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 <ag...@protonmail.com.invalid>:
>
> 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 cluster cache "myName", with
> Label column "MyLable".
>
> I want to run from notebook UI imputer and knn using python API. Export
> results to file storage as an example.
>
> In my opinion, the ability to create such a simple workflow should be our
> goal for the first time.
>
> Thank You!
>
> Best regards,
> Andrei Gavrilov.
>
> Sent with ProtonMail Secure Email.
>
> ‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐
> On Wednesday, March 4, 2020 10:49 PM, kencottrell <
> ken.cottr...@gridgain.com> wrote:
>
> > 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 dataset, already inside this cluster cache "myName", with
> > Label column "MyLable" , take N samples tell me which appear to be
> numeric,
> > unique id, and categorical values?
> >
> > 2. based on N samples, , please run some analysis and tell me the top 5
> > feature columns in terms of predictive value using algorithm =
> RandonForest
> >
> > 3. do a batch run, sample size = N, using these preprocessing steps list
> > {impute, scale, etc} and algorithms (knn, Decision Tree, etc} and
> give me a
> > report of accuracies obtain with each.
> >
> > In other words, we have a simple sample in the Tutorial demo where
> these
> > all run and then we compare outputs - why not automate these with a
> Python
> > Notebook UI of some sort?
> >
> > --
> > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/
> >
>
>
>
