I am working in the following neural network architecture, I am using keras and TensorFlow as a back-end.
It is composed by the following, embedding of words, then I added a layer of Long Short-Term Memory (LSTM) neural networks, one layer of output and finally. I am using the softmax activation function.
model = Sequential() model.add(Embedding(MAX_NB_WORDS, 64, dropout=0.2)) model.add(LSTM(64, dropout_W=0.2, dropout_U=0.2)) model.add(Dense(8)) model.add(Activation('softmax'))
I have the following question, if I am getting a model through this code, could the final product be called a deep learning model?, I know that this code is very small however there is a lot of computations that the machine is making on the background.