Could you discuss the role of regularization techniques such as L1 and L2 regularization in preventing overfitting in machine learning models?

[Archi jain]

Regularization techniques like L1 and L2 regularization play a crucial role in preventing overfitting in machine learning models. Overfitting occurs when a model learns to memorize the training data rather than generalize well to unseen data. This phenomenon can lead to poor performance when the model encounters new data.