Description: “추천시스템 관련 링크”

Table of contents

1. Engineers
2. RecFra
3. Rec Lib
4. Rec paper Repo
5. Dataset
6. Tema
7. News
8. Lecture
9. tutorial

Engineers

1. pyxelr/recommendations-for-engineers

RecFra

1. RUCAIBox/RecBole
2. RUCAIBox/RecBole2.0
3. microsoft/recommenders
4. wubinzzu/NeuRec
5. rn5l/session-rec
6. MaurizioFD/RecSys_Course_AT_PoliMi
7. beta-team/beta-recsys
8. alonsoir/awesome-recommendation-engine
9. maciejkula/spotlight
10. cowjen01/repsys
11. shenweichen/DeepCTR-Torch
12. shenweichen/DeepCTR
13. NVIDIA-Merlin/HugeCTR

Rec Lib

1. yoonjong12/pinsage
2. pytorch/torchrec
3. ShinhwanKang/BeGin

Rec paper Repo

1. FeiSun/BERT4Rec
2. guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
3. loserChen/Awesome-Recommender-System
4. SeongBeomLEE/RecsysTutorial
5. bladejun/Recommend_System_Pytorch
6. doublemul/ADER
7. hongleizhang/RSPapers
8. CRIPAC-DIG/TAGNN
9. CRIPAC-DIG/SR-GNN
10. gusye1234/LightGCN-PyTorch
11. lyst/lightfm
12. xiangwang1223/neural_graph_collaborative_filtering
13. kuandeng/LightGCN
14. zzaebok/KGCN-pytorch
15. cn-uofbasel/PiCN
16. AIM-SE/DIF-SR
17. donalee/BUIR

Dataset

1. otto-de/recsys-dataset
2. khanhnamle1994/movielens
3. sidooms/MovieTweetings

Tema

1. kakao/recoteam
2. Pseudo-Lab/Recommendation-System

News

1. SeongBeomLEE/RecSys-Tech-Blog-Article

Lecture

1. jaewonlee-728/fastcampus-RecSys

tutorial

1. xei/recommender-system-tutorial
2. fastforwardlabs/session_based_recommenders