Over the last 20 years we have witnessed the applications of machine learning in search, recommendations and advertising. The state of the art machine learning systems are large-scale, near-real-time, multi-modal and intelligent in nature. In this presentation, I’ll focus on a few most recent advances, including faster retrieval, large-scale ranking models, advances in reranking, and experimentation. Real-world examples will be given. I’ll also outline some challenges and active areas of research.
Session Summary
Industrial Applications of Machine Learning in Search and Recommendations
MLconf 2022 San Francisco
Jay Wang
Kuaishou
Head of Data Science
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