

#13: The Netflix Recommender System and Beyond with Justin Basilico
12 snips Feb 15, 2023
Justin Basilico, director of research and engineering at Netflix, discusses the evolution of the Netflix recommender system from rating prediction to deep learning. They talk about the misalignment of metrics, the use of history, content, and context data, and the challenges of personalized page construction. They also touch on RecSysOps, cultural aspects at Netflix, and the importance of feedback and team collaboration.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8
Introduction
00:00 • 2min
Justin Basilico's Background and Early Work on Movie Recommendation
01:42 • 3min
Evolution of Recommender Systems
05:00 • 23min
Optimizing Score Evaluation and Balancing Factors
28:00 • 19min
Understanding and Diagnosing Issues in Recommender Systems
46:46 • 16min
The Culture and Collaboration at Netflix
01:03:04 • 2min
Teamwork and Collaboration in Recommender Systems
01:05:32 • 10min
The Rex's Conference and Opportunities for Industry Professionals
01:15:58 • 4min