TIL

1.[TIL] 21.05.06 dataframe

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2.[TIL] 21.05.07 dataframe 조작

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3.[TIL]21.05.10 dataframe 형태변환

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4.[TIL] 21.05.11 미분(derivate)

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5.[TIL] 21.05.13 t-test

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6.[TIL] 21.05.15 groupby, reindex, 카이제곱 검정

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7.[TIL] 21.05.18 신뢰구간, 큰수의법칙, 중심 극한가설

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8.[TIL] 21.05.20 시각화+

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9.[TIL] 21.05.21 numpy 행렬

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10.[TIL] 21.05.24 공분산 상관계수

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11.[TIL] 21.05.25 PCA

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12.[TIL] 21.05.26 K-means clustering

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13.[TIL] 21.05.27 K-means cluster의 K값 구하기

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14.[TIL] 21.06.08 simple regression

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15.[TIL] 21.06.09 Multi linear regression

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16.[TIL] 21.06.10 Ridge Regression

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17.[TIL] 21.06.11 Logistic Regression

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18.[TIL] 21.06.15 Decision Tree Classifier with Pipe line, graphviz

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19.[TIL] 21.06.16 OrdinalEncoder, TargetEncoder

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20.[TIL] 21.06.23 Practice Regression with Used Cars Price Dataset

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21.[TIL] 21.06.24 feature importance

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22.[TIL] 21.06.28 PDP, Shap value plot

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23.[TIL]21.07.09 git

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24.[TIL]21.07.12 SQL

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25.[TIL]21.07.13 PostgreSQL 접속, MongoDB Example

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26.[TIL]21.07.16 python psycopg2를 사용한 Postgresql 접속

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27.[TIL]21.07.20 SQLalchemy

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28.[TIL]21.07.27 flask 기초

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29.[TIL]21.08.09 간단한 딥러닝 회귀예측

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30.[TIL]21.08.12 딥러닝 overfitting 규제 전략

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31.[TIL]21.09.09 Python sorted 함수의 활용

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