How AI Systems Work
Evaluation and Overfitting
How to tell genuine learning from memorizing training examples.
In this lesson
Lesson goals
- Metrics aligned with error cost
- Comparing training and test results
- Improving generalization
Core idea
How to tell genuine learning from memorizing training examples.
1. Metrics aligned with error cost: understand it in context, identify inputs and outputs, and define how the result will be verified.
2. Comparing training and test results: understand it in context, identify inputs and outputs, and define how the result will be verified.
3. Improving generalization: understand it in context, identify inputs and outputs, and define how the result will be verified.
Practical example
Consider a real application of “Evaluation and Overfitting.” Start small, identify available data, and compare the system with a clear baseline before expanding it.
Check your understanding
- Explain “Evaluation and Overfitting” in your own words.
- Give one appropriate and one misleading application.
- What risk or limitation should be monitored?

