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在此项目中,将对 [CIFAR-10 数据集](https://www.cs.toronto.edu/~kriz/cifar.html) 中的图片进行分类。该数据集包含飞机、猫狗和其他物体。你需要预处理这些图片,然后用所有样本训练一个卷积神经网络。图片需要标准化(normalized),标签需要采用 one-hot 编码。应用所学的知识构建卷积的、最大池化(max pooling)、丢弃(dropout)和完全连接(fully connected)的层。最后,需要在样本图片上看到神经网络的预测结果。

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