Linear regression implementation

#1

why we are taking original x in hypothesis function and in other function like error ,gradient and gradientDecent we are taking the normalized value

#2

Hey you are confusing the function parameters at the time of function definition with function calls.

final_theta, error_list,theta_list = gradientDescent(X,Y) // this is a function call to run gradient descent using Normalised data while the cell above this call is where we have defined the functions.

so
def hypothesis(x,theta)
return theta[0] + theta[1]*x

can also be defined as

def hypothesis(a,b):
return b[0] + b[1]*a