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python3 -m venv myenv
source myenv/bin/activate

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pip install tensorflow
pip install keras
pip install torch

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import tensorflow as tf
from tensorflow import keras
import numpy as np

# ¼ÓÔØÊý¾Ý¼¯
mnist = keras.datasets.mnist
(train_images, train_labels), (test_images, test_labels) = mnist.load_data()

# ¹éÒ»»¯
train_images = train_images / 255.0
test_images = test_images / 255.0

# ¹¹½¨Ä£×Ó
model = keras.Sequential([
    keras.layers.Flatten(input_shape=(28, 28)),
    keras.layers.Dense(128, activation=tf.nn.relu),
    keras.layers.Dense(10, activation=tf.nn.softmax)
])

# ±àÒëÄ£×Ó
model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

# ѵÁ·Ä£×Ó
model.fit(train_images, train_labels, epochs=10)

# ÆÀ¹ÀÄ£×Ó
test_loss, test_acc = model.evaluate(test_images, test_labels)
print('Test accuracy:', test_acc)

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