Explanation:
The solution does NOT meet the goal because the Workspace.get() method is used incorrectly. According to the Azure ML documentation and the community discussion consensus (with 80% selecting 'No' and the highest upvoted comments supporting this), the Workspace.get() method requires only the workspace name parameter when retrieving an existing workspace. The subscription_id and resource_group parameters are not needed for the get() method - they are required parameters for the Workspace constructor when creating a new workspace. The correct approach would be either: ws = Workspace.get(name='ml-project') or using the from_config() method. The provided code includes unnecessary parameters that will cause the method to fail or behave unexpectedly.
Ultimate access to all questions.
You have the following Azure subscriptions and Azure Machine Learning service workspaces:
8a12e3a1-fb6c-4ccd-bd84-27b8a12e3fbcml-projectml-resourcesYou need to obtain a reference to the ml-project workspace.
Solution: Run the following Python code:
from azureml.core import Workspace
ws = Workspace.get(name='ml-project',
subscription_id='8a12e3a1-fb6c-4ccd-bd84-27b8a12e3fbc',
resource_group='ml-resources')
from azureml.core import Workspace
ws = Workspace.get(name='ml-project',
subscription_id='8a12e3a1-fb6c-4ccd-bd84-27b8a12e3fbc',
resource_group='ml-resources')
Does the solution meet the goal?
A
Yes
B
No
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