better_deep_learning_mini_course.pdf
本文档讲述了如何构建更好的深度学习网络框架,batch size对预测误差和学习率的影响,如何动态修改学习率(Learning Rate Schedule),Batch Normalization对神经网络训练的加速,Weight Regularization对过拟合的影响,增加网络噪声提供网络的鲁棒性,提前终止也能抑制过拟合。
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