You create an Azure Machine Learning workspace named workspaces. You create a Python SDK v2 notebook to perform custom model training in workspaces. You need to run the notebook from Azure Machine Lea

The correct answer is D. Azure Machine Learning compute instance. An Azure Machine Learning compute instance must be provisioned first because it is the managed, cloud-based Jupyter notebook server used to run notebooks interactively in Azure Machine Learning Studio. A compute instance provides the Python environment, kernel, and execution cont

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Question

You create an Azure Machine Learning workspace named workspaces. You create a Python SDK v2 notebook to perform custom model training in workspaces. You need to run the notebook from Azure Machine Learning Studio in workspaces. What should you provision first?

Options

Adefault storage account
Breal-time endpoint
CAzure Machine Learning compute cluster
DAzure Machine Learning compute instance

How the community answered

(41 responses)

A
2% (1)
B
5% (2)
C
2% (1)
D
90% (37)

Explanation

An Azure Machine Learning compute instance must be provisioned first because it is the managed, cloud-based Jupyter notebook server used to run notebooks interactively in Azure Machine Learning Studio. A compute instance provides the Python environment, kernel, and execution context required to run SDK v2 notebooks. A compute cluster (option C) is designed for scalable batch training jobs, not interactive notebook sessions. A real-time endpoint (option B) is for model serving after training. The default storage account (option A) already exists when the workspace is created and is not something you provision separately for running notebooks.

Topics

#Azure Machine Learning Compute#Compute Instance#Notebook execution#AML Studio

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