Coursera-吴恩达-深度学习-改善深层神经网络：超参数调试、正则化以及优化-week1-测验

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Coursera吴恩达深度学习课程，第二课改善深层神经网络：超参数调试、正则化以及优化(Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization)

第一周：深度学习的实用层面(Practical aspects of Deep Learning)

部分的测验，题目及答案截图。

 

 

Example的数量很多，不需要像传统的比例。因为test需要的量不需要那么多。

 

 

 

 

dropout 只在training 的过程才做。

Do not apply dropout (do not randomly eliminate units) and do not keep the 1/keep_prob factor in the calculations used in training

only use dropout during training. Don't use dropout (randomly eliminate nodes) during test time.

only during training time, divide each dropout layer by keep_prob to keep the same expected value for the activations.