Hello Igniters,
I want to make up some overview of all features and major improvement of ML module for this release. So let me start from the one of our main feature for this release: *TensorFlow integration* <https://issues.apache.org/jira/browse/IGNITE-8670> This integration allows us to use Apache Ignite as a data source for TensorFlow. Also, this integration will allow creating and maintaining TensorFlow clusters over Apache Ignite and submit TF jobs to those clusters. More details in the related umbrella ticket. Also, for this release we have some new algorithms: * Random forest <https://issues.apache.org/jira/browse/IGNITE-8840> * Gradient boosted trees <https://issues.apache.org/jira/browse/IGNITE-7149> * Logistic regression[binary <https://issues.apache.org/jira/browse/IGNITE-8403>][multi-class <https://issues.apache.org/jira/browse/IGNITE-8511>] * ANN <https://issues.apache.org/jira/browse/IGNITE-9261> New features related with data preprocessing: * Pipeline <https://issues.apache.org/jira/browse/IGNITE-9158> * L1,L2 normalization <https://issues.apache.org/jira/browse/IGNITE-8663> * Data filtering for new datasets <https://issues.apache.org/jira/browse/IGNITE-8666> * Encoding categorical features [OneHotEncoder <https://issues.apache.org/jira/browse/IGNITE-8680>][OneOfKEncoder <https://issues.apache.org/jira/browse/IGNITE-8664>] * Imputer and Binarizer <https://issues.apache.org/jira/browse/IGNITE-8567> * MaxAbsScaler <https://issues.apache.org/jira/browse/IGNITE-9285> * Dataset splitting <https://issues.apache.org/jira/browse/IGNITE-8667> New features for a model validation: * Model estimator <https://issues.apache.org/jira/browse/IGNITE-8669> * k-fold cross-validation <https://issues.apache.org/jira/browse/IGNITE-8668> * Param grid for tuning hyper-parameters in cross-validation <https://issues.apache.org/jira/browse/IGNITE-8924> Other features and improvements: * Model updating <https://issues.apache.org/jira/browse/IGNITE-9387> * ML tutorial <https://issues.apache.org/jira/browse/IGNITE-8741> * Optional indexing for decision trees <https://issues.apache.org/jira/browse/IGNITE-9064> * Learning context for trainers(local parallelizing and logging of training process) <https://issues.apache.org/jira/browse/IGNITE-8981> * Unification of API for feature extractor <https://issues.apache.org/jira/browse/IGNITE-8907> * Several tickets for removing old unused classes and improvements for code coverage and examples [1 <https://issues.apache.org/jira/browse/IGNITE-9124> ][2 <https://issues.apache.org/jira/browse/IGNITE-9297>][3 <https://issues.apache.org/jira/browse/IGNITE-9146>][4 <https://issues.apache.org/jira/browse/IGNITE-9316>][5 <https://issues.apache.org/jira/browse/IGNITE-9348>][6 <https://issues.apache.org/jira/browse/IGNITE-8450>] Sincerely, Yuriy Babak |
Enormous and outstanding addition!
Yuriy, I've talked to Akmal and he is happy to help with the documentation. Please start documenting everything and reach out Akmal directly. -- Denis On Wed, Sep 26, 2018 at 10:31 AM Юрий Бабак <[hidden email]> wrote: > Hello Igniters, > > I want to make up some overview of all features and major improvement of ML > module for this release. > > So let me start from the one of our main feature for this release: > > *TensorFlow integration* < > https://issues.apache.org/jira/browse/IGNITE-8670> > > This integration allows us to use Apache Ignite as a data source for > TensorFlow. Also, this integration will allow creating and maintaining > TensorFlow clusters over Apache Ignite and submit TF jobs to those > clusters. More details in the related umbrella ticket. > > Also, for this release we have some new algorithms: > > * Random forest <https://issues.apache.org/jira/browse/IGNITE-8840> > * Gradient boosted trees < > https://issues.apache.org/jira/browse/IGNITE-7149> > * Logistic regression[binary > <https://issues.apache.org/jira/browse/IGNITE-8403>][multi-class > <https://issues.apache.org/jira/browse/IGNITE-8511>] > * ANN <https://issues.apache.org/jira/browse/IGNITE-9261> > > New features related with data preprocessing: > > * Pipeline <https://issues.apache.org/jira/browse/IGNITE-9158> > * L1,L2 normalization <https://issues.apache.org/jira/browse/IGNITE-8663> > * Data filtering for new datasets > <https://issues.apache.org/jira/browse/IGNITE-8666> > * Encoding categorical features [OneHotEncoder > <https://issues.apache.org/jira/browse/IGNITE-8680>][OneOfKEncoder > <https://issues.apache.org/jira/browse/IGNITE-8664>] > * Imputer and Binarizer <https://issues.apache.org/jira/browse/IGNITE-8567 > > > * MaxAbsScaler <https://issues.apache.org/jira/browse/IGNITE-9285> > * Dataset splitting <https://issues.apache.org/jira/browse/IGNITE-8667> > > New features for a model validation: > > * Model estimator <https://issues.apache.org/jira/browse/IGNITE-8669> > * k-fold