The Nextdoor AI team invites industry experts to share best practices and industry knowledge.

How to Build Recommendation Systems and Lessons Learned

Dr. Bee-Chung Chen is a machine learning (ML) expert with extensive industrial and research experience in search and recommender systems, some of which is summarized in his book titled Statistical Methods for Recommender Systems. He is currently a Senior Architect at Pinterest responsible for ML for all Pinterest’s core products. He was the first ever ML Distinguished Engineer at LinkedIn responsible for LinkedIn’s ML technology from hardware and platforms to tools, libraries and algorithms. He started ML-based ranking for LinkedIn Feed and has been a key designer of the ML methods used in a wide variety of search and recommender systems used in Pinterest, LinkedIn and Yahoo!, including the home pages of all these sites. He received the Ph.D. in Computer Science from University of Wisconsin – Madison and a M.S. from National Taiwan University. His research interests include recommender systems, machine learning and big data processing.

Watch the talk here.