"Machine Learning"의 두 판 사이의 차이
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잔글 (→general) |
잔글 (→general) |
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39번째 줄: | 39번째 줄: | ||
* [[Exponential Linear Unit]] | * [[Exponential Linear Unit]] | ||
* [[Neural net이 working하지 않는 37가지 이유]] | * [[Neural net이 working하지 않는 37가지 이유]] | ||
− | * [ | + | * [[deconvolution]] |
* [[Sparse coding]] | * [[Sparse coding]] |
2017년 7월 26일 (수) 16:58 판
by themes
ril
- https://medium.com/technologymadeeasy/the-best-explanation-of-convolutional-neural-networks-on-the-internet-fbb8b1ad5df8
- http://nmhkahn.github.io/Casestudy-CNN
- https://stats.stackexchange.com/questions/205150/how-do-bottleneck-architectures-work-in-neural-networks
- https://www.quora.com/What-exactly-is-the-degradation-problem-that-Deep-Residual-Networks-try-to-alleviate
- dl with torch
- bias 붙여버리면 inv는 어케 구하나? D=0되지 않나? 구할필요 없나?
- pytorch examples
- Identity Mappings in Deep Residual Networks arXiv:1603.05027