input: Write a python function to preprocess the data by scaling the features using StandardScaler.
  assert np.allclose(preprocess_data([[127, 2123]]), scaler.transform([[127, 2123]]))
  assert np.allclose(preprocess_data([[50, 1800]]), scaler.transform([[50, 1800]]))
  assert np.allclose(preprocess_data([[100, 2400]]), scaler.transform([[100, 2400]]))
output: from sklearn.preprocessing import StandardScaler
  import numpy as np
  
  def preprocess_data(data):
      scaler = StandardScaler()
      scaler.fit(data)
      return scaler.transform(data)