Question: What is overfitting in the context of deep learning?

Options:

1. When the model performs well on training data but poorly on unseen data
2. When the model performs equally on training and test data
3. When the model is too simple to capture the underlying patterns
4. When the model has too many parameters

Correct Answer: When the model performs well on training data but poorly on unseen data

Solution:

Overfitting occurs when a model learns the training data too well, including noise, resulting in poor performance on unseen data.