The focus of this Meetup group is to provide free monthly community data events, leading towards the London Data Science Festival.
What is the London Data Science Festival?
Data Science Festival Live - Monday, April 16th to Saturday, April 21st, 2018.
The Data Science Festival LIVE is a free week long, celebration of all things data science. The festival consists of lectures, workshops, demos, code sprints, panel discussions and social events, spread across London and culminated with a day long Mainstage event. Monday to Thursday of the week will be at different venues every evening featuring a range of speakers. Friday night will be a Data Science Networking event and Saturday is our MainStage conference from 9 AM - 6 PM.
Who is this meetup and the Data Science Festival for?
• Data engineers, analysts, scientists, and other practitioners
• R, Python and other software engineers who work with data or want to learn
• Data visualisation developers and designers
• Non-technical team leads, executives, and other decision makers from data centric start-ups and large companies looking to utilise open source tools
Join Data Science Festival - London in partnership with Depop August 14th, for an evening of machine learning and latest framework to production ML systems.
Due to the popularity of Data Science Festival events, we are now allocating event tickets via a random ballot. Registering here enters you into the ticket ballot for the Data Science Festival Event at Depop on August 14th 2019, the ballot will be drawn on August 9th 2019. Those randomly selected will then be e-mailed a Universe ticket for the event, with the joining details.
If you get an allocated Universe ticket, please bring a copy of your paper ticket or your ticket on your phone to the event to check in with your QR code. Tickets are non-transferable.
PLEASE NOTE REGISTERING ON MEETUP DOES NOT GUARANTEE YOU ENTRY TO THIS EVENT.
Please click here to apply for a ticket: https://www.datasciencefestival.com/event/dsf-meetup-with-depop/
6:00pm: Doors open
6:30pm: Clemence Burnichon
7:00pm: Break (pizza provided)
7:30pm: Amy Monkhouse
9:00pm: Leave the building
Clemence Burnichon - Productionising machine learning with spark jobs
Summary: At Depop, we strongly believe that ML deliver value when it is available to all and autonomous. During this talk, I will present our latest framework to production ML systems using spark job and standardised jobs.
Bio: I joined Depop a year and a half ago as a Senior Data Scientist and I am now leading the machine learning effort across Depop. Our mission is to generate knowledge and capabilities to improve our buyer's and seller's experience with Depop. During my 6 years as a data scientist, I have acquired experience in multiple ML fields such as computer vision, recommendation engine and NLP. Prior to Depop, I worked Net-a-porter and Sainsbury’s.
Amy Monkhouse - Using machine learning to protect our users
Summary: Depop has nearly 15 million users, but just like any other online market not all of them are legitimate. A common technique that scammers try to use on our users is to trick them into thinking they want to purchase an item, then moving the conversation out of the app where we can no longer detect any wrongdoings. In this talk, I will discuss the ways we build models to adapt to the specific behaviours scammers use on Depop so that we can automatically ban them with confidence to protect our users.
Bio: I joined Depop just under a year ago as a Junior Data Scientist after graduating from The University of Edinburgh with an MSc in speech and language processing. Since joining, I have used machine learning to allow the business to better understand our inventory and help improve our users’ experiences in the app