Offline to Online: Feature Storage for Real-time Recommendation Systems with NVIDIA Merlin – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-03-27T16:00:00Z http://www.open-lab.net/blog/feed/ Sam Partee <![CDATA[Offline to Online: Feature Storage for Real-time Recommendation Systems with NVIDIA Merlin]]> http://www.open-lab.net/blog/?p=61401 2023-04-11T05:04:25Z 2023-03-01T19:12:21Z Recommendation models have progressed rapidly in recent years due to advances in deep learning and the use of vector embeddings. The growing complexity of these...]]> Recommendation models have progressed rapidly in recent years due to advances in deep learning and the use of vector embeddings. The growing complexity of these...Diagram of four steps with Redis logo beow

Recommendation models have progressed rapidly in recent years due to advances in deep learning and the use of vector embeddings. The growing complexity of these models demands robust systems to support them, which can be challenging to deploy and maintain in production. In the paper Monolith: Real Time Recommendation System With Collisionless Embedding Table, ByteDance details how they built��

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