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Description: TensorFlow学习. Contribute to lyc10031/MachineLearning_TensorFlow development by creating an account on GitHub.

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README	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow
MIT license	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#tensorflow
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#目录
TensorFlow	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#tensorflow
目录	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E7%9B%AE%E5%BD%95
一、TensorFlow介绍	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%B8%80-tensorflow%E4%BB%8B%E7%BB%8D
1、什么是TensorFlow	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E4%BB%80%E4%B9%88%E6%98%AFtensorflow
2、TensorFlow强大之处	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-tensorflow%E5%BC%BA%E5%A4%A7%E4%B9%8B%E5%A4%84
3、安装TensorFlow	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E5%AE%89%E8%A3%85tensorflow
二、TensorFlow基础架构	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%BA%8C-tensorflow%E5%9F%BA%E7%A1%80%E6%9E%B6%E6%9E%84
1、处理结构	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E5%A4%84%E7%90%86%E7%BB%93%E6%9E%84
2、一个例子	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E4%B8%80%E4%B8%AA%E4%BE%8B%E5%AD%90
3、Session会话控制	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-session%E4%BC%9A%E8%AF%9D%E6%8E%A7%E5%88%B6
4、变量	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4-%E5%8F%98%E9%87%8F
5、传入值	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5-%E4%BC%A0%E5%85%A5%E5%80%BC
三、定义一个神经网络	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%B8%89-%E5%AE%9A%E4%B9%89%E4%B8%80%E4%B8%AA%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C
1、添加层函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E6%B7%BB%E5%8A%A0%E5%B1%82%E5%87%BD%E6%95%B0
2、构建神经网络	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E6%9E%84%E5%BB%BA%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C
3、可视化结果	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E5%8F%AF%E8%A7%86%E5%8C%96%E7%BB%93%E6%9E%9C
四、TensorFlow可视化	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%9B%9B-tensorflow%E5%8F%AF%E8%A7%86%E5%8C%96
1、TensorFlow的可视化工具，可视化神经网路额结构	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-tensorflow%E7%9A%84%E5%8F%AF%E8%A7%86%E5%8C%96%E5%B7%A5%E5%85%B7%E5%8F%AF%E8%A7%86%E5%8C%96%E7%A5%9E%E7%BB%8F%E7%BD%91%E8%B7%AF%E9%A2%9D%E7%BB%93%E6%9E%84
2、可视化训练过程	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E5%8F%AF%E8%A7%86%E5%8C%96%E8%AE%AD%E7%BB%83%E8%BF%87%E7%A8%8B
五、手写数字识别_1	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%BA%94-%E6%89%8B%E5%86%99%E6%95%B0%E5%AD%97%E8%AF%86%E5%88%AB_1
1、说明	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E8%AF%B4%E6%98%8E
2、代码实现	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E4%BB%A3%E7%A0%81%E5%AE%9E%E7%8E%B0
六、手写数字识别_2	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%85%AD-%E6%89%8B%E5%86%99%E6%95%B0%E5%AD%97%E8%AF%86%E5%88%AB_2
1、说明	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E8%AF%B4%E6%98%8E
2、代码	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E4%BB%A3%E7%A0%81
七、手写数字识别_3_CNN卷积神经网络	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%B8%83-%E6%89%8B%E5%86%99%E6%95%B0%E5%AD%97%E8%AF%86%E5%88%AB_3_cnn%E5%8D%B7%E7%A7%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C
1、说明	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E8%AF%B4%E6%98%8E
2、代码实现	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E4%BB%A3%E7%A0%81%E5%AE%9E%E7%8E%B0
3、运行结果	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E8%BF%90%E8%A1%8C%E7%BB%93%E6%9E%9C
八、保存和提取神经网络	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%85%AB-%E4%BF%9D%E5%AD%98%E5%92%8C%E6%8F%90%E5%8F%96%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C
1、保存	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E4%BF%9D%E5%AD%98
2、提取	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E6%8F%90%E5%8F%96
以下来自，使用	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%BB%A5%E4%B8%8B%E6%9D%A5%E8%87%AA%E4%BD%BF%E7%94%A8
九、线性模型Linear Model	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%B9%9D-%E7%BA%BF%E6%80%A7%E6%A8%A1%E5%9E%8Blinear-model
1、加载MNIST数据集，并输出信息	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E5%8A%A0%E8%BD%BDmnist%E6%95%B0%E6%8D%AE%E9%9B%86%E5%B9%B6%E8%BE%93%E5%87%BA%E4%BF%A1%E6%81%AF
2、绘制9张图像	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E7%BB%98%E5%88%B69%E5%BC%A0%E5%9B%BE%E5%83%8F
3、定义要训练的模型	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E5%AE%9A%E4%B9%89%E8%A6%81%E8%AE%AD%E7%BB%83%E7%9A%84%E6%A8%A1%E5%9E%8B
4、定义函数进行bgd训练	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4-%E5%AE%9A%E4%B9%89%E5%87%BD%E6%95%B0%E8%BF%9B%E8%A1%8Cbgd%E8%AE%AD%E7%BB%83
5、定义输出准确度的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5-%E5%AE%9A%E4%B9%89%E8%BE%93%E5%87%BA%E5%87%86%E7%A1%AE%E5%BA%A6%E7%9A%84%E5%87%BD%E6%95%B0
6、定义绘制错误预测的图片函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#6-%E5%AE%9A%E4%B9%89%E7%BB%98%E5%88%B6%E9%94%99%E8%AF%AF%E9%A2%84%E6%B5%8B%E7%9A%84%E5%9B%BE%E7%89%87%E5%87%BD%E6%95%B0
