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fastcampus-RecSys

패스트캠퍼스 추천시스템 A to Z

  • 강의에 사용될 코드, 데이터, 논문 등을 정리해서 올려두는 github repo 입니다.
  • 코드 또는 기타 다른 내용에 문제가 있을 경우, issue 또는 pull requests 주시면 반영하겠습니다.
  • Jupyter 코드는 수업 용도로 제작된 코드 입니다. 코드에서 일부분 활용하여 추천시스템을 구현하는데 사용할 수 있습니다.

Data

  • 수업에 사용될 데이터셋은 다음과 같습니다. 아래 링크와 수업 내용을 참고해서 데이터를 직접 다운받아 사용할 수 있습니다.
    1. MovieLens
    2. KMRD
    3. Netflix
    4. Amazon Product Review / Image
      • Download Link에서 review와 image 데이터 모두 다운로드 할 수 있다. image데이터는 상품별 5-core 데이터를 다운로드한다.
    5. Music dataset

Paper

  • 수업에 사용될 논문 리스트는 다음과 같습니다.
    1. Part 2
      • BPR: Bayesian Personalized Ranking from Implicit Feedback
    2. Part 3
      • LARS: A Location-Aware Recommender System
    3. Part 4
      • Neural Collaborative Filtering
      • Factorization Machines
      • Wide & Deep Learning for Recommender Systems
      • DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
      • AutoRec: Autoencoders Meet Collaborative Filtering
      • Training Deep AutoEncoders for Collaborative Filtering
      • Joint Training of Ratings and Reviews with Recurrent Recommender Networks
      • Image-based Recommendations on Styles and Substitutes
      • VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback
      • Deep content-based music recommendation
      • Session-based Recommendations with Recurrent Neural Networks
      • Deep Neural Networks for YouTube Recommendations
      • Deep Learning Based Recommender System: A Survey and New Perspectives

fastcampus-recsys's People

Contributors

jaewonlee-728 avatar jakeyoon-dev avatar

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