Need help with this homework question for my Stats Data Science class! We code in python on Jupyterhub, but I don't mind, as long as it's coded in python it's fine!

Points out of 20.00 Suppose we have ?2 observations of (yi, Ti, Ti2), where r, E RS. The data matrix is of size X E Rx2 and y/ is a column vector. The parameter of interest is 0 = (01 02)". Flag question Given X" , y and ) as inputs, ridge regression computes @ that minimizes the following optimization problem: minimize, f (@) where f(0) = ally - Xol12 + 11013. The 2-norm of a column vector of length k is |lull; = ulu = >!_, up. Part 1 Express f(01, 02) as a sum over fi(61, (2), where i = 1, 2, ..., n. Your expression should look like f(01, 02) = zn EF fi(01, 02). Write out the **complete expression** for f($1, #2). Part 2 Calculate partial derivatives of f (01, 02) respect to 01 and 02: 20, f (0 1, 02) = ... 202 f (01, 02) = ... Part 3 Given an appropriate step length a > 0, derive the updates for current estimates 0, and 02: gnew = 01 + a . ... gnew = 02 + 0 . ... Part 4 Combine the updates given by the previous part into a matrix update. Write your answer in terms of updated parameter vector gnew, current estimate @ , vector y, matrix X" , and other constants (a, n, and ) )