There were some issues with the gradient_descent method which have now been solved; thanks to Sam Lendel https://github.com/lendle for pointing them out.
On Wednesday, July 23, 2014 8:15:56 PM UTC+12, Alireza Nejati wrote: > > 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. > > >
