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  | [ | |
| { | |
| "lastname": "Martin", | |
| "firstname": "Chloe", | |
| "address": { | |
| "numStreet": 15, | |
| "streetName": "rue Lafayette", | |
| "postalCode": "75001", | |
| "city": "Paris" | 
  
    
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  | import numpy as np | |
| from sklearn.preprocessing import add_dummy_feature | |
| class LinearRegression: | |
| def __init__(self): | |
| self.X = None | |
| self.y = None | |
| self.theta = None | |
| self.coaf_ = None | 
  
    
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  | def binary_search(data, param) -> bool : | |
| found = False # To handle recursive calls | |
| if len(data) == 0 : | |
| return None | |
| if len(data) == 2 : | |
| if data[0] == param or data[1] == param : | |
| return True | 
  
    
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  | def linear_search(data, param) -> bool : | |
| for el in data : | |
| if el == param : # We found it | |
| return True | |
| return False | |
| if __name__ == '__main__' : | |
| data = [ 7, 10, 3, 1, 66, 6 ] | |
| param = 1 # The integer we are looking for in the array | 
  
    
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  | std::shared_ptr<Type> sp; | |
| Type* ptr = new Type(); | |
| sp = ptr ; // compiler error!!! | 
  
    
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  | class Type { | |
| public: | |
| foo(); | |
| } | |
| Type::foo(){ | |
| // Doing something | |
| } |