Explanation:
The correct answer is D because in Azure Machine Learning SDK v2, when registering a model from a job output (including MLflow artifacts), the proper URI scheme is 'azureml://jobs/'. This format specifically references artifacts from job outputs, which aligns with the scenario where the model artifact resides in a named output of a training job. Option A ('t//model/') is invalid syntax. Option B ('azureml://registries') is used for model registries, not job outputs. Option C ('mlflow-model/') is not the standard Azure ML SDK v2 URI format for job artifacts.
Ultimate access to all questions.
You have an Azure Machine Learning workspace named WS1.
You plan to use Azure Machine Learning SDK v2 to register a model from an MLflow artifact. The artifact is located in a named output of a training job.
You need to identify the correct path syntax to reference the model during registration.
Which syntax should you use?
A
t//model/
B
azureml://registries
C
mlflow-model/
D
azureml://jobs/
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