Q7 — AWS AIF-C01 Ch.1

Question 7 of 100 | ← Chapter 1

A company performs quarterly forecasting to optimize inventory and meet anticipated demand. The company uses an ML model for forecasting. A developer is writing a report about the trained ML model to provide transparency and explainability to business stakeholders. To meet transparency and explainability requirements, which content should the developer include in the report?

• A. Model training code
• B. Partial Dependence Plot (PDP) ✓
• C. Sample data used for training
• D. Model convergence table

Correct Answer: B. Partial Dependence Plot (PDP)

Explanation

This question tests understanding of content required for ML model reporting to satisfy transparency and explainability. Partial Dependence Plots (PDPs) visually illustrate how individual features influence model predictions, helping stakeholders understand model behavior. Model training code, sample training data, and convergence tables are less accessible and interpretable for non-technical stakeholders. Therefore, option B—the Partial Dependence Plot—is the best choice.