printf("ho_tari\n");

#include #include "rational.h" int main() { Rational r1(3,5); Rational r2(2,7); std::cout

import os import numpy as np class Data(): def __init__(self, fname, ratio): f = open(fname) data = f.read() f.close() lines = data.split("\n") header = lines[0].split('.') lines = lines[1:] values = [line.split(",")[1:] for line in lines] self.float_data = np.array(values).astype('float32') self.data_length = self.float_data.shape[-1] self.ratio = ratio self.train_set_length = int(self.float_da..

from tensorflow.keras.preprocessing.image import ImageDataGenerator from tensorflow.keras import models, layers, optimizers from tensorflow.keras.callbacks import EarlyStopping import matplotlib.pyplot as plt from tensorflow.keras.applications import VGG16 # set image generators train_dir='./datasets/cats_and_dogs_small/train/' test_dir='./datasets/cats_and_dogs_small/test/' validation_dir='./da..

from tensorflow.keras.preprocessing.image import ImageDataGenerator from tensorflow.keras import models, layers, optimizers from tensorflow.keras.callbacks import EarlyStopping import matplotlib.pyplot as plt # set image generators train_dir='./datasets/cats_and_dogs_small/train/' test_dir='./datasets/cats_and_dogs_small/test/' validation_dir='./datasets/cats_and_dogs_small/validation/' train_da..

from tensorflow.keras.datasets import cifar10 from tensorflow.keras.utils import to_categorical from tensorflow.keras import models, layers from tensorflow.keras.callbacks import EarlyStopping import numpy as np import matplotlib.pyplot as plt # data loading (X_train, Y_train), (X_test, Y_test) = cifar10.load_data() # data preprocessing X_train = X_train / 255.0 X_test = X_test / 255.0 num_class..

Kaggle의 레드와인의 질에 대한 데이터셋(Red Wine Quality | Kaggle)을 이용하여 다음의 실험을 진행하라. (즉 kaggle에서 notebook을 열어도 좋고, data를 다운로드 받아 google colab을 사용해도 좋음.) 다음의 조건들을 만족하도록 코드를 구성하고, 실험하도록 한다. Perform the following experiment using the Kaggle's dataset on “the quality of red wine” (Red Wine Quality | Kaggle). You may open a notebook directly in kaggle, or user google colab with its downloaded data.) Write-down yo..