Assume we want to train the parameters of linear regression using gradient descent. Assume the training data has two attributes x1,x2 and one target variable y. The data is given as (x1,x2,y). Find the updated parameters after one step of gradient descent with a learning rate of 0.01. Initial parameters are w1=0.5,w2=0.5, and b=0. Traning data is [(1,2,3),(2,3,5),(3,4,6)] and we are using the following regularized loss function: 21w22+N1i=1N21(fw,b(xi)yi)2 Show all of your calculations (including taking the derivative of the regularized loss function)