DNNGraph – A deep neural network model generation DSL in Haskell

by psoto • 11 years ago

57 8 11 years ago

soup102• 11 years ago

Ok, how does this compare to machine learning tools in packages like R and the other api's out there.

shabadoop2• 11 years ago

I think the idea is it sets up Neural Networks that are then run in Torch, with some nice diagram generating tools. I don't know if that's something people will actually use, but it looks like a pretty concise way to generate a pretty complicated Neural Network, which could be a worthwhile idea considering how complex the more advanced ones are.

soup102• 11 years ago

Ah I see. I guess Haskell wrapper for Torch with diagrams doesn't sound as impressive.

ajtulloch2• 11 years ago

(Author here) - the interactive workflow at http://nbviewer.ipython.org/gist/anonymous/115cc761db1a0d290... might be interesting, FWIW.

sinwave• 11 years ago

This is really cool work. There is a lackluster theano feature which allows you to print a flowchart figure for the "computation graph" corresponding to the symbolic representation of your model.

@ajtulloch's library provides what I imagined the feature would be at first glance - a comprehensible, elegant graphical representation of your NN model. And on top of that, all in Haskell, with Haskell DSL for running torch - so cool.

ajtulloch2• 11 years ago

Hi folks, author here - thanks for the interest in the project. It's literally ~1,000 lines of Haskell that I wrote a couple of weekends ago (and don't use at all in production), but LMK if you find it useful in any way (or have feature requests). Thanks!

DNNGraph – A deep neural network model generation DSL in Haskell

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