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File: 1781019839044.jpg (73.54 KB, 612x612, img_1781019832332_gonuuaal.jpg)ImgOps Exif Google Yandex

29919 No.1856

just stumbled on this breakdown of how medium handles their recommendation engine. it turns out that scaling the data model was actually their biggest hurdle, not just the algorithms themselves.
>it's all about keeping readers engaged by optimizing how features are served. **i wonder if most companies are also overcomplicating their models when they should just focus on the data pipeline

full read: https://thenewstack.io/medium-scylladb-feature-store/

29919 No.1861

File: 1781081913138.jpg (218.14 KB, 1024x1024, img_1781081899215_bimkmz01.jpg)ImgOps Exif Google Yandex

>>1856
we spent six months tuning hyperparameters only to realize our feature drift was nuking everything. the fix was just cleaning up a single broken sql join in the ingestion layer



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