cross-validation > <https://issues.apache.org/jira/browse/IGNITE-8668> > * Param grid for tuning hyper-parameters in cross-validation > <https://issues.apache.org/jira/browse/IGNITE-8924> > > Other features and improvements: > > * Model updating <https://issues.apache.org/jira/browse/IGNITE-9387> > * ML tutorial <https://issues.apache.org/jira/browse/IGNITE-8741> > * Optional indexing for decision trees > <https://issues.apache.org/jira/browse/IGNITE-9064> > * Learning context for trainers(local parallelizing and logging of training > process) <https://issues.apache.org/jira/browse/IGNITE-8981> > * Unification of API for feature extractor > <https://issues.apache.org/jira/browse/IGNITE-8907> > * Several tickets for removing old unused classes and improvements for code > coverage and examples [1 < > https://issues.apache.org/jira/browse/IGNITE-9124> > ][2 <https://issues.apache.org/jira/browse/IGNITE-9297>][3 > <https://issues.apache.org/jira/browse/IGNITE-9146>][4 > <https://issues.apache.org/jira/browse/IGNITE-9316>][5 > <https://issues.apache.org/jira/browse/IGNITE-9348>][6 > <https://issues.apache.org/jira/browse/IGNITE-8450>] > > Sincerely, > Yuriy Babak > |
In reply to this post by Yuriy Babak
Great stuff! Would be nice to see a series of blogs outlining Ignite ML
capabilities.This would give us a better momentum. D. On Wed, Sep 26, 2018 at 10:31 AM Юрий Бабак <[hidden email]> wrote: > Hello Igniters, > > I want to make up some overview of all features and major improvement of ML > module for this release. > > So let me start from the one of our main feature for this release: > > *TensorFlow integration* < > https://issues.apache.org/jira/browse/IGNITE-8670> > > This integration allows us to use Apache Ignite as a data source for > TensorFlow. Also, this integration will allow creating and maintaining > TensorFlow clusters over Apache Ignite and submit TF jobs to those > clusters. More details in the related umbrella ticket. > > Also, for this release we have some new algorithms: > > * Random forest <https://issues.apache.org/jira/browse/IGNITE-8840> > * Gradient boosted trees < > https://issues.apache.org/jira/browse/IGNITE-7149> > * Logistic regression[binary > <https://issues.apache.org/jira/browse/IGNITE-8403>][multi-class > <https://issues.apache.org/jira/browse/IGNITE-8511>] > * ANN <https://issues.apache.org/jira/browse/IGNITE-9261> > > New features related with data preprocessing: > > * Pipeline <https://issues.apache.org/jira/browse/IGNITE-9158> > * L1,L2 normalization <https://issues.apache.org/jira/browse/IGNITE-8663> > * Data filtering for new datasets > <https://issues.apache.org/jira/browse/IGNITE-8666> > * Encoding categorical features [OneHotEncoder > <https://issues.apache.org/jira/browse/IGNITE-8680>][OneOfKEncoder > <https://issues.apache.org/jira/browse/IGNITE-8664>] > * Imputer and Binarizer <https://issues.apache.org/jira/browse/IGNITE-8567 > > > * MaxAbsScaler <https://issues.apache.org/jira/browse/IGNITE-9285> > * Dataset splitting <https://issues.apache.org/jira/browse/IGNITE-8667> > > New features for a model validation: > > * Model estimator <https://issues.apache.org/jira/browse/IGNITE-8669> > * k-fold cross-validation > <https://issues.apache.org/jira/browse/IGNITE-8668> > * Param grid for tuning hyper-parameters in cross-validation > <https://issues.apache.org/jira/browse/IGNITE-8924> > > Other features and improvements: > > * Model updating <https://issues.apache.org/jira/browse/IGNITE-9387> > * ML tutorial <https://issues.apache.org/jira/browse/IGNITE-8741> > * Optional indexing for decision trees > <https://issues.apache.org/jira/browse/IGNITE-9064> > * Learning context for trainers(local parallelizing and logging of training > process) <https://issues.apache.org/jira/browse/IGNITE-8981> > * Unification of API for feature extractor > <https://issues.apache.org/jira/browse/IGNITE-8907> > * Several tickets for removing old unused classes and improvements for code > coverage and examples [1 < > https://issues.apache.org/jira/browse/IGNITE-9124> > ][2 <https://issues.apache.org/jira/browse/IGNITE-9297>][3 > <https://issues.apache.org/jira/browse/IGNITE-9146>][4 > <https://issues.apache.org/jira/browse/IGNITE-9316>][5 > <https://issues.apache.org/jira/browse/IGNITE-9348>][6 > <https://issues.apache.org/jira/browse/IGNITE-8450>] > > Sincerely, > Yuriy Babak > |
In reply to this post by dmagda
Whole documentation for all significant features/improvements was prepared by
different members of ML community and I hope it will be added to readme.io by @ybabak in a few days. -- Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ |
In reply to this post by dsetrakyan
Currently, in release 2.7, the ignite ML has a parity with a Spark ML by ML
