You manage an Azure Machine Learning workspace. You build an Azure Machine Learning pipeline for image classification by using custom components. You need to define the interface, metadata, and code t

The correct answer is B. command_component(). Create and run machine learning pipelines using components with the Azure Machine Learning Define component using Python function By using command_component() function as a decorator, you can easily define the component's interface, metadata and code to execute from a Python func

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Question

You manage an Azure Machine Learning workspace. You build an Azure Machine Learning pipeline for image classification by using custom components. You need to define the interface, metadata, and code to execute components from a Python function. Which function should you use?

Options

Aload_component()
Bcommand_component()
Ccreate_or_update()
Dfrom_config()

How the community answered

(25 responses)

A
4% (1)
B
92% (23)
C
4% (1)

Explanation

Create and run machine learning pipelines using components with the Azure Machine Learning Define component using Python function By using command_component() function as a decorator, you can easily define the component's interface, metadata and code to execute from a Python function. Each decorated Python function will be transformed into a single static specification (YAML) that the pipeline service can process. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-component-pipeline-

Topics

#Azure Machine Learning#ML Pipelines#Custom Components#Python SDK

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