




import numpy as np
import requests





def 							lowerCamelCase    (							)->			Optional[Any]:

       """simple docstring"""




       a			   =requests.get(
           """https://raw.githubusercontent.com/yashLadha/The_Math_of_Intelligence/"""
           """master/Week1/ADRvsRating.csv"""      )
       a			   =response.text.splitlines()
       a			   =[]
       for item in lines:
              a			   =item.split(""","""      )
              data.append(__snake_case      )
       data.pop(0      )  # This is for removing the labels from the list
       a			   =np.matrix(__snake_case      )
       return dataset





def 							lowerCamelCase    (							UpperCAmelCase_	:      Optional[Any]   ,       UpperCAmelCase_	:      Union[str, Any]   ,       UpperCAmelCase_	:      Optional[Any]   ,       UpperCAmelCase_	:      Tuple   ,       UpperCAmelCase_	:      Any      )->			List[str]:

       """simple docstring"""




       a			   =len_data

       a			   =np.dot(__snake_case   ,       data_x.transpose()      )
       prod -= data_y.transpose()
       a			   =np.dot(__snake_case   ,       __snake_case      )
       a			   =theta - (alpha / n) * sum_grad
       return theta





def 							lowerCamelCase    (							UpperCAmelCase_	:      List[str]   ,       UpperCAmelCase_	:      Any   ,       UpperCAmelCase_	:      List[Any]   ,       UpperCAmelCase_	:      Dict      )->			int:

       """simple docstring"""




       a			   =np.dot(__snake_case   ,       data_x.transpose()      )
       prod -= data_y.transpose()
       a			   =np.sum(np.square(__snake_case      )      )
       a			   =sum_elem / (2 * len_data)
       return error





def 							lowerCamelCase    (							UpperCAmelCase_	:      Union[str, Any]   ,       UpperCAmelCase_	:      Optional[Any]      )->			Dict:

       """simple docstring"""




       a			   =10_0000
       a			   =0.0_00_15_50

       a			   =data_x.shape[1]
       a			   =data_x.shape[0] - 1

       a			   =np.zeros((1, no_features)      )

       for i in range(0   ,       __snake_case      ):
              a			   =run_steep_gradient_descent(__snake_case   ,       __snake_case   ,       __snake_case   ,       __snake_case   ,       __snake_case      )
              a			   =sum_of_square_error(__snake_case   ,       __snake_case   ,       __snake_case   ,       __snake_case      )
              print(F'''At Iteration {i + 1} - Error is {error:.5f}'''      )

       return theta





def 							lowerCamelCase    (							UpperCAmelCase_	:      List[Any]   ,       UpperCAmelCase_	:      Optional[int]      )->			Union[str, Any]:

       """simple docstring"""




       a			   =sum(abs(y - predicted_y[i]      ) for i, y in enumerate(__snake_case      )      )
       return total / len(__snake_case      )





def 							lowerCamelCase    (							)->			int:

       """simple docstring"""




       a			   =collect_dataset()

       a			   =data.shape[0]
       a			   =np.c_[np.ones(__snake_case      ), data[:, :-1]].astype(__snake_case      )
       a			   =data[:, -1].astype(__snake_case      )

       a			   =run_linear_regression(__snake_case   ,       __snake_case      )
       a			   =theta.shape[1]
       print("""Resultant Feature vector : """      )
       for i in range(0   ,       __snake_case      ):
              print(F'''{theta[0, i]:.5f}'''      )


if __name__ == "__main__":
    main()






def  a_		(							__snake_case					)	->			str:

			'''simple docstring'''


			return " ".join([word[::-1] for word in input_str.split()]					)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
