@@ -31,11 +31,14 @@ Learn Deep Learning with PyTorch
3131
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 )
34+ - [ 批标准化,batch normalization] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter4_CNN/batch-normalization.ipynb ) )
3435 - [ 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 )
3536 - [ 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 )
3637 - [ 深度残差网络,ResNet] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_CNN/resnet.ipynb )
3738 - [ 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 )
38- - 更好的训练卷积网络:数据增强、批标准化、dropout、正则化方法以及学习率衰减
39+ - 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+ - dropout、正则化方法和学习率衰减] ( )
3942
4043- Chapter 5: 循环神经网络
4144 - LSTM 和 GRU
@@ -53,12 +56,12 @@ Learn Deep Learning with PyTorch
5356- Chapter 7: PyTorch高级
5457 - tensorboard 可视化
5558 - 优化算法
56- - [ SGD] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_NN /optimizer/sgd.ipynb )
57- - [ 动量法] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_NN /optimizer/momentum.ipynb )
58- - [ Adagrad] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_NN /optimizer/adagrad.ipynb )
59- - [ RMSProp] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_NN /optimizer/rmsprop.ipynb )
60- - [ Adadelta] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_NN /optimizer/adadelta.ipynb )
61- - [ Adam] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter3_NN /optimizer/adam.ipynb )
59+ - [ SGD] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances /optimizer/sgd.ipynb )
60+ - [ 动量法] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances /optimizer/momentum.ipynb )
61+ - [ Adagrad] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances /optimizer/adagrad.ipynb )
62+ - [ RMSProp] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances /optimizer/rmsprop.ipynb )
63+ - [ Adadelta] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances /optimizer/adadelta.ipynb )
64+ - [ Adam] ( https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter6_PyTorch-Advances /optimizer/adam.ipynb )
6265 - 灵活的数据读取介绍
6366 - autograd.function 的介绍
6467 - 数据并行和多 GPU
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