小结

在这一节里，给读者介绍了几种经典的图像分类模型，分别是LeNet, AlexNet, VGG, GoogLeNet和ResNet，并将它们应用到眼疾筛查数据集上。除了LeNet不适合大尺寸的图像分类问题之外，其它几个模型在此数据集上损失函数都能显著下降，在验证集上的预测精度在90%左右。如果读者有兴趣的话，可以进一步调整学习率和训练轮数等超参数，观察是否能够得到更高的精度。

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