title: Keras for implement convolution neural network
body: <p>I have just install tensorflow and keras. And I have the simple demo as follow:</p>
  
  <pre><code>from keras.models import Sequential
  from keras.layers import Dense
  import numpy
  # fix random seed for reproducibility
  seed = 7
  numpy.random.seed(seed)
  # load pima indians dataset
  dataset = numpy.loadtxt("pima-indians-diabetes.csv", delimiter=",")
  # split into input (X) and output (Y) variables
  X = dataset[:,0:8]
  Y = dataset[:,8]
  # create model
  model = Sequential()
  model.add(Dense(12, input_dim=8, init='uniform', activation='relu'))
  model.add(Dense(8, init='uniform', activation='relu'))
  model.add(Dense(1, init='uniform', activation='sigmoid'))
  # Compile model
  model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
  # Fit the model
  model.fit(X, Y, nb_epoch=10, batch_size=10)
  # evaluate the model
  scores = model.evaluate(X, Y)
  print("%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))
  </code></pre>
  
  <p>And I have this warning:</p>
  
  <pre><code>/usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.py:86: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(12, activation="relu", kernel_initializer="uniform", input_dim=8)` '` call to the Keras 2 API: ' + signature)
  /usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.py:86: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(8, activation="relu", kernel_initializer="uniform")` '` call to the Keras 2 API: ' + signature)
  /usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.py:86: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(1, activation="sigmoid", kernel_initializer="uniform")` '` call to the Keras 2 API: ' + signature)
  /usr/local/lib/python2.7/dist-packages/keras/models.py:826: UserWarning: The `nb_epoch` argument in `fit` has been renamed `epochs`. warnings.warn('The `nb_epoch` argument in `fit` '
  </code></pre>
  
  <p>So, How can I handle this? </p>