Q83 — AWS AIF-C01 Ch.2

Question 83 of 100 | ← Chapter 2

Select the correct learning method(s) from the list below for the following use case. One or more learning methods may be selected. Building a product recommendation system that recommends similar products based on examples.

• A. Zero-shot Learning
• B. One-shot Learning ✓
• C. Few-shot Learning

Correct Answer: B. One-shot Learning

Explanation

This question evaluates application scenarios of different learning paradigms. One-shot learning enables models to generalize from a single example — ideal for recommending similar products when only limited exemplars are available. Few-shot learning uses a small number of examples (typically 3–5), which may also apply but is less precise than one-shot for minimal-exemplar scenarios. Zero-shot learning requires no task-specific examples and relies on semantic embeddings or prompt engineering — insufficient for reliable similarity-based recommendations without exemplars. Thus, B (One-shot Learning) is the most appropriate choice; C (Few-shot Learning) may also be valid depending on context, but the question emphasizes 'based on examples' with minimal data, making one-shot the primary fit.