import tensorflow as tf
from tensorflow.keras import layers, models, datasets

# データセットの読み込み
(x_train, y_train), (x_test, y_test) = datasets.mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

# modelを準備する
model = models.Sequential([
    layers.Flatten(input_shape=(28, 28)),
    layers.Dense(128, activation='relu'),
    layers.Dropout(0.2),
    layers.Dense(10, activation=”softmax”)
])

# modelをコンパイルする
model.compile(optimizer='adam', loss=”sparse_categorical_crossentropy”, metrics=['accuracy'])

# modelの学習
model.fit(x_train, y_train, epochs=5)

# 学習結果確認
model.evaluate(x_test, y_test, verbose=1)