algorithms, feature preprocessing and other capabilities. I'm going to talk about that in October on two conferences 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library for Apache Ignite https://yappidays.ru/talks.html#zinovev 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, https://jfuture.by/#talkbyAlexeyZinoviev After my previous event, JUG MSK, the new contributor @Ravil Galeyev joined to our community, hope for new members from Yaroslavl and Minsk soon -- Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ |
Alexey,
Thanks for spreading the word about the ML capabilities! *Prachi*, please help us to add the talks Alexey is going to give to Ignite events page: https://ignite.apache.org/events.html Btw, I gave a presentation about Ignite ML + TensorFlow integration today at IMC Summit in the US. It was perceived really well, was bombarded with many questions after the talk and think we've got some potential users ;) -- Denis On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev <[hidden email]> wrote: > Currently, in release 2.7, the ignite ML has a parity with a Spark ML by ML > algorithms, feature preprocessing and other capabilities. > > I'm going to talk about that in October on two conferences > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library for > Apache Ignite https://yappidays.ru/talks.html#zinovev > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > https://jfuture.by/#talkbyAlexeyZinoviev > > After my previous event, JUG MSK, the new contributor @Ravil Galeyev joined > to our community, hope for new members from Yaroslavl and Minsk soon > > > > -- > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ > |
Denis, Alexey,
thank you for work you do to make Ignite more recognizable. Don't forget to encourage contributors to come not only to ML but to core and to other modules as well :) Sincerely, Dmitriy Pavlov ср, 3 окт. 2018 г. в 6:29, Denis Magda <[hidden email]>: > Alexey, > > Thanks for spreading the word about the ML capabilities! *Prachi*, please > help us to add the talks Alexey is going to give to Ignite events page: > https://ignite.apache.org/events.html > > Btw, I gave a presentation about Ignite ML + TensorFlow integration today > at IMC Summit in the US. It was perceived really well, was bombarded with > many questions after the talk and think we've got some potential users ;) > > -- > Denis > > On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev <[hidden email]> > wrote: > > > Currently, in release 2.7, the ignite ML has a parity with a Spark ML by > ML > > algorithms, feature preprocessing and other capabilities. > > > > I'm going to talk about that in October on two conferences > > > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library for > > Apache Ignite https://yappidays.ru/talks.html#zinovev > > > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > > https://jfuture.by/#talkbyAlexeyZinoviev > > > > After my previous event, JUG MSK, the new contributor @Ravil Galeyev > joined > > to our community, hope for new members from Yaroslavl and Minsk soon > > > > > > > > -- > > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ > > > |
In reply to this post by dmagda
It will be great if you can share your presentation/video after this summit
in dev-list. Did you use a TensorFlow integration stand in your presentation? Good news about potential users, it will be great to contact with somebody who are going to use ML in production to discuss possible cases ср, 3 окт. 2018 г. в 6:29, Denis Magda <[hidden email]>: > Alexey, > > Thanks for spreading the word about the ML capabilities! *Prachi*, please > help us to add the talks Alexey is going to give to Ignite events page: > https://ignite.apache.org/events.html > > Btw, I gave a presentation about Ignite ML + TensorFlow integration today > at IMC Summit in the US. It was perceived really well, was bombarded with > many questions after the talk and think we've got some potential users ;) > > -- > Denis > > On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev <[hidden email]> > wrote: > > > Currently, in release 2.7, the ignite ML has a parity with a Spark ML by > ML > > algorithms, feature preprocessing and other capabilities. > > > > I'm going to talk about that in October on two conferences > > > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library for > > Apache Ignite https://yappidays.ru/talks.html#zinovev > > > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > > https://jfuture.by/#talkbyAlexeyZinoviev > > > > After my previous event, JUG MSK, the new contributor @Ravil Galeyev > joined > > to our community, hope for new members from Yaroslavl and Minsk soon > > > > > > > > -- > > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ > > > |
In reply to this post by Dmitriy Pavlov
I will try, Dmitriy, of course, to encourage contributors to other modules.
