Supervised Learning: Learning with a Teacher

Imagine a student learning with the help of a teacher. The teacher provides questions and answers,

and the student learns by correcting mistakes. That's exactly how supervised learning

works. Here, the dataset comes with labels, meaning we already

know the correct output. For example, predicting house prices using features

like size and location, classifying emails as spam or not spam. The model learns a mapping from input/output,

and during training, it checks how far its predictions are from the actual answers.

Common supervised learning tasks include classification, like yes/no, spam/not spam,

regression, like predicting prices or scores. Popular algorithms include linear regression,