Hi,

I understand that in Lasso regression, sum of weights are added to the cost function. And in Ridge regression, sum of squares of weights are added to the cost function.

Mathematically, how do these two differ? How do they affect the update of weights after every iteration? How do they affect the final performance of the model?

Thank you