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PyData Southampton - 24th Meetup

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About this event

What to expect

PyData Southampton's 24th meetup brings together data scientists, Python developers, and analytics enthusiasts for an evening of technical talks, lightning presentations, and community networking. Taking place at Carnival House in Southampton's harbour district, this May 2026 event continues the group's tradition of showcasing practical applications of Python in data science, machine learning, and statistical computing.

Featured Presentations

The evening's main programme features two technical talks exploring cutting-edge approaches to data analysis and optimisation. Andrew Morgan will present "Can we abandon Pareto Fronts? A new compass for optimisation," examining alternative frameworks for multi-objective optimisation problems. A second main talk slot remains to be announced, allowing the community to contribute emerging topics and recent discoveries.

The lightning talk segment includes Adam Hill presenting "Red ball lottery: the 2 urn problem," offering insights into probability theory and statistical reasoning. These shorter presentations provide opportunities for speakers to share quick wins, lessons learned, and interesting challenges they've encountered in their data science work.

Event Experience

Attendees can expect a structured yet welcoming environment that balances technical depth with community building. Doors open at 6:30 PM for early arrivals to network before the 7:00 PM talk schedule begins. The formal programme runs until 9:00 PM, after which participants typically continue conversations at a nearby pub or bar.

Carnival UK generously provides pizza and drinks throughout the evening, creating an informal atmosphere conducive to discussion and collaboration. The venue at Carnival House offers professional facilities in a convenient harbour location, though attendees should note that valid photo ID is required by building security for access.

Who Should Attend

This meetup serves Python practitioners across the spectrum — from data analysts exploring new techniques to experienced machine learning engineers sharing production insights. Topics typically span machine learning, big data processing, statistical computing, and practical Python applications in research and industry. Whether you're working with pandas, scikit-learn, TensorFlow, or exploring new frameworks, you'll find relev

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