2019-12-08 21:00:06 +08:00

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import tensorflow as tf
# https://tensorflow.google.cn/tutorials/quickstart/beginner
mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0 # 将样本从整数转换为浮点数准确度从93%上升到97%。
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(128, activation='relu'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10, activation='softmax')
])
model.compile(
optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy']
)
model.fit(x_train, y_train, epochs=5)
model.evaluate(x_test, y_test, verbose=2)