input: def predict_with_linear_regression(X, Y):
      """
      Perform linear regression on the given dataset to predict the numbers.
      Given two lists, X and Y, representing the independent and dependent variables respectively,
      fit a linear regression model to the data and use it to predict the value of y for a new x value.
      
      Example:
      >>> predict_with_linear_regression([1,2,3,4,5], [3,5,7,9,13])
      [15.]
      """
      import numpy as np
      from sklearn.linear_model import LinearRegression
  
      X = np.array(X).reshape(-1,1)
      Y = np.array(Y)
  
      model = LinearRegression()
      model.fit(X, Y)
  
      return model.predict([[7]])
output:     import numpy as np
      from sklearn.linear_model import LinearRegression
  
      X = np.array(X).reshape(-1,1)
      Y = np.array(Y)
  
      model = LinearRegression()
      model.fit(X, Y)
  
      return model.predict([[7]])