├── 01 intro └── 001 22년도 가을학기 강의계획.pdf ├── 02 bigdata datamining ├── 002 Bigdata.pdf ├── 003 Data Mining.pdf ├── 004 IDE 안내.pdf ├── 005 Data 준비.pdf ├── Sources │ ├── data_loader.ipynb │ └── data_loader.py ├── download.sh └── git.ipynb ├── 03 Dtree Ensemble ├── 006 Decision Tree.pdf ├── 007 Bagging_RF.pdf ├── 008 Boost.pdf ├── data │ └── sdot학습데이터.csv └── sources │ ├── 01 Dtree.py │ ├── 02 Bagging_RF.py │ ├── 03 Boost.py │ ├── 04 GBM.py │ └── 05 summary.py ├── 04 SVM ├── 009 SVM.pdf ├── download.sh └── sources │ ├── 01 SVM_hard_margin.py │ ├── 02 SVM_soft_margin.py │ ├── 03 데이터만들기.py │ └── 04 SVM.py ├── 05 Neural Network ├── 010 Neural Network.pdf └── sources │ ├── 010_1 SLP Source.ipynb │ ├── 010_1 SLP Source.py │ ├── 010_2 MLP Sigmoid.ipynb │ ├── 010_2 MLP Sigmoid.py │ ├── 010_3 KERAS.ipynb │ └── 010_3 KERAS.py ├── 06 CNN ├── 011 CNN(합성곱신경망).pdf ├── download.ipynb ├── download.sh └── soures │ ├── 01 Conv1D.ipynb │ ├── 02 이미지 구조 이해하기.ipynb │ ├── 03 Conv2D.ipynb │ └── 04 건물 외벽 학습.ipynb ├── 07 CNN 2 ├── 012 CNN 2.pdf ├── download.ipynb ├── download.sh └── sources │ ├── 01 LENET.ipynb │ ├── 02 CNN SOTA.ipynb │ ├── 03 YOLO.ipynb │ ├── 04 GAN.ipynb │ ├── 05 GAN Pix2Pix.ipynb │ ├── 06 Unet.ipynb │ └── AlexNet(2012).ipynb ├── 08 Time Series ├── 013 Time Series.pdf ├── data │ ├── MOCT_LINK_SEOUL.cpg │ ├── MOCT_LINK_SEOUL.dbf │ ├── MOCT_LINK_SEOUL.prj │ ├── MOCT_LINK_SEOUL.shp │ ├── MOCT_LINK_SEOUL.shx │ ├── topis_final.csv │ ├── 기준금리.xlsx │ └── 월간_매매가격지수_종합.xlsx └── sources │ ├── 01 Time Series Data.ipynb │ ├── 02 RNN.ipynb │ ├── 03 traffic.ipynb │ └── 도로 데이터 전처리.py ├── 09 Clustering ├── 014 클러스터링.pdf ├── download.ipynb ├── download.sh └── sources │ ├── 01 Clustering.ipynb │ ├── 02 image clustering.ipynb │ ├── 03 kobart_summarization.ipynb │ └── 04 sk kobart clustering.ipynb ├── 10 ETC ├── 015 협업필터링 강화학습.pdf ├── data │ ├── 202210_202210_연령별인구현황_월간.csv │ └── CF_model │ │ ├── keras_metadata.pb │ │ ├── saved_model.pb │ │ └── variables │ │ ├── variables.data-00000-of-00001 │ │ └── variables.index └── sources │ ├── 01 Collaborate Filtering.ipynb │ └── 02 TF-IDF.ipynb ├── README.md └── pandana_test.ipynb /01 intro/001 22년도 가을학기 강의계획.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/01 intro/001 22년도 가을학기 강의계획.pdf -------------------------------------------------------------------------------- /02 bigdata datamining/002 Bigdata.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/002 Bigdata.pdf -------------------------------------------------------------------------------- /02 bigdata datamining/003 Data Mining.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/003 Data Mining.pdf -------------------------------------------------------------------------------- /02 bigdata datamining/004 IDE 안내.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/004 IDE 안내.pdf -------------------------------------------------------------------------------- /02 bigdata datamining/005 Data 준비.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/005 Data 준비.pdf -------------------------------------------------------------------------------- /02 bigdata datamining/Sources/data_loader.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/Sources/data_loader.ipynb -------------------------------------------------------------------------------- /02 bigdata datamining/Sources/data_loader.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/Sources/data_loader.py -------------------------------------------------------------------------------- /02 bigdata datamining/download.sh: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/download.sh -------------------------------------------------------------------------------- /02 bigdata datamining/git.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/02 bigdata datamining/git.ipynb -------------------------------------------------------------------------------- /03 Dtree Ensemble/006 Decision Tree.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/006 Decision Tree.pdf -------------------------------------------------------------------------------- /03 Dtree Ensemble/007 Bagging_RF.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/007 Bagging_RF.pdf -------------------------------------------------------------------------------- /03 Dtree Ensemble/008 Boost.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/008 Boost.pdf -------------------------------------------------------------------------------- /03 Dtree Ensemble/data/sdot학습데이터.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/data/sdot학습데이터.csv -------------------------------------------------------------------------------- /03 Dtree Ensemble/sources/01 Dtree.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/sources/01 Dtree.py -------------------------------------------------------------------------------- /03 Dtree Ensemble/sources/02 Bagging_RF.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/sources/02 Bagging_RF.py -------------------------------------------------------------------------------- /03 Dtree Ensemble/sources/03 Boost.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/sources/03 Boost.py -------------------------------------------------------------------------------- /03 Dtree Ensemble/sources/04 GBM.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/sources/04 GBM.py -------------------------------------------------------------------------------- /03 Dtree Ensemble/sources/05 summary.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/03 Dtree Ensemble/sources/05 summary.py -------------------------------------------------------------------------------- /04 SVM/009 SVM.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/04 SVM/009 SVM.pdf -------------------------------------------------------------------------------- /04 SVM/download.sh: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/04 SVM/download.sh -------------------------------------------------------------------------------- /04 SVM/sources/01 SVM_hard_margin.