10. Write a program to implement Multiple Linear Regression Model using python
import numpy as np
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt

def generate_dataset(n):
	x = []
	y = []
	random_x1 = np.random.rand()
	random_x2 = np.random.rand()
	for i in range(n):
		x1 = i
		x2 = i/2 + np.random.rand()*n
		x.append([1, x1, x2])
		y.append(random_x1 * x1 + random_x2 * x2 + 1)
	return np.array(x), np.array(y)

x, y = generate_dataset(200)

mpl.rcParams['legend.fontsize'] = 12

fig = plt.figure()
ax = fig.add_subplot(projection ='3d')

ax.scatter(x[:, 1], x[:, 2], y, label ='y', s = 5)
ax.legend()
ax.view_init(45, 0)

plt.show()






Output