PyData London Meetup

1. 🚨🚨🚨A valid photo ID is required by building security. 🚨🚨🚨
2. This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event.

If your RSVP status says "You're going" you will be able to get in. No need to show your RSVP confirmation when signing in.
If you can no longer make it, please unRSVP as soon as you know.
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Code of Conduct:
This event follows the NumFOCUS Code of Conduct. Please get in touch with the organisers with any questions or concerns regarding the Code of Conduct.
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As always, there'll be free food & drinks, generously provided by our host, Man Group.
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Main Talks

1. Platforms for valuable AI Products: Iteration, iteration, iteration - John Carney
Platforms for valuable AI Products: Iteration, iteration, iteration
Abstract: Platforms for valuable AI Products: Iteration, iteration, iteration
Abstract: In data science experimentation is vital, the more we can experiment, the more we can learn.
However quick iteration isn't sufficient we also need to be able to easily promote these experiments to production to deliver value. This requires all the stability and reliability of any production system.
John will discuss building platforms that treat iteration as a first class consideration, the role of open source libraries, and balancing trade-offs.

2. Implementing Grounded AI Code Agents - Saurav Maheshkar @maheshkarsaurav
With context window on the rise there's been an increase in the number of tools who depend on entire codebases. In this talk I'll discuss some alternative techniques one could use to provide quality relevant context to build better AI Code Agents with some example projects.

⚡ Lightning Talks
1. The Glicko-2 Algorithm in the context of Go (Baduk, Weiqi): A Smarter Framework for Competitive Ranking in Zero-Sum Games - Victor Zommers

2. Automated Prompt Engineering for Deploying AI Applications at Scale- Anand Rawat

Logistics
Doors open at 6.30 pm (get there early as you have to sign-in via building security), talks start at 7 pm, drinks from 9 pm in the bar. We will have reduced capacity for this event but there will be plenty of people to discuss data science questions with!
Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members!
Follow @pydatalondon (https://twitter.com/pydatalondon) for updates and early announcements.