Ken, thanks for the feedback, part of the ideas looks like the good
candidates for the next release for the Java API.
We should understand, that Python API could only wrap Java API.
We approach with wrapping via P4j library as in mentioned repository could
be used, it is a common approach, it is
Folks,
Does it make sense to take an approach of Python ML implementation
available for GridGain in a beta mode? (where Python APIs wrap around Java
ML library)
https://www.gridgain.com/docs/latest/developers-guide/python-ml/using-python-ml
-
Denis
On Thu, Mar 5, 2020 at 6:50 AM Alexey Zinoviev
Alexey, Andrei,
Here are some thoughts on what would be good to have in Python-Ignite ML
notebook:
- some way to pick an optional sample size (out of a very big cache
size) that gets communicated and set aside to all partitions
- some way to count number of unique values for a category (
Agree with simple case, I think we could start from the simple poc for the
Python for ML in the next release
чт, 5 мар. 2020 г., 17:05 AG :
>
> Thanks, for the reply!
>
> It looks like a high-level API similar to Sklearn pipelines.
> In my opinion, for the first steps easier to add simple assess
Agree with simple case, I think we could start from the simple poc for the
Python for ML in the next release
чт, 5 мар. 2020 г., 17:05 AG :
>
> Thanks, for the reply!
>
> It looks like a high-level API similar to Sklearn pipelines.
> In my opinion, for the first steps easier to add simple assess
Thanks, for the reply!
It looks like a high-level API similar to Sklearn pipelines.
In my opinion, for the first steps easier to add simple assess to gain the
ability to run a simple model or simple preprocessor from python.
According to your example:
Here is raw dataset, already inside this c
Andrei,
I am also working with Apache Ignite ML and am interested in providing
wrappers for Ignite ML API, but am wondering if instead of simply recreating
the low level Java API for ML inside Python, how about creating some higher
level services "Auto ML" workflow ? For example:
1. here is raw
Dear Community,
I was very inspired in Ignite ML and I wanted to try it with Python.
Particularly I was interested in compares Ignite ML VS Spark ML
However, I came across the fact that pyignite component allows only to
perform basic cache operations through the API and it has nothing to do w
