Create and manage Azure Machine Learning service workspaces
In this article, you'll create, view, and delete Azure Machine Learning service workspaces in the Azure portal for Azure Machine Learning service. You can also create and delete workspaces using the CLI, with Python code or via the VS Code extension.
Create a workspace
To create a workspace, you need an Azure subscription. If you don’t have an Azure subscription, create a free account before you begin. Try the free or paid version of Azure Machine Learning service today.
Sign in to the Azure portal by using the credentials for the Azure subscription you use.
In the upper-left corner of the portal, select Create a resource.
In the search bar, enter Machine Learning. Select the Machine Learning service workspace search result.
In the ML service workspace pane, scroll to the bottom and select Create to begin.
In the ML service workspace pane, configure your workspace.
Field Description Workspace name Enter a unique name that identifies your workspace. In this example, we use docs-ws. Names must be unique across the resource group. Use a name that's easy to recall and differentiate from workspaces created by others. Subscription Select the Azure subscription that you want to use. Resource group Use an existing resource group in your subscription, or enter a name to create a new resource group. A resource group is a container that holds related resources for an Azure solution. In this example, we use docs-aml. Location Select the location closest to your users and the data resources. This location is where the workspace is created.
To start the creation process, select Create. It can take a few moments to create the workspace.
To check on the status of the deployment, select the Notifications icon, bell, on the toolbar.
When the process is finished, a deployment success message appears. It's also present in the notifications section. To view the new workspace, select Go to resource.
View a workspace
In top left corner of the portal, select All services.
In the All services filter field, type machine learning service.
Select Machine Learning service workspaces.
Look through the list of workspaces found. You can filter based on subscription, resource groups, and locations.
Select a workspace to display its properties.
Delete a workspace
Use the Delete button at the top of the workspace you wish to delete.
Clean up resources
The resources you created can be used as prerequisites to other Azure Machine Learning service tutorials and how-to articles.
If you don't plan to use the resources you created, delete them, so you don't incur any charges:
In the Azure portal, select Resource groups on the far left.
From the list, select the resource group you created.
Select Delete resource group.
Enter the resource group name. Then select Delete.
Follow the full-length tutorial to learn how to use a workspace to build, train, and deploy models with Azure Machine Learning service.
Send feedback about: