Deep learning II - I Practical aspects of deep learning - Normalizing inputs 输入归一化

时间 2020-12-20

标签输入归一化繁體版

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Normalizing inputs 输入归一化 1. 输入归一化能够加快训练速度 2. 首先，将输入减去均值 μ=1m∑i=1mx(i) μ = 1 m ∑ i = 1 m x ( i ) x:=x−μ x := x − μ 3. 其次，方差归一化 σ2=1m∑i=1mx(i)∗∗2(∗∗meanselement−square) σ 2 = 1 m ∑ i = 1 m x ( i ) ∗ ∗ 2

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1. [coursera/ImprovingDL/week1]Practical aspects of Deep Learning(summary&question)
2. 007 Practical aspects of Deep Learning
3. Deep learning II - I Practical aspects of deep learning - 正则化如何较少过拟合
4. Deep learning II - I Practical aspects of deep learning - Understanding dropout 理解随机失活正则化
5. Deep learning II - I Practical aspects of deep learning - other regularization methods 其他正则化方法
6. Deep learning II - I Practical aspects of deep learning - Dropout regularization 随机失活正则化
7. Deep learning II - I Practical aspects of deep learning - Vanishing/Exploring gradients 梯度消失/爆炸
8. 深度神经网络优化（一）- Practical aspects of Deep Learning
9. Deep learning II - I Practical aspects of deep learning - Regularizing your neural network 神经网络范数正则化
10. 【吴恩达深度学习笔记】2.1 Practical aspects of Deep Learning

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