Supervised Learning
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Learning from labeled data by mapping inputs to known outputs. The most common ML paradigm, used whenever you have examples of correct answers.
Key Properties
How It Works
The model learns a function f(x) → y from training examples where both x (input) and y (label) are provided. During inference, the model predicts y for unseen x.
Related
- Unsupervised Learning (contrast: no labels)
- Semi-Supervised Learning (hybrid approach)