Flux is an experimental machine perception / ANN library for Julia. It's most similar in philosophy to the excellent [Keras](http://keras.io). Like that and other high-level ANN libraries, Flux is designed to make experimenting with novel layer types and architectures really fast, without sacrificing speed.
* Flux's [graph-based DSL](https://github.com/MikeInnes/Flow.jl), which provides optimisations and automatic differentiation (à la Theano), is very tightly integrated with the language. This means nice syntax for your equations (`σ(W*x+b)` anyone?) and no unwieldy `compile` steps.
* The graph DSL directly represents models, as opposed to computations, so custom architectures –and in particular, recurrent models –are easy to express.
* Those fancy features are completely optional. You can implement arbitrary functionality in a Torch-like fashion if you wish, since layers are simply objects that satisfy a small interface (à la Torch).
* Flux is written in [Julia](http://julialang.org), which means there's no "dropping down" to C.It's Julia all the way down, and you can prototype both high-level architectures and high-performance GPU kernels from the same language. This also makes the library itself very easy to understand and extend.
