AI engineering glossary · ML fundamentals
What is regression?
Regression: A supervised task where the goal is to predict a continuous number rather than a category. The model learns how the inputs relate to the numeric target and outputs an estimate for new cases. Errors are measured by how far predictions fall from actual values, for example with mean squared error.
Regression: an example
Predicting the resale price in rupees of a used car from its age, kilometres driven and brand is a regression problem.
Related terms
- Classification
- Supervised learning
- Label
- Loss function
More ML fundamentals terms
- Regularisation
- Representation learning
- Reproducibility
- Selection bias
- Self-supervised learning
- Semi-supervised learning
- Shortcut learning
- Spurious correlation
Where you learn it
Regression is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.