Let me try to answer here. (1) Apache Ignite 2.0 is coming with the early (beta) version of ML Grid. ML Grid (beta) will have basic core math (vectors and matrices) for local and distributed, dense and sparse processing on Ignite cluster. It will also have all the basic surrounding block. The design is heavily borrowed from Apache Mahout but adopted to Apache Ignite in-memory platform.
(2) I know many users of the project use Ignite as-is for speeding up matrix and vector operations even before ML Grid. You can use Compute and Data Grids together to develop highly efficient co-located processing of sparse data sets. You can your training data, for example, in Data Grid and use custom Compute Grid tasks to process it. Obviously, with introduction of ML Grid that should be a lot simpler now... Hope it give you couple of pointers on where to start. Best, -- Nikita Ivanov On Sat, May 6, 2017 at 2:04 AM, ChickyDutt <[email protected]> wrote: > Hi team, > > I want to know how and where could Apache ignite fit in the field of > predictive analytics and machine learning. > > Do you have any use cases or reference that outline the interaction > between the two aforementioned systems. > > Regards. > > ------------------------------ > View this message in context: Machine learning and Apache Ignite > <http://apache-ignite-users.70518.x6.nabble.com/Machine-learning-and-Apache-Ignite-tp12470.html> > Sent from the Apache Ignite Users mailing list archive > <http://apache-ignite-users.70518.x6.nabble.com/> at Nabble.com. >
