@@ -32,14 +32,14 @@ Learn Deep Learning with PyTorch
3232- Chapter 4: 卷积神经网络
3333 - [ PyTorch 中的卷积模块] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN/basic_conv.ipynb )
3434 - [ 批标准化,batch normalization] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN/batch-normalization.ipynb )
35- - [ 使用重复元素的深度网络,VGG] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN /vgg.ipynb )
36- - [ 更加丰富化结构的网络,GoogLeNet] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN /googlenet.ipynb )
37- - [ 深度残差网络,ResNet] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN /resnet.ipynb )
38- - [ 稠密连接的卷积网络,DenseNet] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN /densenet.ipynb )
35+ - [ 使用重复元素的深度网络,VGG] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN /vgg.ipynb )
36+ - [ 更加丰富化结构的网络,GoogLeNet] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN /googlenet.ipynb )
37+ - [ 深度残差网络,ResNet] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN /resnet.ipynb )
38+ - [ 稠密连接的卷积网络,DenseNet] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN /densenet.ipynb )
3939 - 更好的训练卷积网络
40- - [ 数据增强] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN /data-augumentation.ipynb )
41- - [ 正则化] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN /regularization.ipynb )
42- - [ 学习率衰减] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN /lr-decay.ipynb )
40+ - [ 数据增强] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN /data-augumentation.ipynb )
41+ - [ 正则化] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN /regularization.ipynb )
42+ - [ 学习率衰减] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN /lr-decay.ipynb )
4343
4444- Chapter 5: 循环神经网络
4545 - LSTM 和 GRU
@@ -63,7 +63,7 @@ Learn Deep Learning with PyTorch
6363 - [ RMSProp] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances/optimizer/rmsprop.ipynb )
6464 - [ Adadelta] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances/optimizer/adadelta.ipynb )
6565 - [ Adam] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances/optimizer/adam.ipynb )
66- - [ 灵活的数据读取介绍] ( )
66+ - [ 灵活的数据读取介绍] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances/data-io.ipynb )
6767 - autograd.function 的介绍
6868 - 数据并行和多 GPU
6969 - PyTorch 的分布式应用
@@ -72,7 +72,7 @@ Learn Deep Learning with PyTorch
7272
7373### part2: 深度学习的应用
7474- Chapter 8: 计算机视觉
75- - [ Fine-tuning: 通过微调进行迁移学习] ( )
75+ - [ Fine-tuning: 通过微调进行迁移学习] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter7_Computer-Vision/fine-tune.ipynb )
7676 - 语义分割: 通过 FCN 实现像素级别的分类
7777 - Neural Transfer: 通过卷积网络实现风格迁移
7878 - Deep Dream: 探索卷积网络眼中的世界
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