Chicago Python Data Special Interest Group's (SIG) 2020 Kickoff will be held on January 15th. This month's meeting is graciously hosted and sponsored by IBM!
IBM is hiring! Check out their open positions: https://ibm.com/careers
DIRECTIONS TO VENUE
- Once at 71 S Wacker, check-in at security with your driver's license, State ID, or Passport
- You will be directed to the elevators that lead to the 6th-floor conference room
6:00 - Doors open
6:30 - Talks Start
8:30 - See you all next time!
Open-source libraries for Trusted AI
by Svetlana Levitan
Machine learning has moved from the lab into many critical application areas affecting lives and well-being of many people. This includes health care, financial services, justice system, self-driving cars, etc. This makes the issue of trust in ML very important. Are the models fair, explainable, robust to adversarial attacks? In this session we will discuss open source Python libraries created by IBM Research that are designed to address all those issues.
Developer Advocate with IBM Center for Open Source Data and AI Technologies (CODAIT), Svetlana has been a software engineer, architect, and technical lead for SPSS Analytic components for many years. She represents IBM at the Data Mining Group and is the release manager for PMML and PFA, open standards for predictive model deployment. She is also working with other companies on ONNX, an open model exchange format for deep learning models. Svetlana is a co-organizer of several Chicagoland Meetup groups, including Big Data Developers in Chicago and Chicago Cloud Developers. She has authored several blogs and presented at many conferences and other events. Svetlana loves to learn new technologies and to share her expertise, to encourage girls and women in STEM.
Out-of-core Nested Octree for LiDAR
by Arushi Rai
Have you ever had data that was too large to process in memory? See how I used pickle to create a custom out-of-core data structure to store massive LiDAR data and the problems that arose from using a nested octree.
Arushi is a CS major at Illinois Tech (IIT) who loves LiDAR and geospatial stuff.
Insignificant statistics: What statistical significance means, why it's broken, and how to fix it
by Zach Lipp
It has never been easier to either analyze data or communicate to mass audiences. As an unfortunate consequence, faulty scientific results can spread further than ever. Good tooling can help promote good science, but science's most popular tool is the wrong one for the job. In this talk, we will give a real-world introduction to significance and p-values, explain and demonstrate why they are broken, and offer alternatives.
Zach is a data scientist and engineer who loves Python, Docker, and reproducibility. He's currently a Senior Software Engineer at Lumere.