7、定义可视化权重的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#7-%E5%AE%9A%E4%B9%89%E5%8F%AF%E8%A7%86%E5%8C%96%E6%9D%83%E9%87%8D%E7%9A%84%E5%87%BD%E6%95%B0
8、定义输出的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#8-%E5%AE%9A%E4%B9%89%E8%BE%93%E5%87%BA%E7%9A%84%E5%87%BD%E6%95%B0
十：CNN	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%8D%81cnn
1、定义CNN所需要的变量	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E5%AE%9A%E4%B9%89cnn%E6%89%80%E9%9C%80%E8%A6%81%E7%9A%84%E5%8F%98%E9%87%8F
2、初始化weights和biases的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E5%88%9D%E5%A7%8B%E5%8C%96weights%E5%92%8Cbiases%E7%9A%84%E5%87%BD%E6%95%B0
3、定义卷积操作和池化（如果使用的话）的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E5%AE%9A%E4%B9%89%E5%8D%B7%E7%A7%AF%E6%93%8D%E4%BD%9C%E5%92%8C%E6%B1%A0%E5%8C%96%E5%A6%82%E6%9E%9C%E4%BD%BF%E7%94%A8%E7%9A%84%E8%AF%9D%E7%9A%84%E5%87%BD%E6%95%B0
4、定义将卷积层展开的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4-%E5%AE%9A%E4%B9%89%E5%B0%86%E5%8D%B7%E7%A7%AF%E5%B1%82%E5%B1%95%E5%BC%80%E7%9A%84%E5%87%BD%E6%95%B0
5、定义全连接层的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5-%E5%AE%9A%E4%B9%89%E5%85%A8%E8%BF%9E%E6%8E%A5%E5%B1%82%E7%9A%84%E5%87%BD%E6%95%B0
6、定义模型	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#6-%E5%AE%9A%E4%B9%89%E6%A8%A1%E5%9E%8B
7、定义训练的函数，使用bgd	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#7-%E5%AE%9A%E4%B9%89%E8%AE%AD%E7%BB%83%E7%9A%84%E5%87%BD%E6%95%B0%E4%BD%BF%E7%94%A8bgd
8、定义批量预测的函数，方便输出训练错的图像	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#8-%E5%AE%9A%E4%B9%89%E6%89%B9%E9%87%8F%E9%A2%84%E6%B5%8B%E7%9A%84%E5%87%BD%E6%95%B0%E6%96%B9%E4%BE%BF%E8%BE%93%E5%87%BA%E8%AE%AD%E7%BB%83%E9%94%99%E7%9A%84%E5%9B%BE%E5%83%8F
9、定义可视化卷积核权重的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#9-%E5%AE%9A%E4%B9%89%E5%8F%AF%E8%A7%86%E5%8C%96%E5%8D%B7%E7%A7%AF%E6%A0%B8%E6%9D%83%E9%87%8D%E7%9A%84%E5%87%BD%E6%95%B0
10、定义可视化卷积层输出的函数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#10-%E5%AE%9A%E4%B9%89%E5%8F%AF%E8%A7%86%E5%8C%96%E5%8D%B7%E7%A7%AF%E5%B1%82%E8%BE%93%E5%87%BA%E7%9A%84%E5%87%BD%E6%95%B0
十一：使用prettytensor实现CNNModel	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%8D%81%E4%B8%80%E4%BD%BF%E7%94%A8prettytensor%E5%AE%9E%E7%8E%B0cnnmodel
1、定义模型	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E5%AE%9A%E4%B9%89%E6%A8%A1%E5%9E%8B
十二：CNN,保存和加载模型，使用Early Stopping	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%8D%81%E4%BA%8Ccnn%E4%BF%9D%E5%AD%98%E5%92%8C%E5%8A%A0%E8%BD%BD%E6%A8%A1%E5%9E%8B%E4%BD%BF%E7%94%A8early-stopping
1、保存模型	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E4%BF%9D%E5%AD%98%E6%A8%A1%E5%9E%8B
2、Early Stopping	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-early-stopping
3、小批量预测并计算准确率	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E5%B0%8F%E6%89%B9%E9%87%8F%E9%A2%84%E6%B5%8B%E5%B9%B6%E8%AE%A1%E7%AE%97%E5%87%86%E7%A1%AE%E7%8E%87
十二：模型融合	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%8D%81%E4%BA%8C%E6%A8%A1%E5%9E%8B%E8%9E%8D%E5%90%88
1、将测试集和验证集合并后，并重新划分	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E5%B0%86%E6%B5%8B%E8%AF%95%E9%9B%86%E5%92%8C%E9%AA%8C%E8%AF%81%E9%9B%86%E5%90%88%E5%B9%B6%E5%90%8E%E5%B9%B6%E9%87%8D%E6%96%B0%E5%88%92%E5%88%86
2、融合模型	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E8%9E%8D%E5%90%88%E6%A8%A1%E5%9E%8B
十二：Cifar-10数据集，使用重复使用变量	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%8D%81%E4%BA%8Ccifar-10%E6%95%B0%E6%8D%AE%E9%9B%86%E4%BD%BF%E7%94%A8%E9%87%8D%E5%A4%8D%E4%BD%BF%E7%94%A8%E5%8F%98%E9%87%8F
1、数据集	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E6%95%B0%E6%8D%AE%E9%9B%86
2、定义	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E5%AE%9A%E4%B9%89
3、图片处理	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E5%9B%BE%E7%89%87%E5%A4%84%E7%90%86
4、定义tensorflow计算图	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4-%E5%AE%9A%E4%B9%89tensorflow%E8%AE%A1%E7%AE%97%E5%9B%BE
5、获取权重和每层的输出值信息	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5-%E8%8E%B7%E5%8F%96%E6%9D%83%E9%87%8D%E5%92%8C%E6%AF%8F%E5%B1%82%E7%9A%84%E8%BE%93%E5%87%BA%E5%80%BC%E4%BF%A1%E6%81%AF
6、保存和加载计算图参数	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#6-%E4%BF%9D%E5%AD%98%E5%92%8C%E5%8A%A0%E8%BD%BD%E8%AE%A1%E7%AE%97%E5%9B%BE%E5%8F%82%E6%95%B0
7、训练	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#7-%E8%AE%AD%E7%BB%83
十三、Inception model (GoogleNet)	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%8D%81%E4%B8%89-inception-model-googlenet
1、下载和加载inception model	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E4%B8%8B%E8%BD%BD%E5%92%8C%E5%8A%A0%E8%BD%BDinception-model
十四、迁移学习 Transfer Learning	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E5%8D%81%E5%9B%9B-%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0-transfer-learning
1、准备工作	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E5%87%86%E5%A4%87%E5%B7%A5%E4%BD%9C
2、分析	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E5%88%86%E6%9E%90
(1) 使用PCA主成分分析	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E4%BD%BF%E7%94%A8pca%E4%B8%BB%E6%88%90%E5%88%86%E5%88%86%E6%9E%90
