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	https://github.com/YYZ111/DeepLearning_Python#深度学习-deep-learning
这里	https://github.com/lawlite19/MachineLearning_Python
https://github.com/lawlite19/MachineLearning_Python	https://github.com/lawlite19/MachineLearning_Python
	https://github.com/YYZ111/DeepLearning_Python#一cnn卷积神经网络
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	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/CNN_11.png
	https://github.com/YYZ111/DeepLearning_Python#6cnn是如何工作的
https://www.zhihu.com/question/52668301	https://www.zhihu.com/question/52668301
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/CNN_12.png
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/CNN_13.png
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	https://github.com/YYZ111/DeepLearning_Python#7cnn的tensorflow实现
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https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Mnist_03_CNN/mnist_cnn.py	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Mnist_03_CNN/mnist_cnn.py
https://github.com/lawlite19/MachineLearning_TensorFlow	https://github.com/lawlite19/MachineLearning_TensorFlow
	https://github.com/YYZ111/DeepLearning_Python#8cnn公式推导
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	https://github.com/YYZ111/DeepLearning_Python#二权重初始化问题1_sigmoidtanhsoftsign激励函数
	https://github.com/YYZ111/DeepLearning_Python#1说明-1
http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf	http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf
这里	https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/Understanding%20the%20difficulty%20of%20training%20deep%20feedforward%20neural%20networks.pdf
https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/Understanding%20the%20difficulty%20of%20training%20deep%20feedforward%20neural%20networks.pdf	https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/Understanding%20the%20difficulty%20of%20training%20deep%20feedforward%20neural%20networks.pdf
	https://github.com/YYZ111/DeepLearning_Python#2实验
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_01.png
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	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_03.png
	https://github.com/YYZ111/DeepLearning_Python#3初试化方法公式推导
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_04.png
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	https://github.com/YYZ111/DeepLearning_Python#三权重初始化问题2_relu激励函数
	https://github.com/YYZ111/DeepLearning_Python#1说明-2
https://arxiv.org/pdf/1502.01852v1.pdf	https://arxiv.org/pdf/1502.01852v1.pdf
这里	https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/Delving%20Deep%20into%20Rectifiers%20Surpassing%20Human-Level%20Performance%20on%20ImageNet%20Classification%EF%BC%88S%E5%9E%8B%E5%87%BD%E6%95%B0%E6%9D%83%E9%87%8D%E5%88%9D%E5%A7%8B%E5%8C%96%EF%BC%89.pdf
https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/Delving%20Deep%20into%20Rectifiers%20Surpassing%20Human-Level%20Performance%20on%20ImageNet%20Classification%EF%BC%88S%E5%9E%8B%E5%87%BD%E6%95%B0%E6%9D%83%E9%87%8D%E5%88%9D%E5%A7%8B%E5%8C%96%EF%BC%89.pdf	https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/Delving%20Deep%20into%20Rectifiers%20Surpassing%20Human-Level%20Performance%20on%20ImageNet%20Classification%EF%BC%88S%E5%9E%8B%E5%87%BD%E6%95%B0%E6%9D%83%E9%87%8D%E5%88%9D%E5%A7%8B%E5%8C%96%EF%BC%89.pdf
	https://github.com/YYZ111/DeepLearning_Python#2reluprelu激励函数
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_06.png
	https://camo.githubusercontent.com/795f0b688cec9d9f224e81c051d97a3e04a8c7f5f9afec9b5bfd62cfe2351df0/687474703a2f2f6c617465782e636f6465636f67732e636f6d2f6769662e6c617465783f253543666e5f636d25323025323425323466253238253742795f692537442532392532302533442532302535436d617825323025323830253243253742795f692537442532392532302b253230253742615f692537442535436d696e25323025323830253243253742795f69253744253239253234253234
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_07.png
	https://github.com/YYZ111/DeepLearning_Python#3前向传播推导
	https://camo.githubusercontent.com/e84d4a262404d1f438fa6871917ef450d48194e6f4b5d9eabc2686a3044b5f96/687474703a2f2f6c617465782e636f6465636f67732e636f6d2f6769662e6c617465783f253543666e5f636d253230253234253234253742795f6c253744253230253344253230253742575f6c253744253742253742253543726d253742782537442537445f6c2537442532302b253230253742625f6c253744253234253234
