For about two weeks now, Zac Cranko, Pasquale Minervini, and I (Alireza Nejati a.k.a. anj1) have been working on a new package for neural networks in julia: NeuralNets.jl <https://github.com/anj1/NeuralNets.jl>.
The goal is to create a clean, modular implementation of neural networks that can easily be extended, while keeping it fast. This would not be possible in a lot of other languages but it's been pretty straightforward in julia so far. Currently we support a whole bunch of training methods including Levenberg-Marquardt, gradient descent with momentum, and Adagrad. We have not yet released a numbered release, so a lot of things are still in their preliminary stages. Especially, the documentation is incomplete in parts (but you can find working examples in the examples directory). Any and all feedback welcome.