But from my side the main problem is not enough screencasts/tutorials/examples to run something interesting about other modules. Great to see something tasty in examples folder in 2.7 release. If you need my help with examples, I could try to help to other modules. ср, 3 окт. 2018 г. в 11:30, Dmitriy Pavlov <[hidden email]>: > Denis, Alexey, > > thank you for work you do to make Ignite more recognizable. > > Don't forget to encourage contributors to come not only to ML but to core > and to other modules as well :) > > Sincerely, > Dmitriy Pavlov > > ср, 3 окт. 2018 г. в 6:29, Denis Magda <[hidden email]>: > > > Alexey, > > > > Thanks for spreading the word about the ML capabilities! *Prachi*, please > > help us to add the talks Alexey is going to give to Ignite events page: > > https://ignite.apache.org/events.html > > > > Btw, I gave a presentation about Ignite ML + TensorFlow integration today > > at IMC Summit in the US. It was perceived really well, was bombarded with > > many questions after the talk and think we've got some potential users ;) > > > > -- > > Denis > > > > On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev <[hidden email]> > > wrote: > > > > > Currently, in release 2.7, the ignite ML has a parity with a Spark ML > by > > ML > > > algorithms, feature preprocessing and other capabilities. > > > > > > I'm going to talk about that in October on two conferences > > > > > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library for > > > Apache Ignite https://yappidays.ru/talks.html#zinovev > > > > > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > > > https://jfuture.by/#talkbyAlexeyZinoviev > > > > > > After my previous event, JUG MSK, the new contributor @Ravil Galeyev > > joined > > > to our community, hope for new members from Yaroslavl and Minsk soon > > > > > > > > > > > > -- > > > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ > > > > > > |
In reply to this post by Alexey Zinoviev
>
> It will be great if you can share your presentation/video after this summit > in dev-list. The video should be posted on this page in a couple of weeks: https://www.imcsummit.org/2018/us/session/scalable-machine-and-deep-learning-apache-ignite Did you use a TensorFlow integration stand in your presentation? Yes, could present and announce it. Yuri and Andrey helped me with the demo but, unfortunately, could show it because the organizers failed to set up my laptop and projector. -- Denis On Wed, Oct 3, 2018 at 2:35 AM Alexey Zinoviev <[hidden email]> wrote: > It will be great if you can share your presentation/video after this summit > in dev-list. > Did you use a TensorFlow integration stand in your presentation? > > Good news about potential users, it will be great to contact with somebody > who are going to use ML in production to discuss possible cases > > ср, 3 окт. 2018 г. в 6:29, Denis Magda <[hidden email]>: > > > Alexey, > > > > Thanks for spreading the word about the ML capabilities! *Prachi*, please > > help us to add the talks Alexey is going to give to Ignite events page: > > https://ignite.apache.org/events.html > > > > Btw, I gave a presentation about Ignite ML + TensorFlow integration today > > at IMC Summit in the US. It was perceived really well, was bombarded with > > many questions after the talk and think we've got some potential users ;) > > > > -- > > Denis > > > > On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev <[hidden email]> > > wrote: > > > > > Currently, in release 2.7, the ignite ML has a parity with a Spark ML > by > > ML > > > algorithms, feature preprocessing and other capabilities. > > > > > > I'm going to talk about that in October on two conferences > > > > > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library for > > > Apache Ignite https://yappidays.ru/talks.html#zinovev > > > > > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > > > https://jfuture.by/#talkbyAlexeyZinoviev > > > > > > After my previous event, JUG MSK, the new contributor @Ravil Galeyev > > joined > > > to our community, hope for new members from Yaroslavl and Minsk soon > > > > > > > > > > > > -- > > > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ > > > > > > |
Great, will wait video from summit.
