Deep learning II - I Practical aspects of deep learning - Normalizing inputs 輸入歸一化
Normalizing inputs 輸入歸一化 1. 輸入歸一化能夠加快訓練速度 2. 首先，將輸入減去均值 μ=1m∑i=1mx(i) μ = 1 m ∑ i = 1 m x ( i ) x:=x−μ x := x − μ 3. 其次，方差歸一化 σ2=1m∑i=1mx(i)∗∗2(∗∗meanselement−square) σ 2 = 1 m ∑ i = 1 m x ( i ) ∗ ∗ 2
相關文章
- 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 - 正則化如何較少過擬合
- 4. Deep learning II - I Practical aspects of deep learning - Understanding dropout 理解隨機失活正則化
- 5. Deep learning II - I Practical aspects of deep learning - other regularization methods 其他正則化方法
- 6. Deep learning II - I Practical aspects of deep learning - Dropout regularization 隨機失活正則化
- 7. Deep learning II - I Practical aspects of deep learning - Vanishing/Exploring gradients 梯度消失/爆炸
- 8. 深度神經網絡優化（一）- Practical aspects of Deep Learning
- 9. Deep learning II - I Practical aspects of deep learning - Regularizing your neural network 神經網絡範數正則化
- 10. 【吳恩達深度學習筆記】2.1 Practical aspects of Deep Learning
- 更多相關文章...
- • C# 文件的輸入與輸出 - C#教程
- • ionic 表單和輸入框 - ionic 教程
- • Java Agent入門實戰（一）-Instrumentation介紹與使用
- • 算法總結-歸併排序
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
- 1. 在windows下的虛擬機中,安裝華爲電腦的deepin操作系統
- 2. 強烈推薦款下載不限速解析神器
- 3. 【區塊鏈技術】孫宇晨：區塊鏈技術帶來金融服務的信任變革
- 4. 搜索引起的鏈接分析-計算網頁的重要性
- 5. TiDB x 微衆銀行 | 耗時降低 58%，分佈式架構助力實現普惠金融
- 6. 《數字孿生體技術白皮書》重磅發佈（附完整版下載）
- 7. 雙十一「避坑」指南：區塊鏈電子合同爲電商交易保駕護航！
- 8. 區塊鏈產業，怎樣「鏈」住未來？
- 9. OpenglRipper使用教程
- 10. springcloud請求一次好用一次不好用zuul Name or service not known
歡迎關注本站公眾號,獲取更多信息
相關文章
- 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 - 正則化如何較少過擬合
- 4. Deep learning II - I Practical aspects of deep learning - Understanding dropout 理解隨機失活正則化
- 5. Deep learning II - I Practical aspects of deep learning - other regularization methods 其他正則化方法
- 6. Deep learning II - I Practical aspects of deep learning - Dropout regularization 隨機失活正則化
- 7. Deep learning II - I Practical aspects of deep learning - Vanishing/Exploring gradients 梯度消失/爆炸
- 8. 深度神經網絡優化（一）- Practical aspects of Deep Learning
- 9. Deep learning II - I Practical aspects of deep learning - Regularizing your neural network 神經網絡範數正則化
- 10. 【吳恩達深度學習筆記】2.1 Practical aspects of Deep Learning