This is, frankly, a naive way to rank deep learning projects, because Github stars are cheap. Francois Chollet, the creator of Keras, comes out with a monthly ranking that takes other factors into account, such as forks, contributors and issues, all stronger signs of community and users. Here's his July update:
Most of these frameworks are Python-oriented: Keras, Theano, Caffe, TF, neon, Mxnet, etc. The space is saturated. If you look at deep-learning projects by language, then Torch stands out -- it has a Lua API. And Deeplearning4j is the most widely used in Java and Scala. You don't have to crowbar it into a Spark integration, like you do with TensforFlow. http://deeplearning4j.org/
MXnet is not talked about a lot, but it's growing fast. It was heavily used by Graphlab/Turi, recently bought by Apple, so the question is what will happen with it now.
https://twitter.com/fchollet/status/753980621823750145
Most of these frameworks are Python-oriented: Keras, Theano, Caffe, TF, neon, Mxnet, etc. The space is saturated. If you look at deep-learning projects by language, then Torch stands out -- it has a Lua API. And Deeplearning4j is the most widely used in Java and Scala. You don't have to crowbar it into a Spark integration, like you do with TensforFlow. http://deeplearning4j.org/
MXnet is not talked about a lot, but it's growing fast. It was heavily used by Graphlab/Turi, recently bought by Apple, so the question is what will happen with it now.