Today I’m joined by Sachin, a senior data scientist. We’ll go over a machine learning system design question on how to build YouTube’s homepage recommendations system and optimize it.

Watch the rest on the question page: https://www.interviewquery.com/questions/youtube-recommendations

Previous YouTube Recommendations interview with Dan: https://youtu.be/9TxN1VoPYq4

Follow Sachin on LinkedIn: https://www.linkedin.com/in/venugopal-mani-umn/

His sources:
HRNN Paper: https://openreview.net/pdf?id=8QFKbygVy4r
Prof Weinberger’s channel: https://www.youtube.com/channel/UC7p_I0qxYZP94vhesuLAWNA/featured
Prof. Justin Johnson’s course: https://www.youtube.com/watch?v=dJYGatp4SvA&list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r

Ready to find top-tier machine learning talent who can design cutting-edge recommendation systems like YouTube’s? Outsearch.ai leverages AI to match you with candidates who have the skills and experience to tackle complex ML challenges: https://www.outsearch.ai/?utm_source=youtube&utm_medium=video&utm_campaign=outsearch_promotion&utm_content=ml_system_design_youtube

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00:00 – Question
00:17 – Clarifying Questions
03:57 – System Architecture of an ideal recommender
13:24 – Various Components of the architecture
26:25 – Online/Offline evaluation of the recommendation
30:03 – AB Test Launch

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