PyData London - 55th Meetup

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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.

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, AHL.

We are issuing tickets via a lottery - if you want to be in with a chance of a place - sign up for the waitlist! The lottery will be run approx 1 week before the meetup, and we will re-run the lottery to fill any spaces that free up or use the waitlist towards the time of the event.

Main Talks

David Howlett

Playing chess with Python

This talk covers how to build a simple chess playing program in python, this will include minimax, piece valuation and positional evaluation. By the end of the talk there will be a functioning chess program running live. I will assume you know python but not the existing literature on how to write chess engines. I became fascinated by this topic after taking part in a competition with my brothers to build the best chess program during the Christmas holidays 2016.

Bruce Pannaman

User behavior on user session click data

Data pipelines are necessary for the flow of information from its source to its consumers, typically data scientists, analysts and software developers. Managing data flow from many sources is a complex task where the maintenance cost limits the scale of being able to build a large reliable data warehouse. This presentation proposes a number of applied data engineering principles that can be used to build robust easily manageable data pipelines and data products. Examples will be shown using Python on AWS.

Lightning Talks

Jakub Czakon
How to track and organize your experimentation process

Tom Phillips
"What are type hints?"

Logistics

Doors open at 6.30pm (get there early as you have to sign-in via AHL's 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.