Advanced Signal Processing
L2 regularization, also known as weight decay, is a technique used to prevent overfitting in machine learning models, particularly in neural networks. It adds a penalty equal to the square of the magnitude of coefficients (weights) to the loss function, encouraging the model to keep weights small and thus promote simpler models that generalize better to unseen data.
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