使用Keras加载MNIST时尚数据集是一种常见的机器学习任务,旨在训练一个模型来识别时尚物品的图像。下面是对这个问题的完善且全面的答案:
在使用Keras加载MNIST时尚数据集时,可以按照以下步骤进行:
import tensorflow as tf
from tensorflow import keras
fashion_mnist = keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
train_images = train_images / 255.0
test_images = test_images / 255.0
model = keras.Sequential([
keras.layers.Flatten(input_shape=(28, 28)),
keras.layers.Dense(128, activation='relu'),
keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
metrics=['accuracy'])
model.fit(train_images, train_labels, epochs=10)
test_loss, test_acc = model.evaluate(test_images, test_labels, verbose=2)
print('\nTest accuracy:', test_acc)
以上是使用Keras加载MNIST时尚数据集的完善且全面的答案。
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