PMLE Monitoring ML Solutions Practice Question
A company wants to monitor fairness of a model by evaluating performance metrics across demographic subgroups. They have ground truth labels stored in BigQuery. Which Vertex AI service should they use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Vertex AI Model Evaluation
Vertex AI Model Evaluation supports sliced evaluation, allowing you to compute metrics per subgroup (e.g., by demographic) using data in BigQuery.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Vertex AI Model Monitoring
Why it's wrong here
Model Monitoring handles skew/drift, not fairness evaluation.
- ✗
Vertex AI Prediction
Why it's wrong here
Prediction serves the model, does not evaluate fairness.
- ✗
Vertex AI Explainability
Why it's wrong here
Explainability provides feature attributions, not fairness metrics.
- ✓
Vertex AI Model Evaluation
Why this is correct
Model Evaluation's sliced evaluation is designed for fairness assessment.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PMLE exam.