Answer-first summary for fast verification
Answer: resource_group, subscription_id
To connect to an Azure Machine Learning workspace using the SDK, the config.json file must include the subscription_id and resource_group parameters along with workspace_name. The subscription_id identifies the Azure subscription containing the workspace, while the resource_group specifies the resource group where the workspace is deployed. These three parameters together uniquely identify the workspace within Azure. The other options are incorrect: 'login' is not a valid parameter, 'key' refers to authentication keys which are handled separately through Azure authentication methods, and 'region' is not required as the workspace location is determined by the resource group and subscription context.
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You create an Azure Machine Learning workspace and are preparing a local Python environment on a laptop to connect to the workspace and run experiments. You create the following config.json file.
{
"workspace_name": "ml-workspace"
}
{
"workspace_name": "ml-workspace"
}
You must use the Azure Machine Learning SDK to interact with data and experiments in the workspace.
You need to configure the config.json file to connect to the workspace from the Python environment.
Which two additional parameters must you add to the config.json file in order to connect to the workspace? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A
login
B
resource_group
C
subscription_id
D
key
E
region
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