
Use the Azure portal
To manage a Studio workspace in the Azure portal:
- Sign in to the Azure portal using an Azure subscription administrator account.
- In the search box at the top of the page, enter "machine learning Studio workspaces" and then select Machine Learning Studio workspaces.
- 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 workspace, use the Machine Learning Web Services portal. See Manage a Web service using the Azure 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 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 Manage access using RBAC and the Azure portal.
- Learn more about deploy Machine Learning with Azure Resource Manager Templates.
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