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/04 SVM/sources/01 SVM_hard_margin.py -------------------------------------------------------------------------------- /04 SVM/sources/02 SVM_soft_margin.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/04 SVM/sources/02 SVM_soft_margin.py -------------------------------------------------------------------------------- /04 SVM/sources/03 데이터만들기.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/04 SVM/sources/03 데이터만들기.py -------------------------------------------------------------------------------- /04 SVM/sources/04 SVM.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/04 SVM/sources/04 SVM.py -------------------------------------------------------------------------------- /05 Neural Network/010 Neural Network.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/05 Neural Network/010 Neural Network.pdf -------------------------------------------------------------------------------- /05 Neural Network/sources/010_1 SLP Source.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/05 Neural Network/sources/010_1 SLP Source.ipynb -------------------------------------------------------------------------------- /05 Neural Network/sources/010_1 SLP Source.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/05 Neural Network/sources/010_1 SLP Source.py -------------------------------------------------------------------------------- /05 Neural Network/sources/010_2 MLP Sigmoid.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/05 Neural Network/sources/010_2 MLP Sigmoid.ipynb -------------------------------------------------------------------------------- /05 Neural Network/sources/010_2 MLP Sigmoid.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/05 Neural Network/sources/010_2 MLP Sigmoid.py -------------------------------------------------------------------------------- /05 Neural Network/sources/010_3 KERAS.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/05 Neural Network/sources/010_3 KERAS.ipynb -------------------------------------------------------------------------------- /05 Neural Network/sources/010_3 KERAS.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/05 Neural Network/sources/010_3 KERAS.py -------------------------------------------------------------------------------- /06 CNN/011 CNN(합성곱신경망).pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/06 CNN/011 CNN(합성곱신경망).pdf -------------------------------------------------------------------------------- /06 CNN/download.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/06 CNN/download.ipynb -------------------------------------------------------------------------------- /06 CNN/download.sh: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/06 CNN/download.sh -------------------------------------------------------------------------------- /06 CNN/soures/01 Conv1D.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/06 CNN/soures/01 Conv1D.ipynb -------------------------------------------------------------------------------- /06 CNN/soures/02 이미지 구조 이해하기.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/06 CNN/soures/02 이미지 구조 이해하기.ipynb -------------------------------------------------------------------------------- /06 CNN/soures/03 Conv2D.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/06 CNN/soures/03 Conv2D.ipynb -------------------------------------------------------------------------------- /06 CNN/soures/04 건물 외벽 학습.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/06 CNN/soures/04 건물 외벽 학습.ipynb -------------------------------------------------------------------------------- /07 CNN 2/012 CNN 2.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/012 CNN 2.pdf -------------------------------------------------------------------------------- /07 CNN 2/download.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/download.ipynb -------------------------------------------------------------------------------- /07 CNN 2/download.sh: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/download.sh -------------------------------------------------------------------------------- /07 CNN 2/sources/01 LENET.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/sources/01 LENET.ipynb -------------------------------------------------------------------------------- /07 CNN 2/sources/02 CNN SOTA.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/sources/02 CNN SOTA.ipynb -------------------------------------------------------------------------------- /07 CNN 2/sources/03 YOLO.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/sources/03 YOLO.ipynb -------------------------------------------------------------------------------- /07 CNN 2/sources/04 GAN.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/sources/04 GAN.ipynb -------------------------------------------------------------------------------- /07 CNN 2/sources/05 GAN Pix2Pix.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/sources/05 GAN Pix2Pix.ipynb -------------------------------------------------------------------------------- /07 CNN 2/sources/06 Unet.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/sources/06 Unet.ipynb -------------------------------------------------------------------------------- /07 CNN 2/sources/AlexNet(2012).ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/07 CNN 2/sources/AlexNet(2012).ipynb -------------------------------------------------------------------------------- /08 Time Series/013 Time Series.