Q16 — AWS AIF-C01 Ch.2

Question 16 of 100 | ← Chapter 2

A company experiences database errors causing missing words in documents. It wants to build a machine learning model that suggests plausible words to fill in missing text. Which type of model best fits this requirement?

• A. Topic modeling
• B. Clustering model
• C. Prescriptive machine learning model
• D. BERT-based model ✓

Correct Answer: D. BERT-based model

Explanation

BERT-based models leverage bidirectional contextual understanding to predict masked tokens accurately. They excel at natural language inference and masked language modeling—making them ideal for suggesting contextually appropriate words to fill gaps in text. Other options lack the requisite sequence-aware, context-sensitive capabilities.