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From Alexey Zinoviev <zaleslaw....@gmail.com>
Subject Re: H2O integration
Date Thu, 31 Oct 2019 14:41:38 GMT
Thanks, Denis, no, the initial H2O integration is not the same as
TensorFlow integration, it perform the prediction phase (than you have
trained model) nor training as I mentioned "As a result we could predict
something on Ignite data via the model trained in H2O system."

It's the same as XGBost and Spark ML integration, but I hope that we could
extend our integration here and provide something like Ignite data-source
for training in H2O in the future.

чт, 31 окт. 2019 г. в 16:48, Denis Magda <dmagda@apache.org>:

> Hi Alexey,
>
> That’s great to see that our ML and DL capabilities keep growing via
> integrations!
>
> Is it correct to say that H2O uses Ignite as a data source in a way similar
> to what we did for TensorFlow?
>
> Btw, do you have any plans to spread the word about the additions through
> blogging? H2O, Spark ML, XGBoost deserve their own articles.
>
> Denis
>
> On Thursday, October 31, 2019, Alexey Zinoviev <zaleslaw.sin@gmail.com>
> wrote:
>
> > Hi, Igniters,
> >    I happy to announce the new part of Ignite ML functionality.
> >
> > The integration with the popular distributed library H2O
> > https://github.com/h2oai was added.
> > As a result we could predict something on Ignite data via the model
> trained
> > in H2O system.
> >
> > Many thanks to Michal Kurka (https://github.com/michalkurka), waiting
> him
> > on our dev-list, hope that he will help with the backward integration
> from
> > Ignite to H2O system.
> >
> > Remind, that now we have integrations with XGBoost, TensorFlow, Spark ML
> > via SparkMlParser and MLeap integration and waiting for the new
> > integrations with Dl4j or PyTorch for example
> >
> > Sincerely yours,
> >              Alexey Zinoviev
> >
>
>
> --
> -
> Denis
>

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