PMLE Monitoring ML Solutions Practice Question
An organisation wants to monitor fairness of their loan approval model across demographic subgroups. They have predictions stored in BigQuery along with ground truth. Which GCP service can evaluate model performance for each subgroup and identify disparities?
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, where metrics are computed for each subgroup defined by feature values (e.g., gender, race) in BigQuery. This helps identify performance disparities.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud Data Loss Prevention (DLP)
Why it's wrong here
DLP is for data masking and sensitive data detection, not model evaluation.
- ✗
Vertex AI Explainable AI
Why it's wrong here
Explainable AI provides feature attributions, not subgroup performance metrics.
- ✓
Vertex AI Model Evaluation
Why this is correct
Correct: supports sliced evaluation for fairness analysis.
- ✗
Vertex AI Model Monitoring
Why it's wrong here
Model monitoring focuses on drift, not fairness evaluation on stored data.
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JA
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.