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Recommendation @ Scale
Submitted by Aditya Patel (@adityap) on Tuesday, 30 April 2019
Section: Crisp talk Technical level: Intermediate Session type: Lecture
Recommendation is one of the most traditional and wide spread use case of Machine Learning. In this talk we want to showcase, how an advanced recommendation engine can be served at scale in Glance. Glance is an AI-powered, content driven, personalised Screen Zero (lockscreen) platform for mobile, which is used by over 26M DAU users in India. The talk will take you through each component of a recommendation engine and in the end will showcase the learnings which we got from our experiments to make it functional at scale.
- What is Glance
- Recommendation Engine in Glance
- Serving Architecture
Aditya Patel is Director, Data Science at InMobi-Glance. Previously he was head of data science at Stasis and has 7+ years of experience spanning over the fields of Machine Learning and Signal Processing. He graduated with Dual Master’s degree in Biomedical and Electrical Engineering from the University of Southern California. He has presented his work in Machine learning at multiple peer reviewed conference. He also contributed to first generation “Artificial Pancreas” project in Medtronic, Los Angeles. In his current role, he is aiding in building the biggest content platform in India.