AI engineering glossary · ML fundamentals
What is supervised learning?
Supervised learning: Learning from examples where every input comes with the correct answer attached. The algorithm studies these pairs and learns a mapping it can apply to new inputs whose answers are unknown. It covers the two most common tasks, predicting categories and predicting numbers, and needs labelled data, which can be costly to produce.
Supervised learning: an example
A dataset of 10,000 home-loan applications, each marked 'repaid' or 'defaulted', is used to teach a model to predict default for new applicants.
Related terms
More ML fundamentals terms
- Target leakage
- Temporal leakage
- Test set
- Time-series split
- Train-test contamination
- Training
- Training error
- Training example
Where you learn it
Supervised learning is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.