Deep learning II - I Practical aspects of deep learning - other regularization methods 其他正則化方法
Other regularization methods 其他正則化方法 Data augmentation 通過變化已有數據，來豐富數據集，通過使用更大的數據集來防止過擬合發生 Early stopping 通過觀察dev set的表現，提前終止訓練，從而得到不是很大的 w w 值，從而產生類似於 L2 L 2 正則化的效果
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相關文章
- 1. Deep learning II - I Practical aspects of deep learning - Dropout regularization 隨機失活正則化
- 2. Deep learning II - I Practical aspects of deep learning - 正則化如何較少過擬合
- 3. Deep learning II - I Practical aspects of deep learning - Normalizing inputs 輸入歸一化
- 4. Deep learning II - I Practical aspects of deep learning - Understanding dropout 理解隨機失活正則化
- 5. [coursera/ImprovingDL/week1]Practical aspects of Deep Learning(summary&question)
- 6. Deep learning II - I Practical aspects of deep learning - Regularizing your neural network 神經網絡範數正則化
- 7. 007 Practical aspects of Deep Learning
- 8. Deep learning II - I Practical aspects of deep learning - Vanishing/Exploring gradients 梯度消失/爆炸
- 9. 深度神經網絡優化（一）- Practical aspects of Deep Learning
- 10. 【吳恩達深度學習筆記】2.1 Practical aspects of Deep Learning