Details
Submit a talk: https://london.pydata.org/submit-a-talk/
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NOTE: A valid photo ID is required by building security. You MUST use your full real names on your meetup profile, otherwise, you will NOT make it on the guest list!
Tickets are assigned through a lottery draw initially. Waitlist places are assigned manually. We can only admit you if you use your full real names on your meetup profile.
If your RSVP status says "You're going" you will be able to get in. No further confirmation required. You will NOT need to show your RSVP confirmation when signing in.
If you can no longer make it, please unRSVP as soon as you know so we can assign your place to someone on the waiting list.
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CODE OF CONDUCT: https://numfocus.org/code-of-conduct
This event follows the NumFOCUS code of conduct, please familiarise yourself with it before the event. 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.
Main Talks
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* Tariq Rashid on “Trust, Ethics, and Safety in Data Science”
There is a growing interest in how safely and ethically organizations use data, machine learning, and automated decisions. Drawing on recent consultations by the UK government and EU, Tariq will explore a practical framework for developing and demonstrating trustworthy AI that covers not just data and technology, but also process and governance.
* Anders Bogsnes on "PyTorch in three chapters"
Neural Networks are all the rage, with Pytorch this and Tensorflow that. We will strip it all down, building a neural net in pure Numpy, switching to basic Pytorch and ending up with a bells-and-whistles implementation in Pytorch. You should end up with an appreciation for exactly what Pytorch gives you and understand deep learning a little bit more!
Lightning Talks
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Richard on Man Group Hackathon Retrospective: https://www.man.com/hackathon2019
Geir Freysson on Quantipy: an open source python library for analysing survey data. Analysing survey data with python isn't as straight forward as you might think and how Quantipy solves that problem.
Logistics
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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 normally have >200 folks in the room so there's plenty of people to discuss data science questions with!
Please unRSVP in good time if you realize 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.
