input: Write a python function to create and train a Linear Regression model using given feature and target vectors.
  assert type(train_model([1, 2, 3, 4], [500])) == tuple
  assert len(train_model([1, 2, 3, 4], [500])) == 2
  assert type(train_model([1, 2, 3, 4], [500])[0]) == np.ndarray
  assert type(train_model([1, 2, 3, 4], [500])[1]) == np.float64
output: def train_model(features, target):
      import numpy as np
      from sklearn.linear_model import LinearRegression
  
      # Reshaping the features to fit the model
      X = np.array(features).reshape(-1, 1)
      y = np.array(target)
      
      # Creating and training the Linear Regression model
      model = LinearRegression()
      model.fit(X, y)
      
      # Getting the coefficient and intercept
      coef = model.coef_
      intercept = model.intercept_
      
      return coef, intercept