recommenders: 10 curated resources
recommenders
10 resources · page 1 of 1
facebookresearch/dlrm
Meta DLRM GitHub repo: implementation of a deep learning recommendation model.
Generative Recommenders (HSTU)
by meta-recsys
Meta generative-recommenders GitHub repo: code for HSTU generative recommendation from Actions Speak Louder than Words.
Lviv Polytechnic: recommendations on applying generative AI
by Lviv Polytechnic National University
Lviv Polytechnic recommendations on applying generative AI in academic journals and conferences.
RecBole
by RUCAIBox
RUCAIBox RecBole GitHub repo: unified library of recommendation algorithms for reproducible comparison.
Recommenders
Recommenders GitHub repo: examples and utilities for building recommendation systems.
X recommendation algorithm
twitter the-algorithm GitHub repo: source code of the X recommendation algorithm services.
OECD AI Recommendation (OECD-LEGAL-0449)
by OECD
OECD Recommendation of the Council on Artificial Intelligence, the source of the OECD AI Principles and AI system definition.
Deep Learning Recommendation Model for Personalization and Recommendation Systems (DLRM)
arXiv PDF of Meta's DLRM paper (2019), a deep learning recommendation model for personalisation.
Neural Collaborative Filtering
by Xiangnan He et al. (National University of Singapore)
arXiv PDF of the Neural Collaborative Filtering paper (2017) for neural recommender systems.
Wide & Deep
by Heng-Tze Cheng et al. (Google)
arXiv paper (2016) "Wide & Deep Learning for Recommender Systems", introducing Google's Wide & Deep recommender model.