old_contents: from ada_dnn import DNN
  import numpy
  
  #you need numpy data file
  train_x = numpy.load('X.npy')
  train_y = numpy.load('Y.npy')
  
  
  dnn = DNN([69,512, 39],
            learning_rate_decays=0.98, learning_rate=0.02,
            batch_size=256, epochs=10)
  
  dnn.fit(train_x, train_y)
  dnn.predict_proba(train_x)
  
  
new_contents: from ada_dnn import DNN
  import numpy
  from sklearn.externals import joblib
  
  #you need numpy data file
  train_x = numpy.load('X.npy')
  train_y = numpy.load('Y.npy')
  
  
  dnn = DNN([69,2048, 2048, 2048, 2048, 48],
            learning_rate=0.02,
            dropouts=0.25,
            batch_size=256, epochs=30)
  
  dnn.fit(train_x, train_y)
  joblib.dump(dnn, 'model')
  dnn.predict_proba(train_x)
  
  
subject: Add more complex simple