For online recommendation systems, continuous training is needed. :) And we are a living video player, the content is changing every minute, so a real time rec system is the must.
On Fri, Mar 18, 2022 at 3:31 AM Sean Owen <sro...@gmail.com> wrote: > (Thank you, not sure that was me though) > I don't know of plans to expose the streaming impls in ML, as they still > work fine in MLlib and they also don't come up much. Continuous training is > relatively rare, maybe under-appreciated, but rare in practice. > > On Thu, Mar 17, 2022 at 1:57 PM Gourav Sengupta <gourav.sengu...@gmail.com> > wrote: > >> Dear friends, >> >> a few years ago, I was in a London meetup seeing Sean (Owen) demonstrate >> how we can try to predict the gender of individuals who are responding to >> tweets after accepting privacy agreements, in case I am not wrong. >> >> It was real time, it was spectacular, and it was the presentation that >> set me into data science and its applications. >> >> Thanks Sean! :) >> >> Regards, >> Gourav Sengupta >> >> >> >> >> On Tue, Mar 15, 2022 at 9:39 PM Artemis User <arte...@dtechspace.com> >> wrote: >> >>> Thanks Sean! Well, it looks like we have to abandon our structured >>> streaming model to use DStream for this, or do you see possibility to use >>> structured streaming with ml instead of mllib? >>> >>> On 3/15/22 4:51 PM, Sean Owen wrote: >>> >>> There is a streaming k-means example in Spark. >>> https://spark.apache.org/docs/latest/mllib-clustering.html#streaming-k-means >>> >>> On Tue, Mar 15, 2022, 3:46 PM Artemis User <arte...@dtechspace.com> >>> wrote: >>> >>>> Has anyone done any experiments of training an ML model using stream >>>> data? especially for unsupervised models? Any suggestions/references >>>> are highly appreciated... >>>> >>>> --------------------------------------------------------------------- >>>> To unsubscribe e-mail: user-unsubscr...@spark.apache.org >>>> >>>> >>>
