PyData London - 68th meetup

Venue: 1 Angel Lane, EC4R 3AB

Please note:

1. 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!
2. This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event.

Tickets are assigned through a lottery draw about 1 week before the event.

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:
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 Group.

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Main Talks
1️⃣ The 7 lines of code you need to run faster real-time inference — Adrian Boguszewski

You've already trained your great neural network. It reaches 99.9% of accuracy and saves the world, so you would like to deploy it. However, it must run in real time and process data locally, and you don't want to build a web API. After all, you are a Data Scientist, not a Web Developer… So, is it possible to automatically optimize and run the network fast on the local hardware you have, not the hardware you wish you had? Absolutely! During the talk, I'll present the OpenVINO Toolkit. You'll learn how to automatically convert the model using Model Optimizer and run the inference with the Runtime. The magic with only seven lines of code. After all, you'll get a step-by-step jupyter notebook to try at home.

2️⃣ Introducing Nebari: An open source JupyterHub distribution that provides an all-in-one development and experimentation platform for teams to work efficiently and collaboratively — Amit Kumar

In this talk, I will demonstrate how Nebari, an open source project can be used to setup a full-fledged Data Science environment on major cloud providers with a simple configuration file, without the knowledge of complex terms like "Kubernetes" & "Load balancer".

Lightning Talks

1. Intermediate Python regex against the clock. — Ned Stratton
2. Humble Data: Teaching Data Science at PyCon Ghana. — Cheuk Ting Ho

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.