Re: Machine Learning on Flink - Next steps

e Flink however in absence of good > ML suppoer we may have to move back to Spark. > > > > -- > View this message in context: > http://apache-flink-mailing-list-archive.1008284.n3.nabble.com/Machine-Learning-on-Flink-Next-steps-tp16334p16874.html > Sent from the Apache Flink Mailing List archive. mailing list archive at > Nabble.com.

Re: Machine Learning on Flink - Next steps

e Flink however in absence of good > ML suppoer we may have to move back to Spark. > > > > -- > View this message in context: > http://apache-flink-mailing-list-archive.1008284.n3.nabble.com/Machine-Learning-on-Flink-Next-steps-tp16334p16874.html > Sent from the Apache Flink Mailing List archive. mailing list archive at > Nabble.com.

Re: Machine Learning on Flink - Next steps

ttp://apache-flink-mailing-list-archive.1008284.n3.nabble.com/Machine-Learning-on-Flink-Next-steps-tp16334p16874.html Sent from the Apache Flink Mailing List archive. mailing list archive at Nabble.com.

Re: Machine Learning on Flink - Next steps

Hi all, I added a document for the model serving effort. It is in draft mode feel free to drop a comment. Btw I have contacted Eron Wright and he is willing to help to that direction, I will keep all

Re: Machine Learning on Flink - Next steps

Hello all, I've updated the original Gdoc [1] to include a table with coordinators and people interested in contributing to the specific projects. With this latest additions we have many people willing to contribute to the online learning library, and 2 people who have shown interested to at least

Re: Machine Learning on Flink - Next steps

Hi all, @Theodore: +1 for the CTR use-case. Thanks for the suggestion! @Katherin: +1 for reflecting the choices made here and contributor commitment in Gdoc. @Tao, @Ventura: It's great to here you have been working on ML on Flink :) I hope we can all aggregate our efforts somehow. It would be b

Re: Machine Learning on Flink - Next steps

Hello Theodore, I could lead the effort for the model serving thing, I think I have the cycles for it. I would also contact Enron and see if he wants to help in that direction. Best, Stavros On Sun, Mar 19, 2017 at 3:43 PM, Theodore Vasiloudis < theodoros.vasilou...@gmail.com> wrote: > Hello St

Re: Machine Learning on Flink - Next steps

Hello everyone, Here at DFKI, we are currently working on project that involves developing open-source Online Machine Learning algorithms on top of Flink. So far, we have simple moments, sampling (e.g.: simple reservoir sampling) and sketches (e.g., Frequent Directions) built on top of scikit-like

Re: Machine Learning on Flink - Next steps

Hi All, Sorry for joining this discussion late. My graduation thesis is about online learning system. I would build it on flink in the next three months. I'd like to contribute on: - Online learning On Mon, Mar 20, 2017 at 6:51 PM Katherin Eri wrote: Hello, Theodore Could you please move

Re: Machine Learning on Flink - Next steps

Hello, Theodore Could you please move vectors of development and their prioritized positions from *## Executive summary* to the google doc? Could you please also create some table in google doc, that is representing the selected directions and persons, who would like to drive or participate in

Re: Machine Learning on Flink - Next steps

Hello Stavros, The way I thought we'd do it is that each shepherd would be responsible for organizing the project: that includes setting up a Google doc, sending an email to the dev list to inform the wider community, and if possible, personally contacting the people who expressed interest in the

Re: Machine Learning on Flink - Next steps

Hi all... I agree about the tensorflow integration it seems to be important from what I hear. Should we sign up somewhere for the working groups (gdcos)? I would like to start helping with the model serving feature. Best Regards, Stavros On Fri, Mar 17, 2017 at 10:34 PM, Gábor Hermann wrote: >

Re: Machine Learning on Flink - Next steps

Hi Chen, Thanks for the input! :) There is already a project [1] for using TensorFlow models in Flink, and Theodore has suggested to contact the author, Eron Wright for the model serving direction. [1] http://sf.flink-forward.org/kb_sessions/introducing-flink-tensorflow/ Cheers, Gabor On

Re: Machine Learning on Flink - Next steps

scussion > >>> > >>>> up. The general position was that it would be best to have an > >>>>> > >>>> incremental > >>> > >>>> build and keep everything in the same repo. If this is not possible > >>&g

Re: Machine Learning on Flink - Next steps

least mirror the discussions happening in the >>>>> google doc back on the mailing list or ideally conduct the discussions >>>>> directly on the mailing list. That's at least what the ASF encourages. >>>>> >>>>> Cheers, >>>&g

Re: Machine Learning on Flink - Next steps

ues than batch issues because we will have more support on that by the Flink community. Thanks and have a nice weekend, Roberto On 3 March 2017 at 20:20, amir bahmanyari wrote: Great points to start:- Online learning - Offline learning with the streaming API Thanks + have a great

Re: Machine Learning on Flink - Next steps

into issues. E.g. I could > > only > > > > mark the end of input with some hacks, because this is not needed at > a > > > > streaming job consuming input forever. AFAIK, this would be resolved > by > > > > side inputs [1]. > > > > > > > > @T

Re: Machine Learning on Flink - Next steps

> > > > [1] https://cwiki.apache.org/confluence/display/FLINK/FLIP-17+ > > > Side+Inputs+for+DataStream+API > > > [2] https://github.com/project-flink > > > > > > > > > On 2017-03-04 08:44, Roberto Bentivoglio wrote: > > > >

Re: Machine Learning on Flink - Next steps

d > >> development > >> phases it's really interesting. > >> > >> I totally agree with Katherin, we need offline learning, but my opinion > is > >> that it will be more straightforward to fix the streaming issues than > >> batch > >> is

Re: Machine Learning on Flink - Next steps

>> batch >> issues because we will have more support on that by the Flink community. >> >> Thanks and have a nice weekend, >> Roberto >> >> On 3 March 2017 at 20:20, amir bahmanyari >> wrote: >> >> Great points to start:- Online learning &g

Re: Machine Learning on Flink - Next steps

ahmanyari wrote: Great points to start:- Online learning - Offline learning with the streaming API Thanks + have a great weekend. From: Katherin Eri To: dev@flink.apache.org Sent: Friday, March 3, 2017 7:41 AM Subject: Re: Machine Learning on Flink - Next steps Thank you,

Re: Machine Learning on Flink - Next steps

ari wrote: > Great points to start:- Online learning > - Offline learning with the streaming API > > Thanks + have a great weekend. > > From: Katherin Eri > To: dev@flink.apache.org > Sent: Friday, March 3, 2017 7:41 AM > Subject: Re: Machine Learnin

Re: Machine Learning on Flink - Next steps

Great points to start:    - Online learning   - Offline learning with the streaming API Thanks + have a great weekend. From: Katherin Eri To: dev@flink.apache.org Sent: Friday, March 3, 2017 7:41 AM Subject: Re: Machine Learning on Flink - Next steps Thank you, Theodore. Shortly

Re: Machine Learning on Flink - Next steps

Thank you, Theodore. Shortly speaking I vote for: 1) Online learning 2) Low-latency prediction serving -> Offline learning with the batch API In details: 1) If streaming is strong side of Flink lets use it, and try to support some online learning or light weight inmemory learning algorithms. Try

Machine Learning on Flink - Next steps

Hello all, >From our previous discussion started by Stavros, we decided to start a planning document [1] to figure out possible next steps for ML on Flink. Our concerns where mainly ensuring active development while satisfying the needs of the community. We have listed a number of proposals for