L2 Regularized Gradient

Problem

Adding an L2 penalty (lambda / 2) * ||w||^2 to a loss adds lambda * w to the gradient.

Given the data gradient and the weights, return the regularized gradient for the supplied lambda.

Hint

The penalty gradient is linear in the weights.

case 1

in: [[1,2],[3,4],0.1]

expected: [1.3,2.4]

case 2

in: [[0,0],[1,-1],1]

expected: [1,-1]

case 3

in: [[2],[0],5]

expected: [2]

Starter codePython

def l2_regularized_gradient(grad, weights, lam):
    # Your code here
    pass

3 test cases · run your code against them in the editor