TensorFlow, Keras, Theano: Which to Use - DZone AI

So over the past few months, I've been spending a significant amount of time working with TensorFlow and Keras (with TensorFlow under Keras), and I've been running into the question of when I should use which toolset. For those of you who haven't worked with Keras yet, it's a Python library designed for easy neural network assembly that comes with a large number of prepackaged network types, ranging from convolutional networks in two- and three- dimensional flavors, to long- and short-term networks, to more general recurrent networks. Building networks using Keras is straight-forward -- though determining exactly what network to build isn't. The semantics Keras uses in its API design are very layer-oriented, making network assembly relatively intuitive. TensorFlow, on the other hand, is arguably more powerful -- but doesn't have all the prepackaged networks.