Скачать или смотреть M̶o̶d̶e̶l̶ System Design for Recommendations & Search by Eugene Yan

̶M̶o̶d̶e̶l̶ System Design for Recommendations & Search by Eugene Yan at NDR - The AI Conf, November 2021

Most papers and conference talks focus on model architecture and how it improves on the state-of-the-art. Not this one. In this talk, Eugene focuses on system design. How do we design systems for low-latency, high-throughput serving for recommendations and search? In this talk, he shares a 2×2 framework of online vs. offline and retrieval vs. ranking. He also goes through examples of how companies like Alibaba, Facebook, and DoorDash serve their recommendation and search.

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Eugene Yan - Applied Scientist at Amazon

Eugene Yan designs, builds, and operates machine learning systems that serve customers at scale. He’s currently an Applied Scientist at Amazon. Previously, he led the data science teams at Lazada (acquired by Alibaba) and uCare.ai. He writes & speaks about data science, data/ML systems, and career growth at eugeneyan.com and tweets at @eugeneyan.

https://codecamp.ro/e-conferences/ndr...

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