Sample simple linear regression with gradient descent

gradient_descent_simple_regression.py

# initial values 
b = 30
m = 3 
db = 1
dm = 1

limit = 0.00001
learning_rate = 0.001

step_size_b = -3
step_size_m = -3

i = 0

while abs(step_size_m) > limit:
    i += 1
    
    step_size_b = db * learning_rate
    b = b - step_size_b
    db = (1/4) * ((-2*(50-(m*5+b))-2*(72-(m*10+b))-2*(76-(m*15+b))-2*(90-(m*20+b))))
    print("******** iteration: ", i)
    print("b", b)
    print("db", db)
    print("step_size_b", step_size_b)

    step_size_m = dm * learning_rate
    m = m - step_size_m
    dm = (1/4) * (-10*(50-(m*5+b))-20*(72-(m*10+b))-30*(76-(m*15+b))-40*(90-(m*20+b)))
    print("m", m)
    print("dm", dm)
    print("step_size_m", step_size_m)