input: Write a python function to train a Linear Regression model and make predictions.
  assert isinstance(train_and_predict(X_train, y_train, X_test), np.ndarray)
  assert train_and_predict(X_train, y_train, X_test).shape == (len(X_test),)
  assert np.allclose(train_and_predict(X_train, y_train, X_test), predictions)
output: def train_and_predict(X_train, y_train, X_test):
      from sklearn.linear_model import LinearRegression
      import numpy as np
  
      # Train the model
      model = LinearRegression()
      model.fit(X_train, y_train)
  
      # Make predictions
      predictions = model.predict(X_test)
  
      return predictions