WildRoyalPhases created by damntoochill - https://repl.it/@damntoochill/WildRoyalPhases

main.py

import numpy as np 

def Gradient_Descent(x,y):
  iterations = 1000
  n = len(x)
  lr = 0.01
  w_curr = b_curr = 0 #initialising the weights as 0
  for i in range(iterations):
     yhat = w_curr*x + b_curr
     cost_func = sum((y-yhat)**2)
     dw = -(1/n)*sum(2*x*(y-yhat))
     db = -(1/n)*sum(2*(y-yhat))
     w_curr = w_curr - lr*dw
     b_curr = b_curr - lr*db
     print("w {}, b {}, cost_val {}".format(w_curr, b_curr, cost_func))


x = np.array([1,2,3])

y = np.array([3,5,7])

Gradient_Descent(x,y)