Professional Machine Learning Engineer

By Google · Question Mode

QuestionQ27

Collaborating within and across teams to manage data and models

You are training models in Vertex AI with data that spans multiple Google Cloud projects. You need to locate, track, and compare the performance of different versions of your models. Which Google Cloud services should be part of your ML workflow?

Explanation

Vertex AI Pipelines orchestrates ML workflows and enables comparison of pipeline runs. Vertex AI Experiments records experiment runs and supports comparison of their parameters and metrics. Vertex AI Metadata stores ML artifacts and metadata lineage, allowing training data, models, parameters, and metrics to be traced across the workflow.

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