Answer Posted / Ankur

Regularization is a technique used to prevent overfitting in machine learning models, especially those with many parameters (such as neural networks and support vector machines). It adds a penalty term to the loss function that discourages large weights or complex model structures. This helps to improve the generalization ability of the model by reducing noise and capturing more important patterns in the data.

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