//Abstract

While most of the Machine Learning literature focuses on the algorithmic or mathematical aspects of the field, not much has been published about how Machine Learning can deliver meaningful impact in an industrial environment where commercial gains are paramount. We conducted an analysis on about 150 successful customer-facing applications of Machine Learning, developed by dozens of teams in Booking.com, exposed to hundreds of millions of users worldwide, and validated through rigorous Randomized Controlled Trials. Our main conclusion is that an iterative, hypothesis-driven process, integrated with other disciplines was fundamental to build 150 successful products enabled by Machine Learning.

// Bio

Pablo Estevez is the Principal Data Scientist at Booking.com. He has worked on recommendations, personalization, and experimentation across the Booking.com website, as well as as a manager on several machine learning, data science, and product development teams.

// Other Links

Talk on the topic: https://www.youtube.com/watch?v=ljhtfrtuNqw&t=4h24m30s

The paper: https://blog.kevinhu.me/2021/04/25/25-Paper-Reading-Booking.com-Experiences/bernardi2019.pdf

--------------- ✌️Connect With Us ✌️ -------------

Join our slack community: https://go.mlops.community/slack

Follow us on Twitter: @mlopscommunity

Sign up for the next meetup: https://go.mlops.community/register

Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/

Connect with Pablo on LinkedIn: https://www.linkedin.com/in/estevezpablo/