Hi Sourav, That sounds very useful for people who are interested in running SystemML through Zeppelin. It would be great if you could share that.
I was wondering, what is your opinion of running SystemML through Zeppelin? Do you think that is a path that is going to be most useful for data scientists to do exploratory work with SystemML? Is there anything that you would like to see improved with regards to the MLContext API? Deron On Thu, Feb 4, 2016 at 4:01 PM, Sourav Mazumder <[email protected] > wrote: > Hi, > > I have a complete end to end Modeling and Prediction using Zepplein and > also visualization of the prediction using R plots. > > I can share the same too if that is useful. > > Regards, > Sourav > > On Thu, Feb 4, 2016 at 3:20 PM, Luciano Resende <[email protected]> > wrote: > > > I started experimenting with some nice ways to enable data scientists to > > get started with SystemML with the minimum setup and a pleasant user > > experience. > > > > Following the guide published in the SystemML project documentation page > > [1], I created a docker image containing the necessary infrastructure for > > running SystemML in a cluster mode, and also installed and configured > > Zeppelin with SystemML and the sample notebook available. > > > > Please see more detailed instructions to use it at > > > > https://github.com/lresende/docker-systemml-notebook > > > > If people start to find this very useful we could move this to SystemML > > project itself and start making more scenarios available as sample > > Notebooks > > > > [1] > > > > > http://apache.github.io/incubator-systemml/spark-mlcontext-programming-guide.html#zeppelin-notebook-example---linear-regression-algorithm > > > > [2] https://github.com/lresende/docker-systemml-notebook > > > > -- > > Luciano Resende > > http://people.apache.org/~lresende > > http://twitter.com/lresende1975 > > http://lresende.blogspot.com/ > > >
