Question: A factory has only 900 labeled sensor records for detecting machine faults. Explain why carefully designed, expert-crafted features may work better than training a large neural network from scratch.

Sample answer: With only 900 examples, a large neural network may not see enough data to learn reliable patterns and can overfit. Features designed from domain knowledge can inject useful structure into the model, which often improves performance when data is scarce.

Key points:

• Large neural networks usually benefit from more data
• Small datasets limit what a network can learn reliably
• Expert-crafted features add human knowledge
• This can be especially helpful in low-data settings

Rubric: Full credit for explaining that limited data weakens the case for a large neural network and that expert-crafted features supply useful prior knowledge. Partial credit for mentioning only one of those ideas or giving an incomplete explanation.