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From Madison Myers <madisonjmy...@gmail.com>
Subject Re: Documentation Personas
Date Fri, 30 Sep 2016 03:10:21 GMT
Thanks for your input!

I have an all day meeting/brainstorm session with the design team tomorrow
so this is super helpful. I totally agree with Mike that the personas
should not be directly addressed, but rather opportunities for different
personas/levels to interact with SystemML are available on the website for
the different user personas to navigate.

I think starting out, we are going to address the main issue: converting
new users to SystemML. Unfortunately even just a how to write your
algorithms is not a basic enough "hello world" if we want data scientists
to start using SystemML- especially those in school. Because more advanced
users can navigate the current documentation a little easier, we will focus
on that later, though it remains a priority.

I can give you an update after the meeting tomorrow, but for now, we
generally spoke about making tutorials and documentation clearer and even
potentially having links to Jupyter notebooks where users could follow
along. We will also be focusing on the website flow so that people don't
get lost while navigating and so that selections are more intuitive.

If you have any tutorials that are not already on the website, please send
them my way! We want to compile everything in order to have it all in one
place (and more organized!).

Thanks!

On Thu, Sep 29, 2016 at 5:51 PM, <dusenberrymw@gmail.com> wrote:

> These topics and the idea of the personas are great!  I would suggest that
> we don't explicitly use the specific persona titles though. I.e. Instead of
> specifically using "data scientists" we could just use "machine learning"
> such as "Getting started guide to machine learning with SystemML". Likewise
> the topics for "data engineers" could instead be something like "Getting
> started guide to engine development". We could also have a "deployment"
> guide, etc.  In each we could also have beginner and expert sections.
>
> --
>
> Mike Dusenberry
> GitHub: github.com/dusenberrymw
> LinkedIn: linkedin.com/in/mikedusenberry
>
> Sent from my iPhone.
>
>
> > On Sep 29, 2016, at 4:07 PM, Luciano Resende <luckbr1975@gmail.com>
> wrote:
> >
> > On Wed, Sep 28, 2016 at 6:06 PM, Madison Myers <madisonjmyers@gmail.com>
> > wrote:
> >
> >> Thanks for opening up this dialogue Felix & Luciano!
> >> .....
> >>
> >> Additionally, Luciano mentioned that he was trying to find two key
> personas
> >> for the SystemML website. Looking at the results from the SystemML
> survey I
> >> sent out a few weeks ago, it is clear that an overwhelming majority of
> >> people voted for Data Scientist- new and Data Scientist- advanced.
> Input on
> >> if you agree on these results would be helpful.
> >>
> >> ....
> >>
> >> Thanks again!
> >> Madison
> >
> >
> >
> > I was thinking on two main personas : Data Scientist and Data Engineers.
> > And at least for the Data Scientist, we might have to have topics for
> both
> > R and Python.
> >
> >
> > In summary, I would say :
> >
> >
> >
> > Getting Started for Data Scientists (note that we should have a version
> for
> > R and Python):
> >
> > - Creating algorithms with SystemML : this is kind a helloworld where a
> > Data Scientist creates and runs a very simple algorithm.
> >
> > - Running existing algorithms with SystemML : in this scenario, we would
> > guide the data scientist on how to run an algorithm from the sample
> library
> > from SystemML. We should also guide the data scientist to choose the
> right
> > algorithm for his/her specific problem.
> >
> > - Customizing existing algorithms with SystemML: in this scenario, we
> would
> > guide the data scientist to start making customization and applying the
> > algorithm for different data sets.
> >
> >
> >
> >
> > Getting started for Data Engineers:
> >
> > - Overview of different options/runtimes supported by SystemML
> >
> > - Debugging SystemML ???
> >
> > - Engine development guide ???
> >
> > Thoughts ?
> >
> >
> > --
> > Luciano Resende
> > http://twitter.com/lresende1975
> > http://lresende.blogspot.com/
>



-- 
*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 <http://linkedin.com/in/madisonjmyers>

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