

What we’re about
PyData Chicago is a monthly meetup to discuss all things python (or R, Julia, C++, Rust, Go, ...) and data! Our meetup is now hybrid! Enjoy the event in person or virtually, hosted on Zoom. We usually meet on the last Thursday of the month.
All meetups are recorded and posted on PyData's YouTube channel 1 week after the event -- unless the speaker does not want to be recorded. Presentation decks, code and other artifacts from the meeting are also shared with all attendees subscribed to the Meetup event 1 week after the event -- with the permission of the speaker.
The PyData Code of Conduct governs this Meetup. To discuss any issues or concerns relating to the code of conduct or the behavior of anyone at a PyData meetup, please contact co-organizer Olivia Martin via Meetup's message feature.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
Sponsors
See allUpcoming events (2)
See all- Network event6 attendees from 16 groups hostingSciPy 2025 ConferenceGreater Tacoma Convention Center, Tacoma, WA
Join us for the annual SciPy Conference, July 7-13, in Tacoma, Washington and virtually online. Register at https://www.scipy2025.scipy.org/.
SciPy allows participants from all types of organizations to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. The full program will consist of two days of tutorials followed by three days of presentations, and concludes with two days of developer sprints on projects of interest to attendees.
- Machine learning in data assimilationUIC Douglas Hall, Chicago, IL
Abstract: Data assimilation is concerned with sequentially estimating a time-evolving signal from partial and noisy observations. The signal is often assumed to evolve according to a known dynamical system, but in practice, the dynamics are rarely fully known and are subject to significant model error. Machine learning techniques have recently emerged as a promising avenue to improve dynamical system models for data assimilation in important applications such as numerical weather forecasting. In addition to alleviating model error, machine-learned models are cheaper to evaluate and hence enable running multiple parallel forecasts for uncertainty quantification. Machine learning techniques also provide several other potential advantages, including the online co-learning of the signal and the dynamics, the improvement of the spatial resolution of signal estimates, and the data-driven enhancement of data assimilation algorithms. This talk will survey some recent advances and open questions in combining machine learning with data assimilation.
Speaker Name and Bio: Daniel Sanz-Alonso, Associate Professor at University of Chicago
Host: Olivia Martin, Justin Shea, Mehdi Jeddi, and Sou-Cheng Choi
Talk Format: This is a hybrid event. To attend online, join us on Zoom here at 6pm:
https://numfocus-org.zoom.us/j/89399976851?pwd=UEgMUZXdYmKdK1x1dIPL6hwUYnp7NW.1Sponsor: Adyen, UIC College of Business, and PyData Chicago co-host this event. UIC will provide the meeting site. Adyen will sponsor pizza and soft drinks for the onsite participants.
Address: University of Illinois - Chicago, Douglass Hall, Room 220, 705 S Morgan St, Chicago, IL 60607
Logistics: “UIC Douglass Hall” is recognized on Google Maps, which can guide you through campus. Once you arrive, proceed to the second floor, room number 220