IndyPy: La Femme Pythonista

Agenda:

Can't attend in person? Join our livestream here: https://sixfeetup.zoom.us/webinar/register/WN_o6WjQ089Q2aLtE3VBVyQ6Q

7:00p - 7:15p Announcements and introductions

7:15p - 7:30p PBJ Session
"Where to Start When You're New to Machine Learning" by Alyssa Batula
Machine learning can seem complicated and intimidating, so what's a Pythonista to do when they need to use it for a new project? Fortunately, Python libraries can handle most of the technical details for us. To help you use these tools effectively, I'll give an overview of what machine learning is, what types of problems it's good at solving, how to get set up to use it, and how to avoid some common problems when getting started.

7:30p - 7:45p Right Brain Talk
"A Disabled Dev's Journey" by Ashlee Boyer
Every company wants to be first to market, but that's only one part of a product's success. Companies often consider accessibility too time-consuming or difficult to put into place without remembering that meeting customer needs is what keeps them in the market. This talk will cover my experience advocating for accessibility as a disabled developer and why there's no excuse for treating it as an edge case.

7:45p - 8:00p Door Prizes

8:00p - 8:45p Pro Talk
"Machine Learning in Python for Detecting Blight in a Large City" by Cathy Wyss
This talk gives an overview of contemporary Machine Learning techniques and their application to the domain of predicting blight from commonly available data regarding a large city. An example of the use of these techniques is to catch blight before it becomes a systemic problem and/or assist communities in recovering from blight. Discrete and continuous approaches are considered, compared, and contrasted, including decision trees and deep neural nets. A combined approach turns out to be the most beneficial for officials who have to make decisions based on such models.