Anime, Manga, & Novel Recommender Website and Application - User and Content-Based Recommendation using Anilist Account (Android and Web). Recommends Anime, Manga (Manhwa, Manhua, One Shots), Novel (LN - Light Novel, WN - Web Novel).

たまに追加される論文メモ

SEP490 - SU24

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

A simple Recommender System for well-being based on Genetic Algorithms.

Large scale recommender system inference Microservices and APIs （Dubbo 、gRPC and REST ） with Golang.

推荐系统入门指南，全面介绍了工业级推荐系统的理论知识（王树森推荐系统公开课-基于小红书的场景讲解工业界真实的推荐系统），如何基于TensorFlow2训练模型，如何实现高性能、高并发、高可用的Golang推理微服务。Comprehensively introduced the theory of industrial recommender system, how to trainning models based on TensorFlow2, how to implement the high-performance、high-concurrency and high-available inference services base on Golang.

SEP490 - SU24

Survey: A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.

A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io

This repository features a recommendation system and analytics engine using datasets on users, organizations, contents, contacts, events, and recommendations. It includes data preprocessing, building a recommendation system, and creating visual reports with Power BI.

A world wines dataset with user ratings for recommendation systems and general use.

A tutorial series by Preferred.AI

Repository hosting code used to reproduce results in "Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152, ICML'24).

Competition for the Recommender Systems course @ PoliMi. The objective is to recommend relevant TV shows to users. Models were evaluated on their MAP@10.

This repository contains recent research papers, datasets, and source codes (if any) for Group Recommendation

[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"

Pick Me A Flick: A content filtering based Movie Recommendation Engine .

This is the repo for the survey of Bias and Fairness in IR with LLMs.

pytorch version of neural collaborative filtering