(2) 使用TSNE主成分分析	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E4%BD%BF%E7%94%A8tsne%E4%B8%BB%E6%88%90%E5%88%86%E5%88%86%E6%9E%90
3、创建我们自己的网络	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E5%88%9B%E5%BB%BA%E6%88%91%E4%BB%AC%E8%87%AA%E5%B7%B1%E7%9A%84%E7%BD%91%E7%BB%9C
RNN循环神经网络	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#rnn%E5%BE%AA%E7%8E%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C
一、实现MNIST分类	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#%E4%B8%80-%E5%AE%9E%E7%8E%B0mnist%E5%88%86%E7%B1%BB
1、说明	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-%E8%AF%B4%E6%98%8E
2、实现	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-%E5%AE%9E%E7%8E%B0
3、运行结果	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-%E8%BF%90%E8%A1%8C%E7%BB%93%E6%9E%9C
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#一tensorflow介绍
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1什么是tensorflow
https://www.tensorflow.org/	https://www.tensorflow.org/
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2tensorflow强大之处
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3安装tensorflow
官网点击	https://www.tensorflow.org/
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#二tensorflow基础架构
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1处理结构
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/tensors_flowing.gif
1	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/tensors_flowing.gif
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2一个例子
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3session会话控制
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4variable变量
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5placeholder传入值
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#三定义一个神经网络
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1添加层函数add_layer
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2构建神经网络
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3可视化结果
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/example_01.png
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/example_02.gif
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#四tensorflow可视化
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1tensorflow的可视化工具tensorboard可视化神经网路额结构
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/tensorboard_01.png
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/tensorboard_02.png
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/tensorboard_03.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2可视化训练过程
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/tensorboard_04.png
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/tensorboard_05.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#五手写数字识别_1
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1说明
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Mnist_01/mnist.py
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2代码实现
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/Mnist_01.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#六手写数字识别_2
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1说明-1
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Mnist_02/mnist.py
http://yann.lecun.com/exdb/mnist/）	http://yann.lecun.com/exdb/mnist/%EF%BC%89
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2代码
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/Mnist_02.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#七手写数字识别_3_cnn卷积神经网络
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1说明-2
我的博客	http://blog.csdn.net/u013082989/article/details/53673602
http://blog.csdn.net/u013082989/article/details/53673602	http://blog.csdn.net/u013082989/article/details/53673602
github	https://github.com/lawlite19/DeepLearning_Python
https://github.com/lawlite19/DeepLearning_Python	https://github.com/lawlite19/DeepLearning_Python
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Mnist_03_CNN/mnist_cnn.py
http://yann.lecun.com/exdb/mnist/）	http://yann.lecun.com/exdb/mnist/%EF%BC%89
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2代码实现-1
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3运行结果
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/cnn_mnist_02.png
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/cnn_mnist_01.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#八保存和提取神经网络
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1保存
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2提取
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#以下来自tensorflow-turorial使用python35
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#九线性模型linear-model
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/LinearModel/LinearModel.py
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1加载mnist数据集并输出信息
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2绘制9张图像
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/LinearModel_01.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3定义要训练的模型
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4定义函数optimize进行bgd训练
