
"""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()









from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
a_    :				List[str]					=			TypeVar('T', bound='Enum')



@unique
class  SCREAMING_SNAKE_CASE_  ( SCREAMING_SNAKE_CASE__			):


  """simple docstring"""





  _a								=							80
  _a								=							70
  _a								=							60
  _a								=							50
  _a								=							40
  _a								=							30
  _a								=							20
  _a								=							10



@unique
class  SCREAMING_SNAKE_CASE_  ( SCREAMING_SNAKE_CASE__			):


  """simple docstring"""





  _a								=							24
  _a								=							21
  _a								=							18
  _a								=							15
  _a								=							12
  _a								=							9
  _a								=							6
  _a								=							3
  _a								=							2
  _a								=							1
  _a								=							-1
  _a								=							-2
  _a								=							-3
  _a								=							-6
  _a								=							-9
  _a								=							-12
  _a								=							-15
  _a								=							-18
  _a								=							-21
  _a								=							-24





  @classmethod
  def 			__A      (  cls						)		->   dict:





       '''simple docstring'''







       return {unit.name: unit.value for unit in cls if unit.value > 0}







  @classmethod
  def 			__A      (  cls						)		->   dict:





       '''simple docstring'''







       return {unit.name: unit.value for unit in cls if unit.value < 0}




def   _SCREAMING_SNAKE_CASE      (	snake_case_		:						float						):
     __magic_name__				=       SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
     for name_prefix, value_prefix in prefixes.items():
          __magic_name__				=       value / (10**value_prefix)
          if numerical_part > 1:
               return f'{numerical_part!s} {name_prefix}'
     return str(snake_case_						)




def   _SCREAMING_SNAKE_CASE      (	snake_case_		:						float						):
     for prefix in BinaryUnit:
          __magic_name__				=       value / (2**prefix.value)
          if numerical_part > 1:
               return f'{numerical_part!s} {prefix.name}'
     return str(snake_case_						)


if __name__ == "__main__":
    import doctest

    doctest.testmod()