Supervised Learning

Lesson goals

• Inputs and labels
• Classification and regression
• Label quality and representation

Core idea

Learning from labeled examples for classification and prediction.

1. Inputs and labels: understand it in context, identify inputs and outputs, and define how the result will be verified.

2. Classification and regression: understand it in context, identify inputs and outputs, and define how the result will be verified.

3. Label quality and representation: understand it in context, identify inputs and outputs, and define how the result will be verified.

Practical example

Consider a real application of “Supervised Learning.” Start small, identify available data, and compare the system with a clear baseline before expanding it.

Check your understanding

1. Explain “Supervised Learning” in your own words.
2. Give one appropriate and one misleading application.
3. What risk or limitation should be monitored?