title: Keras model.summary() result - Understanding the # of Parameters
body: <p>I have a simple NN model for detecting hand-written digits from a 28x28px image written in python using Keras (Theano backend):</p>
  
  <pre><code>model0 = Sequential()
  
  #number of epochs to train for
  nb_epoch = 12
  #amount of data each iteration in an epoch sees
  batch_size = 128
  
  model0.add(Flatten(input_shape=(1, img_rows, img_cols)))
  model0.add(Dense(nb_classes))
  model0.add(Activation('softmax'))
  model0.compile(loss='categorical_crossentropy', 
           optimizer='sgd',
           metrics=['accuracy'])
  
  model0.fit(X_train, Y_train, batch_size=batch_size, nb_epoch=nb_epoch,
        verbose=1, validation_data=(X_test, Y_test))
  
  score = model0.evaluate(X_test, Y_test, verbose=0)
  
  print('Test score:', score[0])
  print('Test accuracy:', score[1])
  </code></pre>
  
  <p>This runs well and I get ~90% accuracy. I then perform the following command to get a summary of my network's structure by doing <code>print(model0.summary())</code>. This outputs the following:</p>
  
  <pre><code>Layer (type)         Output Shape   Param #     Connected to                     
  =====================================================================
  flatten_1 (Flatten)   (None, 784)     0           flatten_input_1[0][0]            
  dense_1 (Dense)     (None, 10)       7850        flatten_1[0][0]                  
  activation_1        (None, 10)          0           dense_1[0][0]                    
  ======================================================================
  Total params: 7850
  </code></pre>
  
  <p>I don't understand how they get to 7850 total params and what that actually means?</p>