데이터분석2 [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 다음
