solve for machine learning numpy python Linear regression with…

Question Answered step-by-step solve for machine learning numpy python Linear regression with… solve for machine learning numpy pythonLinear regression with numpy 1-linersHere we initialize a random data matrix X and random numerical labels  , import numpy as npX = np.random.randn(10,3)y = np.random.randn(10,1)# we also initialize a hypothetical hyperplane defined by w and bw = np.random.randn(1,3)b = -1(i) find the numerical labels predicted by the model (w,b) for the points in X#  write your code that should be a single numpy line:#  try to generalize it by expressing everying in terms of matrices# write down your code: # y_predicted =(ii) find the updated weights after one application of gradient descent with lr = 0.1#      write your code that should be a single numpy line: y_ = np.random.randn(10,1)  Computer Science Engineering & Technology Python Programming CS 675 Share QuestionEmailCopy link Comments (0)