【機械学習】TensorFlowのチュートリアルを実行する

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=5)
 
model.evaluate(x_test,  y_test, verbose=2)

Epoch 1/5
1875/1875 [==============================] - 5s 3ms/step - loss: 0.2975 - accuracy: 0.9138
Epoch 2/5
1875/1875 [==============================] - 4s 2ms/step - loss: 0.1415 - accuracy: 0.9579
Epoch 3/5
1875/1875 [==============================] - 4s 2ms/step - loss: 0.1044 - accuracy: 0.9690
Epoch 4/5
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0877 - accuracy: 0.9729
Epoch 5/5
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0734 - accuracy: 0.9769
313/313 - 1s - loss: 0.0797 - accuracy: 0.9743 - 627ms/epoch - 2ms/step