чт, 4 окт. 2018 г. в 0:22, Denis Magda <[hidden email]>: > > > > It will be great if you can share your presentation/video after this > summit > > in dev-list. > > > The video should be posted on this page in a couple of weeks: > > https://www.imcsummit.org/2018/us/session/scalable-machine-and-deep-learning-apache-ignite > > Did you use a TensorFlow integration stand in your presentation? > > > Yes, could present and announce it. Yuri and Andrey helped me with the demo > but, unfortunately, could show it because the organizers failed to set up > my laptop and projector. > > -- > Denis > > On Wed, Oct 3, 2018 at 2:35 AM Alexey Zinoviev <[hidden email]> > wrote: > > > It will be great if you can share your presentation/video after this > summit > > in dev-list. > > Did you use a TensorFlow integration stand in your presentation? > > > > Good news about potential users, it will be great to contact with > somebody > > who are going to use ML in production to discuss possible cases > > > > ср, 3 окт. 2018 г. в 6:29, Denis Magda <[hidden email]>: > > > > > Alexey, > > > > > > Thanks for spreading the word about the ML capabilities! *Prachi*, > please > > > help us to add the talks Alexey is going to give to Ignite events page: > > > https://ignite.apache.org/events.html > > > > > > Btw, I gave a presentation about Ignite ML + TensorFlow integration > today > > > at IMC Summit in the US. It was perceived really well, was bombarded > with > > > many questions after the talk and think we've got some potential users > ;) > > > > > > -- > > > Denis > > > > > > On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev <[hidden email] > > > > > wrote: > > > > > > > Currently, in release 2.7, the ignite ML has a parity with a Spark ML > > by > > > ML > > > > algorithms, feature preprocessing and other capabilities. > > > > > > > > I'm going to talk about that in October on two conferences > > > > > > > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library > for > > > > Apache Ignite https://yappidays.ru/talks.html#zinovev > > > > > > > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > > > > https://jfuture.by/#talkbyAlexeyZinoviev > > > > > > > > After my previous event, JUG MSK, the new contributor @Ravil Galeyev > > > joined > > > > to our community, hope for new members from Yaroslavl and Minsk soon > > > > > > > > > > > > > > > > -- > > > > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ > > > > > > > > > > |
Alexey, what do you think about sending announce of your talks also to user
list? Some of the dev-list subscribers are Ignite contributors, so maybe it will be reasonable to inform users about talks. чт, 4 окт. 2018 г. в 11:41, Alexey Zinoviev <[hidden email]>: > Great, will wait video from summit. > > чт, 4 окт. 2018 г. в 0:22, Denis Magda <[hidden email]>: > > > > > > > It will be great if you can share your presentation/video after this > > summit > > > in dev-list. > > > > > > The video should be posted on this page in a couple of weeks: > > > > > https://www.imcsummit.org/2018/us/session/scalable-machine-and-deep-learning-apache-ignite > > > > Did you use a TensorFlow integration stand in your presentation? > > > > > > Yes, could present and announce it. Yuri and Andrey helped me with the > demo > > but, unfortunately, could show it because the organizers failed to set up > > my laptop and projector. > > > > -- > > Denis > > > > On Wed, Oct 3, 2018 at 2:35 AM Alexey Zinoviev <[hidden email]> > > wrote: > > > > > It will be great if you can share your presentation/video after this > > summit > > > in dev-list. > > > Did you use a TensorFlow integration stand in your presentation? > > > > > > Good news about potential users, it will be great to contact with > > somebody > > > who are going to use ML in production to discuss possible cases > > > > > > ср, 3 окт. 2018 г. в 6:29, Denis Magda <[hidden email]>: > > > > > > > Alexey, > > > > > > > > Thanks for spreading the word about the ML capabilities! *Prachi*, > > please > > > > help us to add the talks Alexey is going to give to Ignite events > page: > > > > https://ignite.apache.org/events.html > > > > > > > > Btw, I gave a presentation about Ignite ML + TensorFlow integration > > today > > > > at IMC Summit in the US. It was perceived really well, was bombarded > > with > > > > many questions after the talk and think we've got