GitHub - NicolasPetermann134/music_recommendation: contains the notebooks that I created for implementing probabilistic matrix factorization in PyTorch for music recommendation engine.

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contains the notebooks that I created for implementing probabilistic matrix factorization in PyTorch for music recommendation engine.

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README.txt		README.txt
music_ratings_learner.ipynb		music_ratings_learner.ipynb
music_recommender_EDA.ipynb		music_recommender_EDA.ipynb

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This directory contains two notebooks:

music_recommender_EDA
- contains all EDA that was performed on the music recommendation data set, as
well as all tranformations/corrections applied to the data

music_ratings_learner
- contains the probabilistic matrix factorization model implementation, as well
as all code for data loaders, training the model, etc.


I wrote an entire article explaining the theory and implementation in this
project that can be found at https://towardsdatascience.com/building-a-music-recommendation-engine-with-probabilistic-matrix-factorization-in-pytorch-7d2934067d4a