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5定义输出准确度的函数
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#6定义绘制错误预测的图片函数
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/LinearModel_02.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#7定义可视化权重的函数
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/LinearModel_03.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#8定义输出confusion_matrix的函数
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/LinearModel_04.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#十cnn
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/CNNModel/CNN_Model.py
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1定义cnn所需要的变量
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2初始化weights和biases的函数
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3定义卷积操作和池化如果使用的话的函数
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4定义将卷积层展开的函数
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5定义全连接层的函数
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#6定义模型
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#7定义训练的函数optimize使用bgd
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#8定义批量预测的函数方便输出训练错的图像
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#9定义可视化卷积核权重的函数
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/CNNModel_01.png
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/CNNModel_03.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#10定义可视化卷积层输出的函数
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/CNNModel_02.png
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/CNNModel_04.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#十一使用prettytensor实现cnnmodel
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/CNNModel_PrettyTensor/CNNModel_prettytensor.py
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1定义模型
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#十二cnn保存和加载模型使用early-stopping
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/CNNModel_EarlyStopping_Save_Restore/CNNModel_EarlyStopping_Save_Restore.py
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1保存模型
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2early-stopping
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3-小批量预测并计算准确率
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#十二模型融合
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Ensemble_Learning/ensemble_learning.py
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1将测试集和验证集合并后并重新划分
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2融合模型
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#十二cifar-10数据集使用variable_scope重复使用变量
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Ensemble_Learning/CNN_for_CIFAR-10
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/06_network_flowchart.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1数据集
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2定义placeholder
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3图片处理
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#4定义tensorflow计算图
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#5获取权重和每层的输出值信息
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#6保存和加载计算图参数
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#7训练
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#十三inception-model-googlenet
全部代码	https://github.com/lawlite19/MachineLearning_TensorFlow/blob/master/Inception_model/InceptionModel_pretrained.py
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/07_inception_flowchart.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1下载和加载inception-model
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#十四迁移学习-transfer-learning
全部代码	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow/blob/master/30
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/08_transfer_learning_flowchart.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1准备工作
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2分析transfer-values
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1-使用pca主成分分析
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/08_transfer_learning_pca_visualize.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2-使用tsne主成分分析
	https://raw.githubusercontent.com/lawlite19/MachineLearning_TensorFlow/master/images/08_transfer_learning_pca_visualize_02.png
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3创建我们自己的网络
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#rnn循环神经网络
点击查看	http://lawlite.me/tags/RNN/
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#一实现mnist分类
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#1说明-3
点击查看	http://lawlite.me/tags/RNN/
点击查看	https://github.com/lawlite19/MachineLearning_TensorFlow/tree/master/RNN_mnist/RNN.py
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#2实现
	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#3运行结果-1
Readme	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#readme-ov-file
MIT license	https://patch-diff.githubusercontent.com/lyc10031/MachineLearning_TensorFlow#MIT-1-ov-file
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