Q25 — AWS AIF-C01 Ch.1

Question 25 of 100 | ← Chapter 1

A company is developing a model to predict the price of a specific product. The model performs well on the training dataset. However, when the company deploys the model into production, its performance significantly degrades. What should the company do to resolve this issue?

• A. Reduce the amount of data used during training.
• B. Add hyperparameters to the model.
• C. Increase the amount of data used during training. ✓
• D. Increase the model training time.

Correct Answer: C. Increase the amount of data used during training.

Explanation

This question tests knowledge of resolving performance degradation when deploying a model to production. In machine learning, data volume significantly impacts model generalization. Good training performance but poor production performance often indicates insufficient training data, leading to inadequate learning. Increasing training data helps the model learn more features and patterns, thereby improving generalization. Thus, option C is correct. Option A would worsen the issue; option B does not address the root cause; option D has minimal impact on generalization.