When a consumer opens the Deliveroo app they have the option to pick from a huge variety of restaurants. Depending on their location, the number of available restaurants can vary from 10’s to almost 1,000 (and counting). However, as there is limited screen space on a consumer’s device we want to make sure that the restaurants that we surface first are the most relevant. In October last year we formed a team to address this problem. We needed to decide on the tools and infrastructure to build and deploy these models as well as how we were going to frame the ranking problem. In this talk we’ll explain how we’re using Tensorflow to train and deploy our models. We’ll also discuss the challenges that we’ve faced in tackling the ranking problem and outline the solutions that we’ve implemented or proposed to overcome them.
YOU MAY ALSO LIKE:
- Data-Driven Improvement of Software Quality with Markus Harrer (Online Course on 15th - 16th November 2021)
- Intersectional Communication (Online Meetup on 23rd September 2021)
- Personal SLAs: How to Maintain Balance at Work (Online Meetup on 30th September 2021)
- Building a Runtime Reflection System for Rust (SkillsCast recorded in May 2021)
- Hedge your Bets with Rust (SkillsCast recorded in May 2021)
You got served: How Deliveroo improved the ranking of restaurants
Jonny Brooks-Bartlett is a data scientist at Deliveroo working on algorithms designed to improve the consumer experience. Outside of work Jonny is a keen science communicator and delivers public talks on science and mathematics. He also enjoys sports and keeping fit.