[BangPypers] Making Data Science Work - A Webinar on S/W Engineering in ML - Tonight, 17th of June at 7 PM

[Abhiram R]

Hello,
Yes, I've been informed that it will be available on the same link as in
the previous email.



Regards
Abhiram <https://abhiramr.com>

On Wed, Jun 17, 2020 at 3:23 PM Propadovic Nenad <npropadovic at gmail.com>
wrote:

> Hello,
> will there be a video of this webinar?
> I can not attend, as I work, but I'd like to see it as video, if possible.
> Cheers,
> Nenad
>
> Am Mi., 17. Juni 2020 um 11:45 Uhr schrieb Abhiram R <
> abhi.darkness at gmail.com>:
>
> > Hello,
> > This is a PSA -
> > There's an upcoming Webinar tonight, the 17th of June, on the principles
> of
> > Software Engineering in Machine Learning conducted by Hasgeek from 7 PM -
> > 8.10 PM. In this, Venkata Pingali <https://www.linkedin.com/in/pingali/>
> > and Indrayudh Ghoshal <https://www.linkedin.com/in/indrayudhghoshal/>
> > from Scribble
> > Data <https://www.scribbledata.io/> discuss with  Dmitry Pretrov
> > <https://www.linkedin.com/in/dmitryleopetrov/> and Ivan Shcheklein
> > <https://www.linkedin.com/in/shcheklein/>, co-founders of iterative.ai,
> on
> > the following pertinent points -
> >
> > 1. Do software engineering principles apply to Machine Learning
> development
> > and deployment?
> > 2. How is an ML system different from traditional application?
> > 3. How important is data versioning?
> > 4. What are the next logical steps in the development of the data science
> > engineering tool chains?
> > 5. How will the data ecosystem evolve over the next few years?
> >
> > These are interesting times and the topics in question are extremely
> > important for anyone who's interested in the fields. As an alumnus of
> > Scribble Data, I've had a chance to witness first-hand the complexities
> > data - structured or unstructured - can pose and the way disciplined
> > engineering can make a difference in the workflow of an ML system.
> >
> > RSVP here to check it out and attend the webinar :) -
> > https://hasgeek.com/fifthelephant/making-data-science-work-session-3/
> >
> >
> > Regards
> > Abhiram R <https://abhiramr.com>
> > _______________________________________________
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> > BangPypers at python.org
> > https://mail.python.org/mailman/listinfo/bangpypers
> >
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-- 
-Abhiram R