3 Gaussian Mixture Model (GMM) [40 pts] In this problem, you will implement the Gaussian Mature Model (or mixture of Gaussians). You shoulu implement from scratch, using either MATLAB G Python. Use the same d taset as in the previous problem. You should run your implementation with K = ?, and .un until convergence. You can choose to terminate the iteration when the change on the log-li..elihood, computed by equation (9.28) on page 459 of the textbook, is smaller than a small threshold (such as e-5). Please use the EM algorithm on page 458 and page 459 of the textbook as the reference for implementation, and you could use the code in "init_gmm.m" on Canvas for initializing parameters of GMM. ror K = 2, plot the points using its first two features. Use two different colors or symbols to distinguish the two clusters. The cluster assignment is determined by the posterior y(Znk) computed by equation (9.23) of the textbook. A data point x, is assigned to cluster 1 if :'(Zn) > y(Zn2), and it is assigned to cluster 2 otherwise. Write out your observations from the obtained results. n1