


'''simple docstring'''






def 					_snake_case   (     A ,    A ,    A ,    A       )						->    int:



							if start == end:
														return start if lst[start] > item else start + 1
							if start > end:
														return start

							lowerCAmelCase__          =	(start + end) // 2
							if lst[mid] < item:
														return binary_search(UpperCamelCase_ ,    UpperCamelCase_ ,    mid + 1 ,    UpperCamelCase_       )
							elif lst[mid] > item:
														return binary_search(UpperCamelCase_ ,    UpperCamelCase_ ,    UpperCamelCase_ ,    mid - 1       )
							else:
														return mid


def 					_snake_case   (     A       )						->    Tuple:
							lowerCAmelCase__          =	len(UpperCamelCase_       )

							for index in range(1 ,    UpperCamelCase_       ):
														lowerCAmelCase__          =	lst[index]
														lowerCAmelCase__          =	binary_search(UpperCamelCase_ ,    UpperCamelCase_ ,    0 ,    index - 1       )
														lowerCAmelCase__          =	lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]

							return lst


def 					_snake_case   (     A ,    A       )						->    Any:



							if not left:
														return right

							if not right:
														return left

							if left[0] < right[0]:
														return [left[0], *merge(left[1:] ,    UpperCamelCase_       )]

							return [right[0], *merge(UpperCamelCase_ ,    right[1:]       )]


def 					_snake_case   (     A       )						->    Optional[Any]:
							lowerCAmelCase__          =	len(UpperCamelCase_       )
							lowerCAmelCase__   ,					lowerCAmelCase__          =	[], []
							lowerCAmelCase__          =	[lst[0]]
							lowerCAmelCase__          =	[]
							lowerCAmelCase__          =	1
							while i < length:
														if lst[i] < lst[i - 1]:
																					runs.append(UpperCamelCase_       )
																					lowerCAmelCase__          =	[lst[i]]
														else:
																					new_run.append(lst[i]       )
														i += 1
							runs.append(UpperCamelCase_       )

							for run in runs:
														sorted_runs.append(insertion_sort(UpperCamelCase_       )       )
							for run in sorted_runs:
														lowerCAmelCase__          =	merge(UpperCamelCase_ ,    UpperCamelCase_       )

							return sorted_array


def 					_snake_case   (     )						->    List[str]:
							lowerCAmelCase__          =	[5, 9, 10, 3, -4, 5, 178, 92, 46, -18, 0, 7]
							lowerCAmelCase__          =	tim_sort(UpperCamelCase_       )
							print(UpperCamelCase_       )


if __name__ == "__main__":
		main()







import numpy as np
import requests







def 		_UpperCamelCase      (			)     ->      Dict:

						"""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(UpperCamelCase_						)
						data.pop(0						)  # This is for removing the labels from the list
						lowerCAmelCase__			  =  np.matrix(UpperCamelCase_						)
						return dataset







def 		_UpperCamelCase      (			UpperCamelCase_				:    Union[str, Any]			,				UpperCamelCase_				:    Optional[Any]			,				UpperCamelCase_				:    Dict			,				UpperCamelCase_				:    List[Any]			,				UpperCamelCase_				:    int						)     ->      int:

						"""simple docstring"""



						lowerCAmelCase__			  =  len_data

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







def 		_UpperCamelCase      (			UpperCamelCase_				:    str			,				UpperCamelCase_				:    Any			,				UpperCamelCase_				:    str			,				UpperCamelCase_				:    List[Any]						)     ->      Dict:

						"""simple docstring"""



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







def 		_UpperCamelCase      (			UpperCamelCase_				:    Any			,				UpperCamelCase_				:    List[Any]						)     ->      str:

						"""simple docstring"""



						lowerCAmelCase__			  =  10_0000
						lowerCAmelCase__			  =  0.000_1550

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

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

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

						return theta







def 		_UpperCamelCase      (			UpperCamelCase_				:    Dict			,				UpperCamelCase_				:    Any						)     ->      Union[str, Any]:

						"""simple docstring"""



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







def 		_UpperCamelCase      (			)     ->      List[Any]:

						"""simple docstring"""



						lowerCAmelCase__			  =  collect_dataset()

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

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


if __name__ == "__main__":
					main()





