Case context: You are building a model to spot manufacturing defects in conveyor-belt images. The current network is underfitting, but when you made the network much larger, the validation error got worse. You are now considering a different network architecture rather than only adjusting the size of the current one.

Question: What should you expect about this approach, and where might you look for ideas for new architectures?

Sample answer: A new architecture may help with both underfitting and overfitting at the same time. However, it is usually harder to predict the result of than a simple size change, and it can be more difficult to design and implement. Good places to look for ideas include recent research papers and open-source code repositories such as GitHub.

Key points:

• Can influence both bias and variance
• Less predictable than a simple size adjustment
• Harder to discover and implement
• Search papers and open-source code for ideas

Rubric: The learner must mention the possible effect on both error sources, the difficulty and unpredictability of the change, and sources for architecture ideas.