Microsoft Azure AI Fundamentals AI-900 Practice Question
A data science team needs to manage and keep track of multiple versions of their trained models within Azure Machine Learning to facilitate deployment and collaboration.
Which feature of Azure Machine Learning should they use?
The Model registry in Azure Machine Learning provides a centralized repository to store and manage multiple versions of machine learning models. It allows teams to track model versions, annotate them with metadata, and retrieve specific versions for deployment, ensuring consistent and reproducible results.
Experiment tracking is used to record and analyze training runs but does not handle model versioning.
Data labeling service assists with annotating data for training models, not managing models themselves.
Pipeline orchestration automates machine learning workflows but does not offer model version management.
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Microsoft Azure AI Fundamentals AI-900
Describe Fundamental Principles of Machine Learning on Azure
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