├── .gitignore ├── 01-Recommender-System-101 ├── .gitkeep ├── 02-1-numpy, pandas와 친해지기.ipynb ├── 02-2-PyTorch-기본.ipynb ├── 03-MovieLens 데이터 - 유저와 영화 그리고 평점 데이터 분석.ipynb ├── 04-MovieLens 데이터 - 영화 기본정보 데이터 분석.ipynb └── 05-추천시스템 맛보기.ipynb ├── 02-Basic-Recommender-System ├── .gitkeep ├── 01-컨텐츠기반-06-TF-IDF 실습.ipynb ├── 01_컨텐츠기반_07_TF_IDF로_추천알고리즘_만들기.ipynb ├── 02_이웃기반_협업필터링_04_이웃기반_협업필터링_구현하기.ipynb ├── 03-모델기반 협업필터링-07-Matrix Factorization 실습.ipynb └── 03-모델기반 협업필터링-08-협업필터링 성능 비교 분석하기.ipynb ├── 03-Other-Recommener-Systems └── .gitkeep ├── 04-Recommender-System-with-DeepLearning ├── .gitkeep ├── 01-딥러닝과 추천알고리즘-01-영화데이터셋 비교 feat. MovieLens, Netflix, kmrd.ipynb ├── 01-딥러닝과 추천알고리즘-03-Neural Collaborative Filtering 실습.ipynb ├── 01-딥러닝과 추천알고리즘-05-Factorization Machine 실습.ipynb ├── 01-딥러닝과 추천알고리즘-07-Wide_Deep Learning for Recommender System 실습.ipynb ├── 01-딥러닝과 추천알고리즘-09-DeepFM 실습.ipynb ├── 01-딥러닝과 추천알고리즘-11-AutoEncoder Meet Collaborative Filtering 실습.ipynb ├── 02-나를 위한 추천 알고리즘-02-리뷰데이터로 추천성능 끌어올리기.ipynb ├── 02-나를 위한 추천 알고리즘-04-상품 이미지를 적용하여 추천알고리즘 실습하기.ipynb └── 02-나를 위한 추천 알고리즘-06-듣고싶은 음악 추천알고리즘 실습하기.ipynb ├── README.md ├── data └── movielens │ ├── README.txt │ ├── links.csv │ ├── movies.csv │ ├── ratings.csv │ └── tags.csv ├── news_sample.txt └── paper ├── 2-1-BPR-Bayesian Personalied Ranking from Implicit Feedback.pdf ├── 3-1-LARS-A Location-Aware Recommender System.pdf ├── 4-1-Neural Collaborative Filtering.pdf ├── 4-10-Deep Neural Networks for YouTube Recommendations.pdf ├── 4-11-Deep Learning Based Recommender System A Survey and New Perspectives.pdf ├── 4-2-Factorization Machines.pdf ├── 4-3-Wide_Deep Learning for Recommender Systems.pdf ├── 4-4-DeepFM A Factorization-Machine based Neural Network for CTR Prediction.pdf ├── 4-5-AutoRec Autoencoders Meet Collaborative Filtering.pdf ├── 4-5-Training Deep AutoEncoders for Collaborative Filtering.pdf ├── 4-6-Joint Training of Ratings and Reviews with Recurrent Recommender Networks.pdf ├── 4-7-Image-based Recommendations on Styles and Substitutes.pdf ├── 4-7-VBPR Visual Bayesian Personalized Ranking from Implicit Feedback.pdf ├── 4-8-Deep content-based music recommendation.pdf └── 4-9-Session-based Recommendations with Recurrent Neural Networks.pdf /.gitignore: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jaewonlee-728/fastcampus-RecSys/HEAD/.gitignore -------------------------------------------------------------------------------- /01-Recommender-System-101/.gitkeep: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /01-Recommender-System-101/02-1-numpy, pandas와 친해지기.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jaewonlee-728/fastcampus-RecSys/HEAD/01-Recommender-System-101/02-1-numpy, pandas와 친해지기.ipynb -------------------------------------------------------------------------------- /01-Recommender-System-101/02-2-PyTorch-기본.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jaewonlee-728/fastcampus-RecSys/HEAD/01-Recommender-System-101/02-2-PyTorch-기본.ipynb -------------------------------------------------------------------------------- /01-Recommender-System-101/03-MovieLens 데이터 - 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