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What We Learned from 150 Successful ML-enabled Products at Booking.com.

Posted Jul 12, 2021 | Views 376
# Machine Learning
# ML Products
# Booking.com
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SPEAKERS
Pablo Estevez
Pablo Estevez
Pablo Estevez
Principal Machine Learning Scientist @ Booking.com

Pablo Estevez is a 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.

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Pablo Estevez is a 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.

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Demetrios Brinkmann
Demetrios Brinkmann
Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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Vishnu Rachakonda
Vishnu Rachakonda
Vishnu Rachakonda
Data Scientist @ Firsthand

Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.

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Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.

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SUMMARY

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.

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