1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | import tensorflow as tf from tensorflow import keras import numpy as np import matplotlib.pyplot as plt from tensorflow.keras import datasets, layers, models fashion_mnist = keras.datasets.fashion_mnist (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data() plt.imshow(train_images[0]) train_images = train_images / 255.0 test_images = test_images / 255.0 model = models.Sequential() model.add(layers.Flatten(input_shape=(28, 28))) model.add(layers.Dense(128, activation='relu')) model.add(layers.Dense(10, activation='softmax')) model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) model.fit(train_images, train_labels, epochs=5) | cs |