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Cutting edge data science projects.

Deep Learning frameworks such as Theano, Caffe, TensorFlow, Torch, MXNet and CNTK are the work horses of Deep Learning work. These frameworks as well as the GPU (predominantly Nvidia) are the what enables the rapid growth of Deep Learning. It was refreshing to hear Nando de Freitas acknowledge their work in the recently concluded NIPS 2016 conference. Infrastructure does not get enough of the recognition it deserves in the academic community. Yet, programmers toil on to continually tweak and improve their frameworks.

Recently, a new framework was revealed by Facebook and a bunch of other partners (Twitter * NVIDIA * SalesForce * ParisTech * CMU * Digital Reasoning * INRIA * ENS). PyTorch came out of stealth development. PyTorch is an improvement over the popular Torch framework (Torch was a favorite at DeepMind until TensorFlow came along). The obvious change is the support of Python over the less often used Lua language. Almost all of the more popular frameworks use Python, so it is a relief that Torch has finally joined the club.