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    전자공학회논문지

    Journal of The Institute of Electronics and Information Engineers

    TIIS

    KSII Transactions on Internet and Information Systems

    정보과학회지

    Communications of KIISE

    한국정보처리학회 논문지
    소프트웨어 및 데이터 공학

    KIPS Transactions on Software and Data Engineering

    한국정보통신학회논문지

    Journal of the Korea Institute of Information and
    Communication Engineering

    한국통신학회논문지

    The Journal of Korea Information and Communications Society

  • 연구 첫걸음

    최신 연구 토픽에 관한 개념들을 쉽게 풀이하고
    트렌트 및 관련 기관 현황을 알 수 있는 연구 입문자들을 위한 연구 가이드

  • 고려대학교
    주재걸

    Neural Networks and Decision Trees Decision Trees

    This will give an overview of neural networks and decision trees as well as their variants. In detail, I'll cover the technical details on fully-connected neural networks, a basic form of neural networks and many other deep learning models, in terms of their structures and how the forward and the backward propagations work. Regarding the decision trees. I'll cover classification and regression trees (called CART in short) and their advanced models including random forests and gardient-boosting trees.

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