# 初学者的 TensorFlow 2.0 教程

1. 在 Colab中, 连接到Python运行环境： 在菜单条的右上方, 选择 CONNECT
2. 运行所有的代码块: 选择 Runtime > Run all

``````# 安装 TensorFlow

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')
])

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 [==============================] - 3s 2ms/step - loss: 0.2962 - accuracy: 0.9155
Epoch 2/5
1875/1875 [==============================] - 3s 2ms/step - loss: 0.1420 - accuracy: 0.9581
Epoch 3/5
1875/1875 [==============================] - 3s 2ms/step - loss: 0.1064 - accuracy: 0.9672
Epoch 4/5
1875/1875 [==============================] - 3s 2ms/step - loss: 0.0885 - accuracy: 0.9730
Epoch 5/5
1875/1875 [==============================] - 3s 2ms/step - loss: 0.0749 - accuracy: 0.9765
313/313 - 0s - loss: 0.0748 - accuracy: 0.9778
[0.07484959065914154, 0.9778000116348267]
```

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