What is L1 and L2 regularization in Deep Learning?

In deep learning, L1 and L2 regularization are regularization techniques used to penalize the model’s weights during the training process. This penalty discourages the model from assigning excessive importance to certain features, thereby reducing the risk of overfitting. L1 Regularization L1 regularization, also known as Lasso regularization, adds a penalty proportional to the absolute value…