This repository is for learning & testing various recommender systems.
Models:
- LightFM
- Factorization Machines
- Field Aware Factorization Machines
- Deep Factorization Machines
- Embarrassingly Shallow Autoencoder
- Neural Collaborative Filtering
- Wide and Deep Learning
- Two Tower
Dataset:
Resources I found very helpful:
- https://github.com/rixwew/pytorch-fm/tree/f74ad19771eda104e99874d19dc892e988ec53fa
- https://github.com/microsoft/recommenders
- https://eugeneyan.com/writing/system-design-for-discovery/
- https://github.com/xue-pai/FuxiCTR
- https://d2l.ai/chapter_recommender-systems/
- https://paperswithcode.com/task/recommendation-systems
- https://github.com/openbenchmark/BARS
- https://github.com/khanhnamle1994/MetaRec