[Haskell-cafe] GSoC and Machine learning
alp at mestan.fr
Wed Mar 31 06:19:50 EDT 2010
Note that, if any student is interested, the Haskell Neural Network library
 is being rewritten from scratch. We (Thomas Bereknyi and I) are
discussing many core data structure alternatives, with some suggestions from
Edward Kmett. There may even be some room for a rewrite or update of fgl,
possibly with an alternative conception, to fit well HNN. I am definitely
not sure if this is worth a GSoC and if the community would benefit that
much from such a work, but it's there.
On Tue, Mar 30, 2010 at 1:55 PM, Grzegorz C <pitekus at gmail.com> wrote:
> Ketil Malde-5 wrote:
> > Once upon a time, I proposed a GSoC project for a machine learning
> > library.
> > I still get some email from prospective students about this, whom I
> > discourage as best I can by saying I don't have the time or interest to
> > pursue it, and that chances aren't so great since you guys tend to
> > prefer language-related stuff instead of application-related stuff.
> > But if anybody disagrees with my sentiments and is willing to mentor
> > this, there are some smart students looking for an opportunity. I'd be
> > happy to forward any requests.
> I don't know whether this is a good idea for a GSoC project, but I would
> certainly welcome such a library. I am using Haskell a bit for statistical
> NLP: in my experience currently Haskell is excellent for the components
> which deal with data preprocessing and feature extraction, but when it
> to implementing the core training algorithms and running them on large data
> sets, it's easy to get very poor performance and/or unexpected stack
> overflows. So if a library could provide some well-tuned and tested
> blocks for implementing the performance critical parts of machine learning
> algorithms, it would improve the coding experience in a major way.
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