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Advantages of Supervised Learning
Supervised learning offers several advantages: (1) it learns a mapping from inputs to outputs using labeled examples drawn from prior experience, so predictions are grounded in observed data; (2) because the correct outputs are known during training, model performance can be measured and optimized directly against these known labels; (3) this makes supervised learning applicable to a wide range of real-world prediction and classification problems, such as those addressed by linear regression, logistic regression, and neural networks.
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