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SEMINAR:How to build a recommendation system?

Guest: Utkan Candoğan, Uber Eats

Title: How to build a recommendation system? (IE, CS, EE)

Date/Time: Nov 27, 2024, 09.00

Location: https://sabanciuniv.zoom.us/j/99682567945

Abstract: The Uber Eats home feed recommendation system aims to provide a magical browsing experience to our 150M+ monthly active customers. To this end, the recommendation system leverages machine learning to create a personalized list of stores every time users open the app. In this talk, we will discuss the evolution of this recommendation system. Additionally, we will deep dive into some interesting real life problems that we have encountered in the past, and finally discuss  competencies typically required for ML developer/applied scientist roles in the industry.

Bio: Utkan Candoğan is a Sr. Applied Scientist and ML Developer at Uber Eats, where he focuses on exciting ranking and recommendations problems that surface in the Uber Eats app. He received his PhD from Caltech, where he utilized tools and techniques from mathematical optimization to solve intractable graph problems. Prior to his PhD, he obtained his BS degree from Bilkent University in Electrical Engineering.

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