As deep learning frameworks converge, automation possibilities unfold - SiliconANGLE

From a developer's standpoint, deep learning is usually a hands-on exercise conducted within a particular modeling framework. Typically, a developer has needed to adapt their own manual coding style to interfaces provided by a specific framework, such as TensorFlow, Apache MXNet, Microsoft Cognitive Toolkit (CNTK), Caffe, Caffe2, Torch and Keras.