Q15 — AWS AIF-C01 Ch.1

Question 15 of 100 | ← Chapter 1

A company is building an application that needs to generate synthetic data based on existing data. Which type of model can the company use to meet this requirement?

• A. Generative Adversarial Network (GAN) ✓
• B. XGBoost
• C. Residual Neural Network
• D. WaveNet

Correct Answer: A. Generative Adversarial Network (GAN)

Explanation

This question evaluates knowledge of generative modeling techniques. Generative Adversarial Networks (GANs) are explicitly designed to learn the distribution of input data and generate realistic synthetic samples — making them ideal for synthetic data generation. XGBoost is a gradient-boosted decision tree ensemble for supervised learning (e.g., classification/regression); Residual Neural Networks (ResNets) enhance deep network training but are not inherently generative; WaveNet is a deep generative model for audio synthesis, not general-purpose tabular or unstructured synthetic data. Thus, the correct answer is A.