Case context: Your team has prepared a cleaned dataset for a new image classification problem. The training set contains exactly 1,000,000 labeled examples.

Question: What model family would you favor for this project, and why does the dataset size matter?

Sample answer: I would favor a neural network. With about one million labeled examples, a neural network is often a strong choice because large networks can make good use of very large datasets and usually improve as more labeled data becomes available.

Key points:

• Recommend a neural network.
• Use the dataset size of 1,000,000 labeled examples as the reason.
• Explain that neural networks tend to benefit from large amounts of training data.

Rubric: The answer must recommend a neural network and connect that recommendation to the presence of one million labeled examples.