


import numpy as np
import requests






def  _UpperCAmelCase						( )		->Any:


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






def  _UpperCAmelCase						( __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase							)		->List[Any]:


 '''simple docstring'''
 snake_case :			List[str]							=   len_data

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






def  _UpperCAmelCase						( __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase							)		->List[str]:


 '''simple docstring'''
 snake_case :			Union[str, Any]							=   np.dot(__lowerCamelCase			,  data_x.transpose()							)
 prod -= data_y.transpose()
 snake_case :			Any							=   np.sum(np.square(__lowerCamelCase							)							)
 snake_case :			Union[str, Any]							=   sum_elem / (2 * len_data)
 return error






def  _UpperCAmelCase						( __lowerCamelCase			,  __lowerCamelCase							)		->Union[str, Any]:


 '''simple docstring'''
 snake_case :			Optional[int]							=   100000
 snake_case :			Any							=   0.000_1550

 snake_case :			List[str]							=   data_x.shape[1]
 snake_case :			Tuple							=   data_x.shape[0] - 1

 snake_case :			int							=   np.zeros((1, no_features)							)

 for i in range(0			,  __lowerCamelCase							):
  snake_case :			Tuple							=   run_steep_gradient_descent(__lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase							)
  snake_case :			int							=   sum_of_square_error(__lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase							)
  print(f'''At Iteration {i + 1} - Error is {error:.5f}'''							)

 return theta






def  _UpperCAmelCase						( __lowerCamelCase			,  __lowerCamelCase							)		->List[str]:


 '''simple docstring'''
 snake_case :			Any							=   sum(abs(y - predicted_y[i]							) for i, y in enumerate(__lowerCamelCase							)							)
 return total / len(__lowerCamelCase							)






def  _UpperCAmelCase						( )		->int:


 '''simple docstring'''
 snake_case :			Optional[Any]							=   collect_dataset()

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

 snake_case :			Tuple							=   run_linear_regression(__lowerCamelCase			,  __lowerCamelCase							)
 snake_case :			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()










import os






def  _UpperCAmelCase						( )		->Tuple:


 '''simple docstring'''
 snake_case :			Dict							=   0
 snake_case :			int							=   0
 with open(os.path.dirname(__lowerCamelCase							) + '''/p022_names.txt'''							) as file:
  snake_case :			int							=   str(file.readlines()[0]							)
  snake_case :			Any							=   name.replace('''"'''			,  ''''''							).split(''','''							)

 name.sort()
 for i in range(len(__lowerCamelCase							)							):
  for j in name[i]:
   temp_sum += ord(__lowerCamelCase							) - ord('''A'''							) + 1
  total_sum += (i + 1) * temp_sum
  snake_case :			List[Any]							=   0
 return total_sum


if __name__ == "__main__":
  print(solution())






