06-03, 11:45–12:25 (Europe/London), Warwick
I will present the challenges we encountered while migrating an ML model from batch to real-time predictions and how we handled them. In particular, I will focus on the design decisions and open-source tools we built to test the code, data and models as part of the CI/CD pipeline and enable us to ship fast with confidence.
At GetYourGuide we build a marketplace for travel experiences. The ranking of activities on the platform is one of the most essential machine-learning products for the business.
In this talk, I will explain how we gradually migrated our ranking from global precomputed scores to a live reranking service. Building such a service with high availability requirements and constant modifications brings challenges. I will dive into the design decisions and open-source tools we built to enable us to test code, data, and models as part of the CI/CD pipeline. It allows us to ship fast with confidence without losing ourselves in cumbersome tests and/or a mocking hell.
At the end of the talk, you will have actionable insights you can apply to your Machine Learning products and understand how to introduce good MLOps practices using open-source tools.
No previous knowledge expected
Theodore Meynard is a data scientist at GetYourGuide. He works on our ranking algorithm to help customers to find the best activities to book and locations to explore. He is one of the co-organisers of the Pydata Berlin meetup. When he is not programming, he loves riding his bike looking for the best bakery-patisserie in town.