Very cool! I look forward to testing this out. Cheers, Kevin
On Tue, Sep 20, 2016 at 11:31 AM, Deniz Yuret <denizyu...@gmail.com> wrote: > It has been a year and a half since I wrote the first version of this post > <https://groups.google.com/d/topic/julia-users/rSgtUpcYPbE/discussion> > and it is time for an update, just in time with the Julia 0.5.0 release! > > Knet <https://github.com/denizyuret/Knet.jl> (pronounced “kay-net”) is > the Koç University deep learning framework implemented in Julia. The latest > version (0.8.0) is finally registered as an official Julia package. Unlike > gradient generating compilers like Theano and TensorFlow which force users > into a restricted mini-language, Knet allows the definition and training of > machine learning models using the full power and expressivity of Julia. > Models are defined by describing only the forward calculation in plain > Julia using helper functions, loops, conditionals, recursion, closures, > tuples and dictionaries, array indexing and concatenation and almost > everything else Julia offers. High performance is achieved by combining > automatic differentiation of most of Julia with efficient GPU kernels and > memory management. The computations can be performed on the GPU by simply > using KnetArray instead of Array for parameters and data. To find out more > and see some examples check out the README > <https://github.com/denizyuret/Knet.jl/blob/master/README.rst>. > > best, > deniz > >
