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"Best Practices for Recommendation Systems", Vedant Dhandhania Lead Scientist (AI, ML) at BCG Digital Ventures
Abstract:
Recommender systems are ubiquitous in today's digital ecosystem.
It solves a search/discovery problem by sifting through large volumes of dynamically generated information/content/products to provide users with personalized content.
This talk explores the different characteristics & potentials of different recommendation engines in various verticals such as news/eCommerce/media.
We further discuss practical business consideration (that complements theoretical formulations) & layout commonly seen problems observed in recommendation engines in big companies. Relevant topics pertaining to recommender systems such as practical A-B testing & evaluations are concluded.
Vedant is a Lead Machine Learning Scientist at Apple, with 10 years of Industry experience building AI-driven products in a variety of industries - Retail, Manufacturing, Entertainment.
Prior to that, Vedant was at Boston Consulting Group & Retention Science. He has an M.S degree in EE with focus on start-ups.
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