
"""simple docstring"""





import numpy as np
import requests







def       __a	(						):
   UpperCAmelCase_   :   Union[str, Any]     	=       requests.get(
       "https://raw.githubusercontent.com/yashLadha/The_Math_of_Intelligence/"
       "master/Week1/ADRvsRating.csv"    )
   UpperCAmelCase_   :   List[Any]     	=       response.text.splitlines()
   UpperCAmelCase_   :   Dict     	=       []
   for item in lines:
      UpperCAmelCase_   :   Tuple     	=       item.split(","    )
      data.append(__lowerCamelCase    )
   data.pop(0    )  # This is for removing the labels from the list
   UpperCAmelCase_   :   Optional[int]     	=       np.matrix(__lowerCamelCase    )
   return dataset







def       __a	(						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    ):
   UpperCAmelCase_   :   Union[str, Any]     	=       len_data

   UpperCAmelCase_   :   Any     	=       np.dot(__lowerCamelCase,						data_x.transpose()    )
   prod -= data_y.transpose()
   UpperCAmelCase_   :   List[Any]     	=       np.dot(__lowerCamelCase,						__lowerCamelCase    )
   UpperCAmelCase_   :   Dict     	=       theta - (alpha / n) * sum_grad
   return theta







def       __a	(						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    ):
   UpperCAmelCase_   :   Any     	=       np.dot(__lowerCamelCase,						data_x.transpose()    )
   prod -= data_y.transpose()
   UpperCAmelCase_   :   Optional[Any]     	=       np.sum(np.square(__lowerCamelCase    )    )
   UpperCAmelCase_   :   Optional[Any]     	=       sum_elem / (2 * len_data)
   return error







def       __a	(						__lowerCamelCase,						__lowerCamelCase    ):
   UpperCAmelCase_   :   List[Any]     	=       10_0000
   UpperCAmelCase_   :   str     	=       0.000_1550

   UpperCAmelCase_   :   List[Any]     	=       data_x.shape[1]
   UpperCAmelCase_   :   str     	=       data_x.shape[0] - 1

   UpperCAmelCase_   :   str     	=       np.zeros((1, no_features)    )

   for i in range(0,						__lowerCamelCase    ):
      UpperCAmelCase_   :   Dict     	=       run_steep_gradient_descent(__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    )
      UpperCAmelCase_   :   Optional[int]     	=       sum_of_square_error(__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    )
      print(f"""At Iteration {i + 1} - Error is {error:.5f}"""    )

   return theta







def       __a	(						__lowerCamelCase,						__lowerCamelCase    ):
   UpperCAmelCase_   :   List[str]     	=       sum(abs(y - predicted_y[i]    ) for i, y in enumerate(__lowerCamelCase    )    )
   return total / len(__lowerCamelCase    )







def       __a	(						):
   UpperCAmelCase_   :   int     	=       collect_dataset()

   UpperCAmelCase_   :   List[str]     	=       data.shape[0]
   UpperCAmelCase_   :   Tuple     	=       np.c_[np.ones(__lowerCamelCase    ), data[:, :-1]].astype(__lowerCamelCase    )
   UpperCAmelCase_   :   Optional[int]     	=       data[:, -1].astype(__lowerCamelCase    )

   UpperCAmelCase_   :   str     	=       run_linear_regression(__lowerCamelCase,						__lowerCamelCase    )
   UpperCAmelCase_   :   Union[str, Any]     	=       theta.shape[1]
   print("Resultant Feature vector : "    )
   for i in range(0,						__lowerCamelCase    ):
      print(f"""{theta[0, i]:.5f}"""    )


if __name__ == "__main__":
    main()






'''simple docstring'''



import math
from decimal import Decimal, getcontext




def       _a      (		_lowercase   :      int = 4000000    ):





     '''simple docstring'''






     try:
          __UpperCAmelCase      :					List[str]    				=     int(_lowercase    )
     except (TypeError, ValueError):
          raise TypeError('''Parameter n must be int or castable to int.'''    )
     if n <= 0:
          raise ValueError('''Parameter n must be greater than or equal to one.'''    )
     __UpperCAmelCase      :					Tuple    				=     100
     __UpperCAmelCase      :					Optional[Any]    				=     (Decimal(5    ) ** Decimal(0.5    ) + 1) / Decimal(2    )

     __UpperCAmelCase      :					Tuple    				=     (math.floor(math.log(n * (phi + 2)     ,   _lowercase    ) - 1    ) // 3) * 3 + 2
     __UpperCAmelCase      :					List[Any]    				=     Decimal(round(phi ** Decimal(index + 1    )    )    ) / (phi + 2)
     __UpperCAmelCase      :					List[str]    				=     num // 2
     return int(_lowercase    )


if __name__ == "__main__":
      print(f"""{solution() = }""")