by Michele Laurelli
A machine learning paradigm where models learn from labeled training data with input-output pairs.
In supervised learning, algorithms learn to map inputs to outputs using labeled examples. The model is trained to minimize the difference between predictions and true labels. Common tasks include classification and regression.
Image classification with labels
Spam email detection
House price prediction