One really interesting blog I read today was about how Instagram built and scaled its recommendation system ⚡
They talked about how they leverage interests and engagement to build a ranking system and how they use the Two Towers approach to predict engagement events (e.g., someone liking a post) and that is used as a similarity measure.
The blog covers both high-level design and low-level details. So, if you are building a recommendation engine, or are keen on exploring it, do give it a read. if some concepts seem alien to you, apply DFS. That’s what I did :)
give it a read - https://lnkd.in/gxAHSNg6
⚡ I keep writing and sharing my practical experience and learnings every day, so if you resonate then follow along. I keep it no fluff.
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