nerdexam
Microsoft

DP-100 · Question #501

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…

The correct answer is B. No. Creating a compute instance is not the prerequisite for adding a Jupyter kernel because a compute instance is already running as evidenced by the active terminal session.

Design and prepare a machine learning solution

Question

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio. You plan to add a new Jupyter kernel that will be accessible from the same terminal session. You need to perform the task that must be completed before you can add the new kernel. Solution: Create a compute instance. Does the solution meet the goal?

Options

  • AYes
  • BNo

How the community answered

(25 responses)
  • A
    8% (2)
  • B
    92% (23)

Why each option

Creating a compute instance is not the prerequisite for adding a Jupyter kernel because a compute instance is already running as evidenced by the active terminal session.

AYes

Answering Yes is incorrect because the active terminal session confirms a compute instance already exists, so creating another one does not address the real prerequisite of configuring a new Python environment for the kernel.

BNoCorrect

The question states the user is already connected to a terminal session from the Notebooks page, which means a compute instance is already provisioned and active. The actual prerequisite for adding a new Jupyter kernel is creating a new conda or Python environment within that existing compute instance, not creating another compute instance.

Concept tested: Azure ML compute instance Jupyter kernel prerequisites vs compute provisioning

Source: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-terminal

Topics

#Azure Machine Learning#Compute Instance#Jupyter Kernel#Terminal Session

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