Skip to content

Show HN: LambdaNet – A functional neural network library written in Haskell

github.com/jbarrow
56 pointsjbarrow7 comments
On HN

Comments

Thanks for sharing this. I've been interested in Haskell for a while and I hadn't really started writing any actual programs until very recently[1]. I also wanted to learn about neural networks, and reading your source code was quite pleasant. It looks really interesting, congratulations.

[1] I wrote a toy IRC bot for a channel I have with some friends. It's quite primitive. https://github.com/jdiez17/HaskellHawk

This looks really cool. Are there any papers that describe neural networks that function in a manner similar to how this library works?

There are a really great soup to nuts explanation of implementing neural nets in Haskell in issue 21 of the monad reader http://themonadreader.files.wordpress.com/2013/03/issue214.p...

off-topic question: is it possible to speed up a neuron network software using a gpu or specialized hardware running openCL ? what about using supercomputers ?

Actually, that's exactly how they speed up neural networks, especially deep neural networks. Andrew Ng showed that they could run the Google Brain on COTS GPUs for about $21,000 [1].

You can experiment with this yourself using a package like Theano (Python) [2] or Caffe (C++) [3].

[1] http://cs.stanford.edu/people/ang/?news=stanford-team-develo... [2] http://deeplearning.net/software/theano/ [3] http://caffe.berkeleyvision.org

Looks very nice! May I ask how fast it is?

It's reasonably fast, as it uses HMatrix for linear algebra -- HMatrix relies on BLAS rather than native Haskell for all the matrix and vector math.

AboutSource Built by g1lg1l

Hackerly is an independent reader for Hacker News, built on the public HN API. Not affiliated with Y Combinator.