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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #110
You are an ML engineer at a travel company. You have been researching customers' travel behavior for many years, and you have deployed models that predict customers' vacation patterns. You have observ
The correct answer is D. Store the performance statistics of each version of your models using seasons and years as. Store the performance statistics of each version of your models using seasons and years as events in Vertex ML Metadata. Compare the results across the slices. https://cloud.google.com/vertex-ai/docs/ml-metadata/analyzing#filtering
Submitted by javi_es· Apr 18, 2026Monitoring, optimizing, and maintaining ML solutions
Question
You are an ML engineer at a travel company. You have been researching customers' travel behavior for many years, and you have deployed models that predict customers' vacation patterns. You have observed that customers' vacation destinations vary based on seasonality and holidays; however, these seasonal variations are similar across years. You want to quickly and easily store and compare the model versions and performance statistics across years. What should you do?
Options
- AStore the performance statistics in Cloud SQL. Query that database to compare the performance
- BCreate versions of your models for each season per year in Vertex AI. Compare the performance
- CStore the performance statistics of each pipeline run in Kubeflow under an experiment for each
- DStore the performance statistics of each version of your models using seasons and years as
How the community answered
(35 responses)- A11% (4)
- B3% (1)
- C6% (2)
- D80% (28)
Explanation
Store the performance statistics of each version of your models using seasons and years as events in Vertex ML Metadata. Compare the results across the slices. https://cloud.google.com/vertex-ai/docs/ml-metadata/analyzing#filtering
Topics
#Model Versioning#Performance Monitoring#MLOps#Model Registry
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