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Monitoring ML SolutionsmediumMultiple SelectObjective-mapped

PMLE Monitoring ML Solutions Practice Question

An ML engineer wants to monitor a deployed model for fairness across different age groups and genders. Which TWO Vertex AI services should they use together to achieve this? (Choose two.)

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

BigQuery

Vertex AI Model Evaluation provides sliced evaluation when ground truth is available in BigQuery. Vertex AI Explainable AI can help understand feature importance but is not required for fairness monitoring.

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 Feature Store

    Why it's wrong here

    Feature Store is not used for fairness evaluation.

  • Vertex AI Explainable AI

    Why it's wrong here

    Explainable AI is not required for fairness evaluation; it provides feature attributions.

  • BigQuery

    Why this is correct

    BigQuery stores the ground truth labels and can be used as the source for sliced evaluation.

  • Cloud Monitoring

    Why it's wrong here

    Cloud Monitoring can display metrics but does not perform fairness evaluation.

  • Vertex AI Model Evaluation

    Why this is correct

    Model Evaluation with sliced evaluation can compute metrics per subgroup.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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