some potential > users > > ;) > > > > > > > > -- > > > > Denis > > > > > > > > On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev < > [hidden email] > > > > > > > wrote: > > > > > > > > > Currently, in release 2.7, the ignite ML has a parity with a Spark > ML > > > by > > > > ML > > > > > algorithms, feature preprocessing and other capabilities. > > > > > > > > > > I'm going to talk about that in October on two conferences > > > > > > > > > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning Library > > for > > > > > Apache Ignite https://yappidays.ru/talks.html#zinovev > > > > > > > > > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > > > > > https://jfuture.by/#talkbyAlexeyZinoviev > > > > > > > > > > After my previous event, JUG MSK, the new contributor @Ravil > Galeyev > > > > joined > > > > > to our community, hope for new members from Yaroslavl and Minsk > soon > > > > > > > > > > > > > > > > > > > > -- > > > > > Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ > > > > > > > > > > > > > > > |
Good idea, will do that in the nearest future
чт, 4 окт. 2018 г. в 13:27, Dmitriy Pavlov <[hidden email]>: > Alexey, what do you think about sending announce of your talks also to user > list? > > Some of the dev-list subscribers are Ignite contributors, so maybe it will > be reasonable to inform users about talks. > > чт, 4 окт. 2018 г. в 11:41, Alexey Zinoviev <[hidden email]>: > > > Great, will wait video from summit. > > > > чт, 4 окт. 2018 г. в 0:22, Denis Magda <[hidden email]>: > > > > > > > > > > It will be great if you can share your presentation/video after this > > > summit > > > > in dev-list. > > > > > > > > > The video should be posted on this page in a couple of weeks: > > > > > > > > > https://www.imcsummit.org/2018/us/session/scalable-machine-and-deep-learning-apache-ignite > > > > > > Did you use a TensorFlow integration stand in your presentation? > > > > > > > > > Yes, could present and announce it. Yuri and Andrey helped me with the > > demo > > > but, unfortunately, could show it because the organizers failed to set > up > > > my laptop and projector. > > > > > > -- > > > Denis > > > > > > On Wed, Oct 3, 2018 at 2:35 AM Alexey Zinoviev <[hidden email] > > > > > wrote: > > > > > > > It will be great if you can share your presentation/video after this > > > summit > > > > in dev-list. > > > > Did you use a TensorFlow integration stand in your presentation? > > > > > > > > Good news about potential users, it will be great to contact with > > > somebody > > > > who are going to use ML in production to discuss possible cases > > > > > > > > ср, 3 окт. 2018 г. в 6:29, Denis Magda <[hidden email]>: > > > > > > > > > Alexey, > > > > > > > > > > Thanks for spreading the word about the ML capabilities! *Prachi*, > > > please > > > > > help us to add the talks Alexey is going to give to Ignite events > > page: > > > > > https://ignite.apache.org/events.html > > > > > > > > > > Btw, I gave a presentation about Ignite ML + TensorFlow integration > > > today > > > > > at IMC Summit in the US. It was perceived really well, was > bombarded > > > with > > > > > many questions after the talk and think we've got some potential > > users > > > ;) > > > > > > > > > > -- > > > > > Denis > > > > > > > > > > On Tue, Oct 2, 2018 at 8:54 AM Alexey Zinoviev < > > [hidden email] > > > > > > > > > wrote: > > > > > > > > > > > Currently, in release 2.7, the ignite ML has a parity with a > Spark > > ML > > > > by > > > > > ML > > > > > > algorithms, feature preprocessing and other capabilities. > > > > > > > > > > > > I'm going to talk about that in October on two conferences > > > > > > > > > > > > 1) [Ru] Yaroslavl, Open Source Distributed Machine Learning > Library > > > for > > > > > > Apache Ignite https://yappidays.ru/talks.html#zinovev > > > > > > > > > > > > 2) [En] Minsk, Nuances of Machine Learning with Ignite ML, > > > > > > https://jfuture.by/#talkbyAlexeyZinoviev > > > > > > > > > > > > After my previous event, JUG MSK, the new contributor @Ravil > > Galeyev > > > > > joined > > > > > > to our community, hope for new members from Yaroslavl and Minsk > > soon > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > Sent from: > http://apache-ignite-developers.2346864.n4.nabble.com/ > > > > > > > > > > > > > > > > > > > > > |
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