Hey,
I have a working prototype of an multi layer perceptron implementation
working in Flink.
I made every possible effort to utilize existing code when possible.
In the process of doing this there were some hacks I want/need, and think
this should be broken up into multiple PRs and possible abs
Hi all,
I'm curious how long the tests are expected to take for cascading-flink.
I know that https://github.com/dataArtisans/cascading-flink recommends running
mvn clean install with -DskipTests, but I was going to try updating to flink
1.0.0 (currently using 0.10.0) and cascading 3.1.0-wip-56
Hey All,
As a follow up to my earlier post on things to do for Flink ML, here is a
technically working, though certainly not PR ready branch for neural
networks. Meant as a visual aid to starting a conversation on road-map to
some need updates.
https://github.com/apache/flink/compare/master...raw
Thanks Chiwan.
I think this example still creates a lazy-evaluated plan. And if i need to
collect statistics to front end (and use it in subsequent iteration
evaluation) as my example with computing column-wise averages suggests?
problem generally is, what if I need to eagerly evaluate the statis
