원문 Building Seq2Seq LSTM with Luong Attention in Keras for Time Series Forecasting | by Huangwei Wieniawska | Level Up Coding (gitconnected.com) Building Seq2Seq LSTM with Luong Attention in Keras for Time Series Forecasting Do you want to try some other methods to solve your forecasting problem rather than traditional regression? There are many neural network… levelup.gitconnected.com 시계열 예측을 위..

import keras fm = keras.datasets.fashion_mnist (trainImage, trainLabel), (testImage, testLabel)= fm.load_data() import pandas as pd import numpy as np from keras.preprocessing.image import * from keras.utils import to_categorical from sklearn.model_selection import train_test_split import matplotlib.pyplot as plt import random import os # 검증데이터 분리 trainImage, valImage= train_test_split(trainImag..

데이터 이미지증식기 클래스 불러오기 from keras.preprocessing.image import array_to_img, img_to_array, load_img # 이미지 증식 augGen=ImageDataGenerator(rescale=1./255, rotation_range=15, width_shift_range=0.1, height_shift_range=0.1, shear_range=0.5, zoom_range=[0.8,2.0], horizontal_flip=True, vertical_flip=True, fill_mode='nearest') ImageDataGenerator 내 속성이 랜덤으로 적용됌. rotation_range: 회전, 90(0-90)사이 랜덤 width_shift_ran..