MSDS Seminar Series in Data Science: Best Practices for Recommendation Systems with Vedant Dhandhania, Lead Scientist (AI, ML) at BCG Digital Ventures
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 and potentials of different recommendation engines in various verticals such as news/eCommerce/media.
We further discuss practical business consideration (that complements theoretical formulations) and layout commonly seen problems observed in recommendation engines in big companies. Relevant topics pertaining to recommender systems such as practical A-B testing and 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 and Retention Science. He has an M.S degree in EE with focus on start-ups.