Supervised Learning

Supervised Learning

Supervised Learning is a type of Machine Learning where the system learns from a labeled dataset — meaning each input data point is paired with the correct output (or label).

How it works:

• The algorithm is trained on examples where the answer is already known.

• It learns to map inputs (like images or text) to the correct output (like categories or numbers).

• Once trained, it can predict the output for new, unseen data.

Examples:

• Email spam detection: The system learns from emails labeled as “spam” or “not spam” to classify new emails.

• Image recognition: The model learns to identify animals in photos by training on images labeled with the correct animal names.

Supervised Learning is widely used for classification and regression problems where clear answers are available.