PyData Lancaster October 2023 Meetup 🎃

Welcome to PyData Lancaster, a community of data enthusiasts who like to meet together once a month and talk all things data related!
Along with pizza, cake and drinks, we will be bringing in local data scientists, developers, researchers, and data professionals from all different fields, backgrounds and experiences.

Our meeting place is Fraser House Hub, in the centre of Lancaster at White Cross Business Park.

You can expect to see a new event on the last Wednesday of every month! (With the exception of December)

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Schedule
18:00 - Meet and greet. Grab some pizza, cake, or something to drink and meet some people!
18:30 - First speaker
19:00 - Break
19:15 - Second speaker
19:45 - Wrap up, hang out and then to the pub!
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Speaker Lineup

> > Shubhan Kamat (he/him) - Data Scientist at Reliable Insights
> > > "Peeking Inside the Black Box: Making AI Models More Interpretable": Interpretable machine learning has become increasingly important as AI systems are being deployed in critical domains like healthcare, finance, and law. Complex black box models can make highly accurate predictions but offer no transparency into how they arrive at those predictions. Lack of model interpretability can hinder the debugging, auditing and improvement of AI systems. It also makes it difficult to build trust with end-users. This talk will provide an overview of techniques like LIME, SHAP, and integrated gradients that generate post-hoc explanations to make opaque models more interpretable. We will also cover inherent interpretability methods like decision trees, rule-based systems, and generalized additive models. Using real-world examples, I will demonstrate how these interpretability techniques help shed light on model behavior, detect biases, and make AI more transparent, fair, robust and trustworthy. The talk aims to stress the growing importance of model interpretability in responsible AI development.

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> > Cristine Rauber Oliveira (she/her) - Applied Scientist at Yelp
> > > "Why you should not rely solely on summary statistics": In this presentation we will unleash the mask behind those sneaky summary statistics! Get ready for an eye-opening adventure that'll turn your 'means', 'medians' and 'modes' upside down. Cause guess what? They're not telling you the whole truth!

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Location:
Fraser House Hub
South Road
Lancaster
LA1 4XQ
We will be meeting at Fraser House Hub (Relative Insight HQ) on the ground floor.

Pizza, coffee, tea, beer, wine, soft drinks and cakes will be provided free of charge (thanks sponsors!)

Feel free to come early to hang out, have a drink, or help set up. The Organisers will be arriving at 18:00

If you have any questions, send us a message on your preferred social media platform.

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We welcome everyone with an interest in all things data, from beginners to seasoned pros, whether you work in linguistics, journalism, eCommerce, physics, or anything in between. We're big fans of open source. Python and R are data science staples, but other languages and perspectives are more than welcome!

PyData Lancaster is a chapter of PyData, an educational program of NumFOCUS and thus abides by the NumFOCUS Code of Conduct https://pydata.org/code-of-conduct.html. Please take a moment to familiarise yourself with its contents.

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Sponsors:
Relative Insight - https://relativeinsight.com/
Fraser House - https://fraserhousehub.co.uk/
NumFocus - https://numfocus.org/

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Organisers
Ryan Callihan - Head of NLP at Relative Insight (he/him)
Joshua Bailey - Data Scientist at Relative Insight (he/him)
Emily Ward - Research Executive at DJS Research (she/her)
Rory Southworth - Community Manager at Fraser House (he/him)
Alice Ashcroft - Researcher in Diversity and Inclusion (she/they)