+1 for either "Apache SystemDS - A open-source ML system for the
end-to-end data science life cycle" or "Apache SystemDS - A declarative
ML system for the end-to-end data science life cycle", although I lean
more towards the second, because, as Mark stated, open-source can be
inferred.
I dislike the combination though, since the terms are not referring to
the same aspect.
Regards,
Kevin
On 5/22/21 4:59 AM, Janardhan wrote:
We can also consider, "Apache SystemDS - A open-source/declarative ML
system for the end-to-end
data science life cycle" since the word "life cycle" seems redundant.
Still, I am ok with "Apache SystemDS - A open-source ML system for the
end-to-end
data science life cycle".
Thank you,
Janardhan
On Sat, May 22, 2021 at 4:40 AM Mark Dokter <mdok...@know-center.at> wrote:
Thank you Janardhan, for pointing out the issue that this is
inconsistent in some places. Imho consistency in this regard is a good
thing. Staying with well established terms and not following the trend
du jour is also a good thing.
My vote goes to the already often proposed one (see below). But I am
also not pedantic about *minor* variations like machine learning/ML or
open source/declarative. Where in the latter I slightly lean towards
declarative since open source is kinda obvious if that sentence sands
right below the source on our Github page.
jm2c,
Mark
On 5/19/21 6:44 PM, Shafaq Siddiqi wrote:
+1 for "Apache SystemDS - An open-source ML system for the end-to-end
data science lifecycle" but it would be nice to have "declarative"
somewhere to bring DML and ease of programming into reference.
Shafaq Siddiqi
On 5/19/2021 2:58 PM, Matthias Boehm wrote:
+1 for : "Apache SystemDS - An open source ML system for the end-to-end
data science lifecycle"
