CNN ResNet for FASHION MNIST with Tensorflow CNN ResNet for FASHION MNIST with Tensorflow¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST) FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35 FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36 FASHION MNIST with Python (DAY 3) : http://deepstat.tistory.com/37 FASHION MNIST wi..
'ggmap'을 이용해서 대구 메트로 시각화하기 - 2일차 함께 보기 목적 필요한 패키지 데이터 전국도시철도역사정보표준데이터.csv ("df_역"이라 명명) 대구도시철도공사_일별시간별승하차인원_20171231.csv ("df_승하차인원"이라 명명) 데이터 전처리 df_역에서 대구 메트로 정보만 가져오기. 대구 지도에 지하철역 뿌려보기 df_승차자인원을 조금 더 다루기 쉬운 형태로 정리하기. 가공한 데이터 2개 (df_대구메트로역, df_승하차_melted)를 합치자. 환승역 합치기 합치기 전에 살펴보기 반월당역 신남역 다시 합치기 지도에 뿌리기 2017년 12월 24일 오후 6시에서 7시 이용현황 (다시 그리기) 2017년 요일별 이용현황 2017년 시간대별 이용현황 (아침, 점심, 저녁) 정리, 반성 ..
'ggmap'을 이용해서 대구 메트로 시각화하기 - 1일차 목적 필요한 패키지 데이터 전국도시철도역사정보표준데이터.csv ("df_역"이라 명명) 데이터 정보 대구도시철도공사_일별시간별승하차인원_20171231.csv ("df_승하차인원"이라 명명) 데이터 정보 데이터 전처리 df_역에서 대구 메트로 정보만 가져오기. df_승차자인원을 조금 더 다루기 쉬운 형태로 정리하기. 가공한 데이터 2개 (df_대구메트로역, df_승하차_melted)를 합치자. 지도에 뿌리기 대구지도 가져오기 (여러 테마) 대구 지도에 지하철 역 뿌리기 2017년 12월 24일 오후 6시에서 7시 이용현황 정리, 반성 및 Future work 목적 대구 메트로 상하차 정보가 인터넷에 공개되어있는데, 이를 기반으로 지도에 시각화해보..
CNN for FASHION MNIST with Tensorflow (test accuracy 0.9308) CNN for FASHION MNIST with Tensorflow (test accuracy 0.9308)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST) FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35 FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36 FASHION MNIST with Python (DAY 3) : http://deepstat..
FASHION_MNIST_DAY10_with_Python FASHION MNIST with Python (DAY 10)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST)FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36FASHION MNIST with Python (DAY 3) : http://deepstat.tistory.com/37FASHION MNIST with Python (DAY 4) : http://..
FASHION_MNIST_DAY9_with_Python FASHION MNIST with Python (DAY 9)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST)FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36FASHION MNIST with Python (DAY 3) : http://deepstat.tistory.com/37FASHION MNIST with Python (DAY 4) : http://de..
FASHION_MNIST_DAY8_with_Python FASHION MNIST with Python (DAY 8)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST)FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36FASHION MNIST with Python (DAY 3) : http://deepstat.tistory.com/37FASHION MNIST with Python (DAY 4) : http://de..
FASHION_MNIST_DAY7_with_Python FASHION MNIST with Python (DAY 7)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST)FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36FASHION MNIST with Python (DAY 3) : http://deepstat.tistory.com/37FASHION MNIST with Python (DAY 4) : http://de..
FASHION_MNIST_DAY6_with_Python FASHION MNIST with Python (DAY 6)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST)FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36FASHION MNIST with Python (DAY 3) : http://deepstat.tistory.com/37FASHION MNIST with Python (DAY 4) : http://de..
FASHION_MNIST_DAY5_with_Python FASHION MNIST with Python (DAY 5)¶DATA SOURCE : https://www.kaggle.com/zalando-research/fashionmnist (Kaggle, Fashion MNIST)FASHION MNIST with Python (DAY 1) : http://deepstat.tistory.com/35FASHION MNIST with Python (DAY 2) : http://deepstat.tistory.com/36FASHION MNIST with Python (DAY 3) : http://deepstat.tistory.com/37FASHION MNIST with Python (DAY 4) : http://de..