Development systems for deep learning, such as Theano, Torch, TensorFlow, or MXNet, are easyto-use tools for creating complex neural network models. Since gradient computations are automatically baked in, and execution is mapped to high performance hardware, these models can be trained endto-end on large amounts of data. However, it is currently not easy to implement many basic machine learning...
