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Regularization in machine learning explained clearly — what it is, how L1 and L2 regularization work, and why it prevents overfitting in neural networks and statistical models. This short covers the penalty term formula, the difference between Ridge and Lasso regression, and how lambda controls model complexity. Perfect for CS students ...
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