👉 Regularization is a technique used in machine learning where we add extra noise to our model's weights so that it can be easier for the model to find local minima. This adds an extra layer of complexity and can lead to better generalization on unseen data, but at the cost of potentially increased computational costs. In simple terms, regularization is a technique used in machine learning where we add extra noise or bias to our model's weights so that it can be easier for the model to find local min
