本文总结了深度学习模型训练中常见的11个错误，包括数据标准化、结果检查、数据预处理等，帮助读者避免这些陷阱，提升模型效果。
转自：https://blog.youkuaiyun.com/wangdongwei0/article/details/81256423
没错的，又是传送门
大概分为以下几点：
1、You Forgot to Normalize Your Data
2、You Forgot to Check your Results
3、You Forgot to Preprocess Your Data
4、You Forgot to use any Regularization
5、You Used a too Large Batch Size
6、You Used an Incorrect Learning Rate
7、You Used the Wrong Activation Function on the Final Layer
8、Your Network contains Bad Gradients
9、You Initialized your Network Weights Incorrectly
10、You Used a Network that was too Deep
11、You Used the Wrong Number of Hidden Units
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