fitting_straight_line_pytorch___01___predifined_m_and_c.py

# Defining the range of 'x', the independent variable
x_range = [-2000, 2000]

# Defining the extent of noise, which would be added to both the dependent as well as the independent variable
deviation = 100

# For the data points to roughly fall on a staright line, we need to define the slope and the intercept of that line
# Let's intoduce some randomness in the slope and intercept selection process
m_synthetic = random.randint(-100, 100)/100. # m_synthetic is real number from the set(-1.0, -0.99, -0.98 ...., 0.98, 0.99, 1.0)
c_synthetic = random.randint(-10, 10)        # c_synthetic is an integer from the set(-10, -9, -8 ..., 8, 9, 10)

print('\nm_synthetic: {}'.format(m_synthetic))
print('c_synthetic: {}'.format(c_synthetic))

fitting_straight_line_pytorch___01___predifined_m_and_c_output.py

m_synthetic: -0.67
c_synthetic: 6