Supervised Learning
In plain terms
Training models on labeled examples.
Going deeper
Supervised learning teaches a model from input-output pairs so it can predict labels for new data. It learns from answers provided during training.
Under the hood
Splits into classification and regression; performance depends on label quality and quantity.
Examples
Spam detection, image classification, price prediction, labeled datasets.
Think of it like...
Like learning with flashcards that show both the question and the correct answer.