ML Sys Design¶
Notes on ML systems at scale — recommendation engines, feed ranking, retrieval architectures, and the engineering choices behind them.
Each piece is structured in two parts: the original source (a paper or engineering post), then where the field has moved since.
Notes¶
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YouTube Recommendations — Deep neural networks for recommendation at scale. Based on the 2016 Google RecSys paper by Covington, Adams, and Sargin.
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Facebook News Feed Ranking — Multi-objective ranking on a social graph. Based on Meta's 2021 engineering post on Feed ranking.