管理 Azure 机器学习工作室(经典)工作区Manage an Azure Machine Learning Studio (classic) workspace

适用于: yes机器学习工作室(经典) noAzure 机器学习APPLIES TO: yesMachine Learning Studio (classic) noAzure Machine Learning

备注

有关在机器学习 Web 服务门户中管理 Web 服务的信息,请参阅使用 Azure 机器学习 Web 服务门户管理 Web 服务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.

可以在 Azure 门户中管理机器学习工作室(经典)工作区。You can manage Machine Learning Studio (classic) workspaces in the Azure portal.

使用 Azure 门户Use the Azure portal

若要在 Azure 门户中管理工作室(经典)工作区,请执行以下操作:To manage a Studio (classic) workspace in the Azure portal:

  1. 使用 Azure 订阅管理员帐户登录到 Azure 门户Sign in to the Azure portal using an Azure subscription administrator account.
  2. 在页面顶部的搜索框中,输入“机器学习工作室(经典)工作区”,并选择“机器学习工作室(经典)工作区” 。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. 单击想要管理的工作区。Click the workspace you want to manage.

除了标准的资源管理信息和可用选项外,还可以:In addition to the standard resource management information and options available, you can:

  • 查看属性 - 此页显示工作区和资源信息,并可以更改此工作区连接到的订阅和资源组。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.
  • 重新同步存储密钥 - 此工作区维护存储帐户的密钥。Resync Storage Keys - The workspace maintains keys to the storage account. 如果存储帐户更改密钥,则可以单击“重新同步密钥” 将密钥与工作区同步。If the storage account changes keys, then you can click Resync keys to synchronize the keys with the workspace.

若要管理与此工作室(经典)工作区关联的 Web 服务,请使用“机器学习 Web 服务”门户。To manage the web services associated with this Studio (classic) workspace, use the Machine Learning Web Services portal. 有关完整信息,请参阅使用 Azure 机器学习 Web 服务门户管理 Web 服务See Manage a Web service using the Azure Machine Learning Web Services portal for complete information.

备注

若要部署或管理新 Web 服务,必须分配有该 Web 服务部署到的订阅上的参与者或管理员角色。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. 如果邀请其他用户加入机器学习工作室(经典)工作区,必须向其分配订阅上的参与者或管理员角色,然后这些用户才能部署或管理 Web 服务。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.

有关设置访问权限的更多信息,请参阅使用 RBAC 和 Azure 门户管理访问权限For more information on setting access permissions, see Manage access using RBAC and the Azure portal.

后续步骤Next steps