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[C2W1] Improving Deep Neural Networks : Practical aspects of Deep Learning

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吴恩达《深度学习》-第二门课 (Improving Deep Neural Networks:Hyperparameter tuning, Regularization and Optimization)-第一周：深度学习的实践层面 (Practical aspects of Deep Learning) -课程笔记

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吴恩达《深度学习》-课后测验-第二门课 (Improving Deep Neural Networks:Hyperparameter tuning, Regularization and Optimization)-Week 1 - Practical aspects of deep learning（第一周测验 - 深度学习的实践）

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课程二(Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization)，第一周（Practical aspects of Deep Learning） —— 4.Programming assignments:Gradient Checking

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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization（第一周）深度学习的实践层面 (Practical aspects of Deep Learning)

1. Setting up your Machine Learning Application 1.1 训练,验证,测试集(Train / Dev / Test sets) 1.2 Bias/Variance(偏差和方差) 高偏差(high bias)称为"欠拟合"(underfitting), 练集误差与验证集误差都高. 高方差(high variance)称为过拟合(overfitting), 训练集误差很低而验证集误差很高. 1.3 Basic "recipe"…

Practical aspects of deep learning

If your Neural Network model seems to have high variance, what of the following would be promising things to try? Make the Neural Network deeper N Get more training data Y Get more test data N Add regularization Y Increase the number of units in each…

[C3] Andrew Ng - Neural Networks and Deep Learning

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Why Deep Learning Works – Key Insights and Saddle Points

Why Deep Learning Works – Key Insights and Saddle Points A quality discussion on the theoretical motivations for deep learning, including distributed representation, deep architecture, and the easily escapable saddle point. By Matthew Mayo. This post…

【深度学习Deep Learning】资料大全

最近在学深度学习相关的东西,在网上搜集到了一些不错的资料,现在汇总一下: Free Online Books  by Yoshua Bengio, Ian Goodfellow and Aaron Courville Neural Networks and Deep Learning42 by Michael Nielsen Deep Learning27 by Microsoft Research Deep Learning Tutorial23 by LISA lab, University…