1. Supervised Learning

Definition: Learning from labeled data (input-output pairs).

Examples:

Email Spam Detection:

Input: Emails (features like subject, content).

Output: Label (spam or not spam).

Goal: Classify incoming emails as spam or not spam.

House Price Prediction:

Input: Features (size, location, number of rooms).

Output: Predicted house price.

Goal: Estimate property value based on historical data.

Face Recognition:

Input: Facial features from images.

Output: Person's identity.

Goal: Match a face with a labeled database.


  1. Unsupervised Learning

Definition: Learning patterns from unlabeled data.