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Recommendation System at Lyft

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@ -734,6 +734,7 @@ An updated and organized reading list for illustrating the patterns of scalable,
* [Machine Learning Platform at Uber](https://eng.uber.com/michelangelo/) * [Machine Learning Platform at Uber](https://eng.uber.com/michelangelo/)
* [Machine Learning Platform at Yelp](https://engineeringblog.yelp.com/2020/07/ML-platform-overview.html) * [Machine Learning Platform at Yelp](https://engineeringblog.yelp.com/2020/07/ML-platform-overview.html)
* [Machine Learning Platform at Etsy](https://codeascraft.com/2021/12/21/redesigning-etsys-machine-learning-platform/) * [Machine Learning Platform at Etsy](https://codeascraft.com/2021/12/21/redesigning-etsys-machine-learning-platform/)
* [Recommendation System at Lyft](https://eng.lyft.com/the-recommendation-system-at-lyft-67bc9dcc1793)
* [Platform for Serving Recommendations at Etsy](https://www.etsy.com/sg-en/codeascraft/building-a-platform-for-serving-recommendations-at-etsy) * [Platform for Serving Recommendations at Etsy](https://www.etsy.com/sg-en/codeascraft/building-a-platform-for-serving-recommendations-at-etsy)
* [Infrastructure to Run User Forecasts at Spotify](https://engineering.atspotify.com/2022/06/how-we-built-infrastructure-to-run-user-forecasts-at-spotify/) * [Infrastructure to Run User Forecasts at Spotify](https://engineering.atspotify.com/2022/06/how-we-built-infrastructure-to-run-user-forecasts-at-spotify/)
* [Aroma: Using ML for Code Recommendation at Facebook](https://code.fb.com/developer-tools/aroma/) * [Aroma: Using ML for Code Recommendation at Facebook](https://code.fb.com/developer-tools/aroma/)