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class's Introduction

대학교 수업시간에 배운 과목들 中 유의미한 과제들을 모아둔 저장소


Introduction to Data Analysis

  • 20-2 데이터개론
    • 성적 데이터 분석을 통한 학점 부여(R)
    • 데이터: 19-2 수학2 반별 최종점수 - 개인정보 비식별화(신상정보:제거 , 과제점수:범주화, 결측값:평균값 대체)
    • 기울기 차이나는 성적 구간 中 두 개 의 점을 locator 함수로 plot 후에 성적 부여

Multivariate Data Analysis

  • 21-1 다변량자료분석(R)
    • 과제3 : 행렬만들기, 다차원시각화, 가설검정
    • 과제4 : 다변량데이터 정규성확인
    • 과제5 : 신뢰구간
    • 과제6 : MANOVA
    • 과제7 : PCA
    • 과제8 : Factor Analysis
    • 과제9 : Linear Discriminant Analysis
    • 과제10 : 로지스틱 회귀분석

Machine-Learning

  • 21-1 기계학습
    • 바둑 기력 예측 프로젝트
    • 데이터: x_train - 기보 / y_train - 기력
    • 모델: SVM, Ensemble, Eigen Value
    • 스킬: 모델들의 기력 예측값 -> 평균,올림,반올림,내림

Aritificial-Intelligence

  • 21-2 인공지능
    • MNIST with PyTorch
    • 데이터: x_train - 손글씨 / y_train - 숫자 label
    • 학습 : BackPropagation, 활성화함수, normalization(BN-LN-IN-GN), size(Batch size, roup size)

Data-Base

  • 21-2 데이터베이스
    • 과제1: Crawler, Crawler w/ login
    • 과제2: Parser

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