Using Python:

2. (15 points) In a regularized regression model (ridge regression), the target function to be minimized is f()=i=1n(yixi)2+2 where xi and yi are the observed predictor and response values, n is the number of observations, is a given hyper-parameter, and is the target parameter to be estimated. Use the gradient descent method with a fixed learning rate 0.0001 and tolerance 0.0001 to find , respectively when =1,10,100. The observed data are as follows, i.e., n=6,x1=10,y1=32,x6=22,y6=72, etc