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Microsoft

DP-100 · Question #251

You manage an Azure Machine Learning workspace named proj1. You plan to use assets defined in proj1 to create a pipeline in the Machine Learning studio designer. You need to set the Registry name…

The correct answer is A. proj1. In Azure ML studio designer, the Registry name filter must be set to the exact workspace name to display only the assets defined within that specific workspace.

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Question

You manage an Azure Machine Learning workspace named proj1. You plan to use assets defined in proj1 to create a pipeline in the Machine Learning studio designer. You need to set the Registry name filter to display only the list of assets defined in proj1. What should you set the Registry name filter to?

Options

  • Aproj1
  • Bazureml-meta
  • Cazureml
  • Dworkspace

How the community answered

(36 responses)
  • A
    92% (33)
  • C
    6% (2)
  • D
    3% (1)

Why each option

In Azure ML studio designer, the Registry name filter must be set to the exact workspace name to display only the assets defined within that specific workspace.

Aproj1Correct

Setting the Registry name filter to 'proj1' targets the Azure Machine Learning workspace named proj1 directly, so the designer asset panel displays only the components, datasets, and models registered or defined within that workspace rather than shared or built-in registries.

Bazureml-meta

'azureml-meta' is a Microsoft-managed registry for meta-components and curated pipeline assets provided by the platform, not a filter for user-defined assets in a specific workspace.

Cazureml

'azureml' is the identifier for the built-in Azure ML curated component registry maintained by Microsoft and contains platform-provided components, not assets defined by users in proj1.

Dworkspace

'workspace' is not a recognized Registry name filter value in Azure ML studio designer; the actual workspace name must be used to scope the asset list to a specific workspace.

Concept tested: Azure ML studio designer Registry name filter for workspace-scoped assets

Source: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-pipeline-ui

Topics

#Azure Machine Learning Studio#Workspaces#Asset Management#UI Filtering

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