torchrec and RecTools
PyTorch RecSys is a low-level tensor computation framework for building recommendation models at scale, while RecTools is a higher-level library that simplifies the end-to-end workflow of building and evaluating recommender systems, making them complementary tools that could be used together in a production pipeline.
About torchrec
meta-pytorch/torchrec
Pytorch domain library for recommendation systems
This helps recommendation system engineers and machine learning scientists build, train, and deploy large-scale personalization models more efficiently. You provide user interaction data (like clicks or purchases), and it helps generate predictions for what users might like next. This is for teams developing recommendation features for products with many users and items, like e-commerce platforms or social media feeds.
About RecTools
MTSWebServices/RecTools
RecTools - library to build Recommendation Systems easier and faster than ever before
This helps data scientists and machine learning engineers quickly build and evaluate recommendation systems. You provide historical user interaction data (like purchases or views), and it generates a list of personalized item recommendations for each user. This is ideal for those responsible for improving user engagement and conversion rates in products and services that offer a large catalog of items.
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