python7 MuLife - Music Video Generator 중간 점검 https://docs.google.com/presentation/d/1EVylBFpbJzng-LSOxG37c2SP2AVR4JKXGgaY_-yv4aI/edit?usp=sharing MuLife - 노지민 Music is our Life: MuLife Music Generator With Riffusion AI Model Text Recommend Generator Our Music Playlists docs.google.com 2023. 1. 23. [CNN] Traffic Signs Classification with Explanation Traffic Signs Preprocessed with CNN https://www.kaggle.com/code/emilyjiminroh/cnn-traffic-signs-classification-with-explanation [ ✒️Description ] Sichkar V. N. Real time detection and classification of traffic signs based on YOLO version 3 algorithm. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2020, vol. 20, no. 3, pp. 418–424. DOI: 10.17586/2226-1494-2020.. 2022. 5. 27. [EDA & Visualization] Netflix Dataset https://www.kaggle.com/code/emilyjiminroh/netflix-dataset-eda-visualization-collabo-ver # This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python # For example, here's several helpful packages to load import numpy as np # linear algebra import pandas as pd # data processing, CSV fil.. 2022. 5. 27. [EDA] Home-credit-default-risk Dataset https://www.kaggle.com/code/emilyjiminroh/eda-visualization-home-credit-default-risk 대출 상환 예측 데이터 https://www.kaggle.com/c/home-credit-default-risk 고객 정보를 기반으로 대출 상환 가능 여부 예측(0이면 상환 가능, 1이면 상환 불가능) 메인 테이블(application_train, application_test)만 사용 예정 linkcode 많은 사람들이 신용 기록이 부족하거나 존재하지 않아 대출을 받기 위해 애쓴다. 그리고 불행하게도, 이 인구는 종종 신뢰할 수 없는 대출자들에 의해 이용된다. 홈 크레딧은 긍정적이고 안전한 대출 경험을 제공함으로써 비은행 인구에 대한 금융 포함을 확대하.. 2022. 5. 27. [EDA & Visualization] San_Francisco Data https://www.kaggle.com/code/emilyjiminroh/eda-visualization-san-francisco-notebook # This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python # For example, here's several helpful packages to load import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O.. 2022. 3. 31. [CNN] Fashion-Mnist-Data https://www.kaggle.com/code/emilyjiminroh/cnn-fashion-mnist Import 라이브러리 In [1]: import sys import os In [2]: from keras.datasets import mnist from keras.utils import np_utils # 원-핫 인코딩. np_utils.to_categorical(클래스, 클래스의 개수) In [3]: from keras.models import Sequential from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPooling2D from keras.callbacks import ModelCheckpoint, EarlyStopping.. 2022. 3. 31. 이전 1 2 다음
