Supervised Learning

Training with labeled examples (input → target).

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Supervised learning uses input–target pairs to learn a mapping function.

• Tasks: Classification (category), regression (numeric value), ranking.
• Key factors: Label quality, class balance, appropriate metrics.
• Risks: Data leakage, overfitting, distribution shifts in deployment.
• Practice: Cross-validation, regularization, early stopping, data augmentation.