Each day, over 1.2 million room nights are reserved on Booking.com. That gives us access to huge amount of data which we can utilise in order to provide a better experience to our customers.
We understand that while there are a lot of machine learning frameworks and libraries available, putting the models in production at large scale is still a challenge. I’d like to talk about how we took on the challenge of deploying deep learning models in production: how we chose our tools and developed our internal deep learning infrastructure. I’ll cover how we do model training in Docker containers, distributed TensorFlow training in a cluster of containers, automated re-training of models and finally - deployment of models using Kubernetes. I’ll also talk about how we optimise our model prediction infrastructure for latency or throughput depending on the use case.
Sahil is a software developer at Booking.com. He has been involved in leveraging container infrastructure to help Booking.com’s internal teams in taking advantage of deep learning techniques at scale. An open source software enthusiast, Sahil is a core contributor and community... Read More →
