Type of machine learning where the model is trained on labeled data (examples with known correct answers). The model learns to predict the correct label for new inputs. Includes classification and regression.
In AI-901: most business use cases are supervised. Examples: classifying emails as spam (classification), predicting house prices (regression), detecting fraud. The training data always has labels.
Supervised learning is a concept that can show up on the exam. Check the full guide to see it in context.