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	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_09.png
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	https://github.com/YYZ111/DeepLearning_Python#4反向传播推导
	https://camo.githubusercontent.com/ca2272d84ff4c2ea28519de9728f5e55567e0bcbc832ceda6b7701e6362f1e3b/687474703a2f2f6c617465782e636f6465636f67732e636f6d2f6769662e6c617465783f253543666e5f636d25323025323425323425354344656c7461253230253742253742253543726d253742782537442537445f6c25374425323025334425323025354377696465686174253230253742253742575f6c25374425374425354344656c7461253230253742795f6c253744253234253234
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	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_10.png
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	https://github.com/YYZ111/DeepLearning_Python#5正向和反向传播讨论实验和prelu函数
	https://camo.githubusercontent.com/db99a2e4815dd5727fc9b6f5ebe04d65e687e4023146bffc9d6cf722316329e2/687474703a2f2f6c617465782e636f6465636f67732e636f6d2f6769662e6c617465783f253543666e5f636d25323025323425323425354370726f642535436c696d6974735f2537426c253230253344253230322537442535454c253230253742253742312532302535436f76657225323032253744253543776964656861742532302537422537426e5f6c253744253744566172253542253742775f6c25374425354425374425323025334425323031253234253234
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_11.png
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/Weights_initialization_12.png
	https://camo.githubusercontent.com/08b4342b05f3e70b9ebd4890e27df6d922f107b45d339c88498ae5d0a12a3fce/687474703a2f2f6c617465782e636f6465636f67732e636f6d2f6769662e6c617465783f253543666e5f636d253230253234253234253742312532302535436f76657225323032253744253238312532302b25323025374261253545322537442532392537426e5f6c253744566172253542253742775f6c25374425354425323025334425323031253234253234
	https://github.com/YYZ111/DeepLearning_Python#四batch-normalizationbn批标准化
	https://github.com/YYZ111/DeepLearning_Python#1说明-3
http://jmlr.org/proceedings/papers/v37/ioffe15.pdf	http://jmlr.org/proceedings/papers/v37/ioffe15.pdf
这里	https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/%EF%BC%88BN%EF%BC%89Batch%20Normalization%20Accelerating%20Deep%20Network%20Training%20by%20Reducing%20Internal%20Covariate%20Shift.pdf
https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/%EF%BC%88BN%EF%BC%89Batch%20Normalization%20Accelerating%20Deep%20Network%20Training%20by%20Reducing%20Internal%20Covariate%20Shift.pdf	https://github.com/lawlite19/DeepLearning_Python/blob/master/paper/%EF%BC%88BN%EF%BC%89Batch%20Normalization%20Accelerating%20Deep%20Network%20Training%20by%20Reducing%20Internal%20Covariate%20Shift.pdf
	https://github.com/YYZ111/DeepLearning_Python#2论文概述
	https://github.com/YYZ111/DeepLearning_Python#3bn思路
	https://camo.githubusercontent.com/d8af08772a45d2359f17e900ae2a66c9f5339d83a7517452fe35f1ae082d979d/687474703a2f2f6c617465782e636f6465636f67732e636f6d2f6769662e6c617465783f2532342532342535437769646568617425323078253742253543726d2537422532302533442532302537442537444e253742253543726d2537426f726d253744253744253238253742253543726d25374278253744253744253243253543636869253230253239253234253234
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	https://github.com/YYZ111/DeepLearning_Python#4bn网络的训练和推断
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	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/BN_02.png
	https://github.com/YYZ111/DeepLearning_Python#5实验
	https://github.com/YYZ111/DeepLearning_Python/blob/master/images/BN_03.png
	https://github.com/YYZ111/DeepLearning_Python#五rnn和lstm_01基础
我的博客	http://lawlite.me/2017/06/14/RNN-%E5%BE%AA%E7%8E%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C%E5%92%8CLSTM-01%E5%9F%BA%E7%A1%80/
查看这里	http://lawlite.me/2017/06/14/RNN-%E5%BE%AA%E7%8E%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C%E5%92%8CLSTM-01%E5%9F%BA%E7%A1%80/
查看这里	http://lawlite.me/2017/06/21/RNN-LSTM%E5%BE%AA%E7%8E%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C-03Tensorflow%E8%BF%9B%E9%98%B6%E5%AE%9E%E7%8E%B0/
Readme	https://github.com/YYZ111/DeepLearning_Python#readme-ov-file
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