What we’re about
Our group is a hub in the Exeter area for those working with or interested in working with data in Python. Meetups will feature interesting talks from local python data wranglers and provide ample opportunity to meet likeminded people.
If you're interested in presenting, at this or any future events, please submit a talk proposal: PyData Talk Proposal Form.
We are part of the global PyData network that is an educational program of NumFOCUS, a nonprofit charity promoting open practices in research, data, and scientific computing.
Upcoming events (1)
See all- PyData Exeter #7Exeter Innovation Hub, Exeter
Join us enjoy three talks from our brilliant speakers after some drinks and networking.
Agenda:
- 18:45 Doors open
- 19:15 Talks start
- 20:30 Talks finish - stick around for a drink and networking at the CUCKOO taproom across the road.
Talks:
Pathway to Net Zero: Utilising Open Source Data to Gain Insights into Risks and Rewards of Net Zero Technologies, Dr. Kimberley Green
The talk describes how Butterfly Data and several other collaborating partners gathered open source data on differing Net Zero Technologies and their dependencies and readiness for utilisation. With this information we asked the question of what technologies are most needed and most likely to be available and up and running in time to meet the UK's 2030 and 2050 net zero targets. Using Butterfly Data’s Collide platform we brought the various data sources together to answer this question from a workforce, resource security, and manufacturing capability standpoint.Using Python to Help Optimize AAA Games, Matt Osbond
I have worked in a "Technical Art" field in video games for nearly 17 years and I've been lucky enough to have worked on a huge variety of projects. But they all have one thing in common - they all need optmizing at the end. I'll go over some of the ways in which I use Python tools to find issues, and then resolve them.Enhancing Retrieval-Augmented Generation for Financial Document Processing, Josh Argyle
Retrieval-Augmented Generation (RAG) systems excel in diverse natural language processing tasks, yet integrating graph-based models has been shown to significantly improve performance, especially in complex domains like finance. We've developed a dynamic knowledge graph, specifically tailored for the financial domain, continuously evolving to capture the ever-changing landscape of financial concepts and relationships. This technical overview will highlight how these innovations contribute to more accurate and efficient information retrieval and processing for financial data analysis.Sponsors: Butterfly Data, NumFOCUS, Thinking Connected
CODE OF CONDUCT
The PyData Code of Conduct governs this meetup (https://pydata.org/code-of-conduct/). To discuss any issues or concerns relating to the code of conduct or behaviour of anyone at the PyData meetup, please contact the PyData Exeter organisers, or you can submit a report of any potential Code of Conduct violation directly to NumFOCUS (https://numfocus.typeform.com/to/ynjGdT).
