When applying regularization to neural networks, do we need to optimize lambda? If yes, do we look at the training and cross-validation error for various lambda values and then choose the one corresponding to the lowest cross-validation error?
i trained my model first without applying Regularization term ( right side ). and then applying Regularization the way Andrew applied to the model( left side ).You can see the differences and how it might affect preventing overfitting.