You are using Vertex AI to manage your ML models and datasets. You recently updated one of your models. You want to track and compare the new version with the previous one and incorporate dataset vers

Question

Options

• AUse Vertex AI TensorBoard to visualize the training metrics of the new model version, and use
• BUse Vertex AI Model Monitoring to monitor the performance of the new model version, and use
• CUse Vertex AI Experiments to track and compare model artifacts and versions, and use Vertex ML
• DUse Vertex AI Experiments to track and compare model artifacts and versions, and use Vertex AI

• A
  8% (3)
• B
  16% (6)
• C
  73% (27)
• D
  3% (1)

Explanation

Two distinct needs: (1) track and compare model versions/artifacts, and (2) version datasets. Vertex AI Experiments is designed specifically to log, track, and compare runs, metrics, parameters, and model artifacts across versions-it provides a structured comparison UI. Vertex ML Metadata provides lineage tracking for ML artifacts including datasets, enabling dataset versioning by recording dataset versions as metadata artifacts linked to training runs. Option A (TensorBoard) visualizes training metrics but does not manage model versioning or dataset versioning. Option B (Model Monitoring) tracks production data drift, not version comparison. Option D is likely incomplete or refers to a less appropriate pairing. Option C correctly pairs the right tool for each requirement.

No community discussion yet for this question.