I've started the discussion here http://apache-ignite-developers.2346864.n4.nabble.com/Proposed-Release-2-7-7-2-7-6-ML-extra-fixed-bugs-td43537.html
пт, 13 сент. 2019 г. в 22:12, Alexey Zinoviev <zaleslaw....@gmail.com>: > The reason was that the last year there is no significant releases of > Ignite between 2.7 and 2.8, only minor releases with long story of renaming. > I am and another ML guys are ready in 1-2 months prepare ML module for 2.8 > or for the minor release 2.7.7 = 2.7.6 + updated ML + new fixed bugs > > Let's discuss it in separate thread next week > > > > пт, 13 сент. 2019 г. в 21:55, Denis Magda <dma...@apache.org>: > >> Alexey, I'm wondering, >> >> Are there any dependencies on Ignite Core that make us put off the ML >> changes release until 2.8? I know that you do not support the idea of ML >> as >> a separate Ignite module but this concept would allow us to release ML as >> frequently as we want not being blocked by Ignite core releases. >> >> >> - >> Denis >> >> >> On Fri, Sep 13, 2019 at 11:45 AM Alexey Zinoviev <zaleslaw....@gmail.com> >> wrote: >> >> > I could answer as one of developers of ML module. >> > Currently is available the ML in version 2.7.5, it supports a lot of >> > algorithms and could be used in production, but the API is not stable >> and >> > will be changed in 2.8 >> > >> > The ML module will be stable since next release 2.8, also we have no >> > performance report to compare for example with Spark ML >> > Based on my exploration the performance of in terms of Big O notation is >> > the same like in Spark ML (real numbers says that Ignite ML is more >> faster >> > than Spark ML due to Ignite in-memory nature and so on) >> > >> > Since 2.8 it will have good integration with TensorFlow, Spark ML, >> XGBoost >> > via model inference. >> > >> > You as a user have no ability to run, for-example scikit-learn or R >> > packages in distributed mode over Ignite, but you could run the >> TensorFlow, >> > using Ignite as a distributed back-end instead of Horovod. >> > >> > If you have any questions, please let me know >> > >> > >> > >> > пт, 13 сент. 2019 г. в 21:28, Denis Magda <dma...@apache.org>: >> > >> >> David, >> >> >> >> Let me loop in Ignite dev list that has Ignite ML experts subscribed. >> >> Please, could you share more details in regards to your performance >> >> testing >> >> and objectives for Ignite ML overall? >> >> >> >> The module is ready for production and we're ready to help solve any >> >> cornerstones. >> >> >> >> - >> >> Denis >> >> >> >> >> >> On Fri, Sep 6, 2019 at 4:50 AM David Williams <leeon2...@gmail.com> >> >> wrote: >> >> >> >> > Python is 25 times slower than Java for ML at runtimes, which I found >> >> out >> >> > online. But I don't know that statement is true or not. I need >> insiders' >> >> > opinion. Which ml other packages are best options for Ignite? >> >> > >> >> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mikael-arons...@telia.com> >> >> wrote: >> >> > >> >> >> Hi! >> >> >> >> >> >> I have never used it myself but it's been there for long time and I >> >> >> would expect it to be stable, and yes it will run distributed, I >> can't >> >> >> say anything about performance as I have never used it. >> >> >> >> >> >> You will find a lot of more information at: >> >> >> >> >> >> https://apacheignite.readme.io/docs/machine-learning >> >> >> >> >> >> Mikael >> >> >> >> >> >> >> >> >> Den 2019-09-06 kl. 11:50, skrev David Williams: >> >> >> > >> >> >> > >> >> >> > I am evaluating ML framework for Java platform. I knew Ignite has >> ML >> >> >> > package. >> >> >> > But I like to know its stability and performance for production. >> Can >> >> >> > Ignite >> >> >> > ML code run in distribute way? >> >> >> > >> >> >> > Except its own ML package, which ml packages are best options for >> >> >> Ignite? >> >> >> >> >> > >> >> >> > >> >
