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Home Page: https://makgyver.github.io/rectorch/
License: MIT License
rectorch is a pytorch-based framework for state-of-the-art top-N recommendation
Home Page: https://makgyver.github.io/rectorch/
License: MIT License
Hello! I'm very interested in using these models (especially the conditioned variational autoencoder), and thank you for your work!
I saw in a thread that in 2020 a tutorial was made for this. Where could I find that tutorial?
Thank you so much!
Thank you very much for sharing your great work.
I would like to know if there is any sample code or notebook that explains all steps (load dataset, build a model, train, evaluate or predict).
Thank a lot.
FEATURE REQUEST
Might be a good idea to take 2-3 popular top-N recommendation datasets and add a results table. Of course depends on available hardware.
Might also want to check out https://github.com/microsoft/recommenders/blob/master/README.md for documentation ideas.
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