About us
PyLadiesATX is a social/professional group for lady Python enthusiasts at every experience level. Beginners are always welcome! We represent Pythonistas from a wide variety of disciplines and interest areas - full-time developers and hobbyists alike.
Unless otherwise noted, PyLadiesATX events are exclusively for PyLadies and their invited guests. We are a group for women and other gender minorities. Trans women are welcome and recognized as women. If you are a woman who enjoys learning about and writing Python, we would love to have you come join us.
PyLadiesATX is dedicated to providing a respectful, harassment-free community. Please read & follow our Code of Conduct: http://www.pyladies.com/CodeOfConduct/
If you would like to report an incident or contact our leadership team, please fill out this form. No identifying information needed.
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* Join us on IRC: #pyladies
* Follow us on Twitter: https://twitter.com/pyladiesatx
* Join us on Facebook: https://www.facebook.com/PyladiesAustin
* Join us on Slack: https://pyladiesatx.slack.com - To Join, please message us your email address to get an invite!
* Join us on LinkedIn: https://www.linkedin.com/company/65837560
And if you'd like to get some more information about our parent organization, check out the web site: http://www.pyladies.com
Upcoming events
2
- Network event

PyTexas Monthly Meetup: LLM-powered Merge Conflict Resolution
·OnlineOnline30 attendees from 10 groupsJoin us for our monthly meetup! The meetup will take place in the PyTexas Discord server, so be sure to join!
This month we are excited to be joined by Advitya Gemawat
Speaker: Advitya Gemawat
Topic: LLM-powered Merged Conflict ResolutionMerge Conflicts in software programming occur in 20% of all merges in open-source projects, incurring a median resolution time of ~6 minutes for a single conflict at best, or multiple days at worst. This talk will touch upon LLM Evaluations, Azure OpenAI Fine-Tuning, AI-generated resolution explanations, and usage of multiple Python SDKs to craft a scalable LLM-powered Merge Conflict Resolver. Our results indicate up to 125% performance improvement over vanilla LLM resolution accuracy.
3 attendees from this group
Past events
244







