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# Write a code to Implement Linear Regression to find the line of best fit for the given data with the following template linear_regression.py

INSTRUCTIONS TO CANDIDATES

Write a code to Implement Linear Regression to find the line of best fit for the given data with the following template linear_regression.py Download linear_regression.py #!/usr/bin/python3 import numpy as np import matplotlib.pyplot as plt x = np.array([1.94604787,0.29870663,1.16572212,0.23660326,1.1853177,0.02483777,1.66238768,1.14064289,0.30998417,1.76655137,0.1108289,1.3818357,1.90275341,1.17903071,1.91377347,1.32758051,0.78688845,0.39573134,0.80218988,1.7508366]) y = np.array([10.95850425,4.24627261,6.86303134,4.06642225,7.00694291,3.77130116,8.43058007,6.1613416,5.24132551,10.04738966,4.73768563,8.82735864,7.72214599,6.6697928,9.70689272,7.46825204,5.67151139,4.44101235,5.785642,8.48418181]) L = 0.05 # The learning Rate trial = 10000 # The number of iterations to perform gradient descent # Initialization m = 0 c = 0 # Implement Linear Regression Algorithm as Machine Learning for i in range(trial): # Performing Gradient Descent # End of Implementation print (m, c)

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