Machine Learning, Linear Regression, Gradient Descent, Python, Stochastic Gradient.
stepsize = stepsize_i b0=0; b1=0 g_b0 = 1; g_b1 = 1 # while not converge (tolerance is 0.0001) satisfied = False tol = 0.0001 number_of_pass = 0 while satisfied == False: # if go over the entire dataframe, then add one number_of_pass +=1 for i in range(df.shape[0]): xi = x_norm[i] yi = y_norm[i] #