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/013 Time Series.pdf -------------------------------------------------------------------------------- /08 Time Series/data/MOCT_LINK_SEOUL.cpg: -------------------------------------------------------------------------------- 1 | ISO-8859-1 -------------------------------------------------------------------------------- /08 Time Series/data/MOCT_LINK_SEOUL.dbf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/data/MOCT_LINK_SEOUL.dbf -------------------------------------------------------------------------------- /08 Time Series/data/MOCT_LINK_SEOUL.prj: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/data/MOCT_LINK_SEOUL.prj -------------------------------------------------------------------------------- /08 Time Series/data/MOCT_LINK_SEOUL.shp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/data/MOCT_LINK_SEOUL.shp -------------------------------------------------------------------------------- /08 Time Series/data/MOCT_LINK_SEOUL.shx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/data/MOCT_LINK_SEOUL.shx -------------------------------------------------------------------------------- /08 Time Series/data/topis_final.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/data/topis_final.csv -------------------------------------------------------------------------------- /08 Time Series/data/기준금리.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/data/기준금리.xlsx -------------------------------------------------------------------------------- /08 Time Series/data/월간_매매가격지수_종합.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/data/월간_매매가격지수_종합.xlsx -------------------------------------------------------------------------------- /08 Time Series/sources/01 Time Series Data.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/sources/01 Time Series Data.ipynb -------------------------------------------------------------------------------- /08 Time Series/sources/02 RNN.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/sources/02 RNN.ipynb -------------------------------------------------------------------------------- /08 Time Series/sources/03 traffic.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/sources/03 traffic.ipynb -------------------------------------------------------------------------------- /08 Time Series/sources/도로 데이터 전처리.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/08 Time Series/sources/도로 데이터 전처리.py -------------------------------------------------------------------------------- /09 Clustering/014 클러스터링.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/09 Clustering/014 클러스터링.pdf -------------------------------------------------------------------------------- /09 Clustering/download.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/09 Clustering/download.ipynb -------------------------------------------------------------------------------- /09 Clustering/download.sh: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/09 Clustering/download.sh -------------------------------------------------------------------------------- /09 Clustering/sources/01 Clustering.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/09 Clustering/sources/01 Clustering.ipynb -------------------------------------------------------------------------------- /09 Clustering/sources/02 image clustering.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/09 Clustering/sources/02 image clustering.ipynb -------------------------------------------------------------------------------- /09 Clustering/sources/03 kobart_summarization.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/09 Clustering/sources/03 kobart_summarization.ipynb -------------------------------------------------------------------------------- /09 Clustering/sources/04 sk kobart clustering.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/09 Clustering/sources/04 sk kobart clustering.ipynb -------------------------------------------------------------------------------- /10 ETC/015 협업필터링 강화학습.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/015 협업필터링 강화학습.pdf -------------------------------------------------------------------------------- /10 ETC/data/202210_202210_연령별인구현황_월간.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/data/202210_202210_연령별인구현황_월간.csv -------------------------------------------------------------------------------- /10 ETC/data/CF_model/keras_metadata.pb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/data/CF_model/keras_metadata.pb -------------------------------------------------------------------------------- /10 ETC/data/CF_model/saved_model.pb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/data/CF_model/saved_model.pb -------------------------------------------------------------------------------- /10 ETC/data/CF_model/variables/variables.data-00000-of-00001: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/data/CF_model/variables/variables.data-00000-of-00001 -------------------------------------------------------------------------------- /10 ETC/data/CF_model/variables/variables.index: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/data/CF_model/variables/variables.index -------------------------------------------------------------------------------- /10 ETC/sources/01 Collaborate Filtering.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/sources/01 Collaborate Filtering.ipynb -------------------------------------------------------------------------------- /10 ETC/sources/02 TF-IDF.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/10 ETC/sources/02 TF-IDF.ipynb -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/README.md -------------------------------------------------------------------------------- /pandana_test.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kloud80/urban-data-mining/HEAD/pandana_test.ipynb --------------------------------------------------------------------------------