input: def identify_fruit(X: List[List[float]], y: List[int], test_data: List[List[float]]) -> List[int]:
      """Develop a machine learning algorithm using SVM to identify apples from bananas.
      >>> identify_fruit([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]], [0, 0, 0, 1, 0, 1], [[2,2,2], [4,4,4]])
      [0, 1]
      """
output:     from sklearn.svm import SVC
      from sklearn.preprocessing import StandardScaler
  
      scaler = StandardScaler()
      X_scaled = scaler.fit_transform(X)
      test_data_scaled = scaler.transform(test_data)
  
      svm = SVC(kernel='linear')
      svm.fit(X_scaled, y)
  
      predictions = svm.predict(test_data_scaled)
      return predictions.tolist()