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When does regularization become necessary in machine learning?
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Answer / Satendra Kumar
Regularization becomes necessary in machine learning when the model starts to overfit the training data, leading to poor performance on unseen data. Regularization methods such as L1 and L2 regularization help prevent overfitting by adding a penalty term to the loss function.
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