colorblank/RecJourney
recommendation system models and notes
Building or improving a recommendation system involves selecting the right algorithms and evaluating their performance. This project helps you experiment with various mainstream recommendation algorithms by providing their PyTorch implementations and evaluating them on public datasets. Data scientists, machine learning engineers, and researchers working on recommender systems will find this useful for comparing and understanding different models.
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Use this if you need to quickly implement, train, and evaluate over 20 different recommendation algorithms using PyTorch and public datasets.
Not ideal if you're looking for a low-code solution or a ready-to-deploy recommendation service without needing to understand the underlying models.
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Python
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Last pushed
Jun 18, 2025
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