import tensorflow as tf
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
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=1, validation_split=0.2)
model.evaluate(x_test, y_test)
标签：layers,keras,test,train,字体,tf,手写,model From： https://www.cnblogs.com/chinasoft/p/17131783.html