Dear community -
I'm cancelling the vote due to -1 feedback from Luciano due to RAT
failures.
For details see
https://lists.apache.org/thread.html/51e9ab05edae2089c74a253000a92d5aa5c6406f54e5bd0a0b3c3879@%3Cgeneral.incubator.apache.org%3E
The MXNet community will discuss next steps.
Regards,
Stef
Those are compelling points! There's also another more recent follow-up
from the Julia team: https://julialang.org/blog/2018/12/ml-language-compiler
.
It seems that Julia will likely have it's place in ML regardless of how
other tools progress; the latest offerings from Julia/Flux are really
compe
Wanted to chime in as well.
I have reviewed the design shared in the mail offline with Ankit, Lai and
Naveen (we work in the same team in Amazon).
I think it does a good job at simplifying many low-complexity training use
cases, which can make MXNet/Gluon even more friendly to so-called "deep
lear
