makgyver / rectorch Goto Github PK

rectorch is a pytorch-based framework for state-of-the-art top-N recommendation

Home Page: https://makgyver.github.io/rectorch/

License: MIT License

Python 99.39% Makefile 0.29% Batchfile 0.31%

recommender-system collaborative-filtering autoencoder variational-autoencoder generative-adversarial-network pypi pytorch matrix-factorization top-n-recommendations

rectorch's Issues

Sample training code

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.

Where could I find a tutorial?

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!

Add results?

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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