[Chicago] ChiPy July 2020 __main__ Meeting
Joe Jasinski
joe.jasinski at gmail.com
Tue Jul 7 21:59:49 EDT 2020
Hi ChiPy,
Our next remote ChiPy __main__ meeting is just about here! We hope you'll
join us - we have some great talks planned. See you there!
*When: * Thursday July 9, 2020, 6 p.m.
*Where: *Remote Meeting
You can join our Live Stream at the following link:
https://www.youtube.com/watch?v=pazAZW9xFQY
*More info:*
https://www.chipy.org/
*What*
- *Ten Ways to Fizz Buzz*
By: Joel Grus
Description:
Fizz Buzz is the following (simple) problem:
Print the numbers from 1 to 100, except that if the number is divisible
by 3, instead print "fizz"; if the number is divisible by 5, instead print
"buzz"; and if the number is divisible by 15, instead print "fizzbuzz".
My association with this problem began in 2016, when I wrote a blog post
called Fizz Buzz in Tensorflow, the (possibly fictional) story of one such
insulted programmer who decided to show up his interviewer by approaching
Fizz Buzz as a deep learning problem. This post went modestly viral, and
ever since then I have been seen as a thought leader in the Fizz Buzz space.
Accordingly, over the years I have come up with and/or collected various
other stupid and/or clever ways of solving Fizz Buzz. I have not blogged
about them, as I am not the sort of person who beats a joke to death, but
occasionally I will tweet about them, and recently in response someone
suggested that I write a book on "100 Ways of Writing Fizz Buzz in Python."
Now, I could probably come up with 100 ways of solving Fizz Buzz, but
most of them would not be very interesting. Luckily for you, I was able to
come up with 10 that are interesting in various ways, which I will barrel
through in 15 minutes or less.
- *Introduction to AutoML*
By: Paco Nathan
Description:
AutoML is a very active area of AI research in academia as well as R&D
work in industry. The public cloud vendors each promote some form of AutoML
service. Tech unicorns have been developing AutoML services for their data
platforms. Many different open source projects are available, which provide
interesting new approaches. But what does AutoML mean? Ostensibly automated
machine learning will help put ML capabilities into the hands of
non-experts, help improve the efficiency of ML workflows, and accelerate AI
research overall. While in the long-term AutoML services promise to
automate the end-to-end process of applying ML in real-world business use
cases, what are the capabilities and limitations in the near-term? This
talk surveys the landscape and history for projects and research efforts
related to AutoML, looking beyond just hyperparameter optimization and
considering the impact on end-to-end workflows and data science practices.
We'll show sample code using different open source projects and provide
pointers to online resources to learn more.
- *ChiPy Mentorship Returns*
By: Ben Xia-Reinert and Emily Xia-Reinert
Description:
The new ChiPy Mentorship site is going live on July 4th. While the
structured, 13-week ChiPy Mentorship program is not returning, this app
will enable members of the Chicago Python community who wish to be mentees
and mentors to find and connect with each other. In this talk, we will
explain how the app was made, what we are looking to accomplish, and how
you can be a part of it.
Thank you always to our sponsors, including our Event Sponsor, Rally
Health. ChiPy is a community run event and we depend on generous donations
from our sponsors to make events and activities possible.
If you or your company is interested in sponsoring, we'd love to talk with
you as we update our sponsorships for 2020.
Please be aware of and abide by our code of conduct
http://www.chipy.org/pages/conduct/
Engage with ChiPy
Website: https://www.chipy.org/
Slack: https://joinchipyslack.herokuapp.com/
Meetup: https://www.meetup.com/_ChiPy_/
Github: https://github.com/chicagopython/chipy.org
Twitter: https://twitter.com/chicagopython
YouTube: https://www.youtube.com/channel/UCT372EAC1orBOSUd2fsA8WA
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