Keras基于单层神经网络实现手写数字识别

 1 import tensorflow as tf
 2 import matplotlib.pyplot as plt
 3 import numpy as np
 4 
 5 # 导入数据
 6 mnist = np.load('mnist.npz')
 7 x_train, y_train = mnist['x_train'], mnist['y_train']
 8 x_test, y_test = mnist['x_test'], mnist['y_test']
 9 # 归一化处理
10 x_train, x_test = x_train / 255, x_test / 255
11 model = tf.keras.models.Sequential([
12     tf.keras.layers.Flatten(),
13     tf.keras.layers.Dense(128, activation='relu'),
14     tf.keras.layers.Dense(10, activation='softmax')
15 ])
16 model.compile(
17     optimizer='adam',
18     loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),
19     metrics=['sparse_categorical_accuracy']
20 )
21 model.fit(x_train, y_train, batch_size=32, epochs=5, validation_data=(x_test, y_test), validation_freq=1)
22 model.summary()
23 # 保存模型
24 # model.save('mnist_model.h5')