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Answer: Run Python code that uses the Azure ML SDK library and calls the Workspace.create method with name, subscription_id, and resource_group parameters., Navigate to Azure Machine Learning studio and create a workspace., Use the Azure Command Line Interface (CLI) with the Azure Machine Learning extension to call the az group create function with --name and --location parameters, and then the az ml workspace create function, specifying ג€"w and ג€"g parameters for the workspace name and resource group.
The question asks for three valid methods to create an Azure Machine Learning workspace in a new subscription with no existing resources. Based on the community discussion and official Microsoft documentation, the correct methods are: A (Python SDK with Workspace.create), B (Azure Machine Learning studio), and C (Azure CLI). Option A is valid because Workspace.create can create a new workspace, and the resource group can be created automatically if specified with create_resource_group=True. Option B is correct as Azure Machine Learning studio provides a UI to create workspaces. Option C is valid as Azure CLI commands can create both the resource group and workspace. Option D is a duplicate of B and should not be counted separately. Option E is incorrect because Workspace.get retrieves an existing workspace but cannot create a new one.
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You have a new Azure subscription with no resources. You need to create an Azure Machine Learning workspace. Which three methods can you use to accomplish this? Each answer represents a full solution.
A
Run Python code that uses the Azure ML SDK library and calls the Workspace.create method with name, subscription_id, and resource_group parameters.
B
Navigate to Azure Machine Learning studio and create a workspace.
C
Use the Azure Command Line Interface (CLI) with the Azure Machine Learning extension to call the az group create function with --name and --location parameters, and then the az ml workspace create function, specifying ג€"w and ג€"g parameters for the workspace name and resource group.
D
Navigate to Azure Machine Learning studio and create a workspace.
E
Run Python code that uses the Azure ML SDK library and calls the Workspace.get method with name, subscription_id, and resource_group parameters.
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