Supervised learning involves input-output pairs where the model learns to predict outputs based on labeled data. Classification tasks categorize inputs into specific groups, while regression tasks predict continuous values. Labeling can be manual or derived from existing ratings, making the process efficient yet sometimes challenging. Understanding these concepts is crucial for tackling machine learning problems effectively.
