




'''simple docstring'''




import numpy as np
import requests





def   a_							(   )							->		Tuple:



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





def   a_							(   __snake_case							:    List[str]     , __snake_case							:    Optional[Any]     , __snake_case							:    Tuple     , __snake_case							:    Optional[int]     , __snake_case							:    int     )							->		List[str]:



       """simple docstring"""
       lowerCamelCase_							=len_data

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





def   a_							(   __snake_case							:    Dict     , __snake_case							:    Dict     , __snake_case							:    List[str]     , __snake_case							:    Dict     )							->		List[Any]:



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





def   a_							(   __snake_case							:    Any     , __snake_case							:    int     )							->		Tuple:



       """simple docstring"""
       lowerCamelCase_							=10_0000
       lowerCamelCase_							=0.0_0_0_1_5_5_0

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

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

       for i in range(0     , __snake_case     ):
              lowerCamelCase_							=run_steep_gradient_descent(__snake_case     , __snake_case     , __snake_case     , __snake_case     , __snake_case     )
              lowerCamelCase_							=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   a_							(   __snake_case							:    str     , __snake_case							:    str     )							->		int:



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





def   a_							(   )							->		List[str]:



       """simple docstring"""
       lowerCamelCase_							=collect_dataset()

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

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


if __name__ == "__main__":
     main()










'''simple docstring'''




import warnings

from .generation import FlaxGenerationMixin


class 						__UpperCamelCase (				lowerCamelCase__       ):
       # warning at import time
       warnings.warn(
           'Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will '
           'be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead.'    ,      lowerCamelCase__    ,      )




