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From Jeremy Anderson <>
Subject Re: Getting new users to adopt SystemML
Date Fri, 07 Oct 2016 02:17:09 GMT
+1 Madison

I started started doing some user research with a few other designers.
We're looking for patterns and pain points around adoption and use of
SystemML. We'd love to share our findings so far to continue this
discussion and get thoughts and feedback from everyone. I think clear
tutorials and site architecture will help address some of the concerns
we're hearing and could improve adoption. I love the idea of generating
more articles and content on Stack Overflow. All of this would be really
helpful in increasing awareness and building community.

We're synthesizing our research so far and we'll share it here. Thanks for
starting this thread!



Jeremy Anderson

On 6 October 2016 at 10:33, Madison Myers <> wrote:

> Hi all,
> Thought it may be a good idea to implement some measures on getting new
> users to adopt SystemML. At the moment, I feel there is a big learning
> curve and that we could make it easier through clearer tutorials and
> examples, a better user experience on the website (continuing the process
> of making it better), more articles that explain SystemML at a high level
> and how to use it/why it's important. I also think we should get more
> questions and answers on Stack Overflow so that overcoming issues is a bit
> easier for new users. Longer-term I'd also love to see a course taught
> online such as on Coursera as well as in university classrooms so that
> people in the field adopt SystemML more early-on.
> Also Deron and Mike had some interesting suggestions about visibility. They
> suggested having projects using SystemML on personal Github accounts as
> well as mentioning SystemML as a skill on LinkedIn.
> Would love to know if others agree and/or have suggestions.
> Thanks!
> --
> *Madison J. Myers*
> *UC Berkeley, Master of Information & Data Science '17*
> *King's College London, MA Political Science '14*
> *New York University, BA Political Science '12*
>    -
>       LinkedIn <>

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