Keras (https://keras.io) is a high-level deep learning framework that works seamlessly with low-level backends like TensorFlow, Theano or CNTK. In Keras a model is like a sequence of layers where each output is fed into the following computational block until the final layer is reached. The generic structure of a model is:
from keras.models import Sequential
>>> model = Sequential()
>>> model.add(...)
>>> model.add(...)
...
>>> model.add(...)
The class Sequential defines a generic empty model, that already implements all the methods needed to add layers, compile the model according to the underlying framework, to fit and evaluate the model and to predict the output given an input. All the most common layers are already implemented, including:
- Dense, Dropout and Flattening layers
- Convolutional (1D, 2D and 3D) layers...
