On Monday, 27 June 2016 at 18:01:54 UTC, Jack Stouffer wrote:
On Monday, 27 June 2016 at 15:31:07 UTC, Guillaume Piolat wrote:
Well I get the manpower thing, everything we do is quite
labour-intensive. I'm just curious nobody started such an
effort (but there was with DlangScience, gamedev, web...).
D doesn't even have the building blocks in D code. Ndslice and
the upcoming BLAS in D are nessesary steps if we want a
idiomatic D machine learning library. And that's just the
foundational work.
You don't need to match the manpower and stability of the
established solution to make something useful. Perhaps there
could be something distinctive enough to make it attractive?
Unfortunately, academics (who are usually the target audience
for these libraries) are very set in their ways. You'll need
something that surpasses the functionality of the current
solutions and is just as easy to use in order for it to catch
on :/
It should be added that for the development library "mir" where
the upcoming BLAS in D will be hosted, we have plans to integrate
also building blocks for ML. In fact Ilya already pushed an
online LDA algorithm [1].
At the moment we lack the manpower to focus more on this, but any
help is of course appreciated ;-)
See this issue for details:
https://github.com/libmir/mir/issues/166
[1] http://docs.mir.dlang.io/latest/mir_model_lda_hoffman.html
