├── .gitignore ├── README.md ├── lesson01-PyTorch初见 ├── autograd_demo.py ├── gpu_accelerate.py ├── 初见PyTorch.pdf ├── 版权声明.png ├── 答疑群-926107229.png └── 请学员务必加群答疑！！！.txt ├── lesson02-开发环境安装 ├── lesson2.pdf ├── main.py └── 版权声明.png ├── lesson03-简单回归案例 ├── lesson3.pdf └── 版权声明.png ├── lesson04-简单回归案例实战 ├── data.csv ├── gd.py ├── lesson4.pdf └── 版权声明.png ├── lesson05-手写数字问题 ├── lesson5.pdf ├── mnist_train.py ├── utils.py └── 版权声明.png ├── lesson06-基本数据类型 ├── lesson6.pdf └── 版权声明.png ├── lesson07-创建Tensor ├── lesson7.pdf ├── 版权声明.png └── 这一章代码量少，同学们照着写.txt ├── lesson08-索引与切片 ├── lesson8.pdf └── 这一章代码量少，同学们照着写.txt ├── lesson09-维度变换 ├── Expand.pdf └── 这一章代码量少，同学们照着写.txt ├── lesson10-Broadcasting ├── Broadcasting.pdf └── 这一章代码量少，同学们照着写.txt ├── lesson11-合并与分割 ├── Concat.pdf └── 这一章代码量少，同学们照着写.txt ├── lesson12-数学运算 ├── math operation.pdf └── 这一章代码量少，同学们照着写.txt ├── lesson13-Tensor统计 ├── statisics.pdf └── 这一章代码量少，同学们照着写.txt ├── lesson14-Tensor高阶 ├── tensor advanced.pdf └── 这一章代码量少，同学们照着写.txt ├── lesson16-什么是梯度 └── 16 梯度.pdf ├── lesson17-常见函数的梯度 └── 17 常见函数梯度.pdf ├── lesson18-激活函数与Loss的梯度 ├── 18.1 激活函数梯度.pdf └── 18.2 LOSS及其梯度.pdf ├── lesson19-感知机的梯度推导 ├── 19.1 单一输出感知机.pdf ├── 19.2 多输出感知机.pdf ├── lesson19.1.mp4.baiduyun.uploading.cfg └── lesson19.2.mp4.baiduyun.uploading.cfg ├── lesson20-链式法则 └── 20.pdf ├── lesson21-MLP反向传播推导 └── 21.pdf ├── lesson22-优化小实例 ├── 22 Himmelblau.pdf └── main.py ├── lesson24-Logistic Regression └── 24 LR.pdf ├── lesson25-交叉熵 └── 25 交叉熵.pdf ├── lesson26-LR多分类实战 ├── 26.pdf └── main.py ├── lesson27-MLP网络层 ├── 27 全连接层.pdf └── main.py ├── lesson28-激活函数与GPU加速 ├── 28.pdf └── main.py ├── lesson29-MNIST测试 ├── 29.pdf └── main.py ├── lesson30-Visdom可视化 ├── 30 可视化.pdf └── main.py ├── lesson31-过拟合与欠拟合 └── 31.pdf ├── lesson32-Train-Val-Test-交叉验证 ├── 32.pdf └── main.py ├── lesson33-regularization ├── 33.pdf └── main.py ├── lesson34-动量与lr衰减 └── 34.pdf ├── lesson35-Early-stopping-Dropout ├── 35.pdf └── main.py ├── lesson37-什么是卷积 └── 37 卷积.pdf ├── lesson38-卷积神经网络 └── 38 CNN.pdf ├── lesson39-Pooling-Sampling └── 39.pdf ├── lesson40-BatchNorm └── 40.pdf ├── lesson41-经典卷积网络 └── 41.pdf ├── lesson42-ResNet ├── 42.pdf └── resnet.py ├── lesson43-nn.Module ├── 43.pdf └── main.py ├── lesson44-数据增强 ├── 44.pdf └── main.py ├── lesson45-Cifar10与ResNet18实战 ├── .gitignore ├── .idea │ ├── Cifar10与ResNet18实战.iml │ ├── encodings.xml │ ├── inspectionProfiles │ │ └── Project_Default.xml │ ├── misc.xml │ ├── modules.xml │ ├── vcs.xml │ └── workspace.xml ├── lenet5.py ├── main.py └── resnet.py ├── lesson46-时间序列表示 ├── 46.pdf └── main.py ├── lesson47-RNN原理 └── 47.pdf ├── lesson48-RNN-Layer使用 ├── 48.pdf └── rnn.py ├── lesson49-时间序列预测 ├── 49.pdf └── seris.py ├── lesson50-RNN训练难题 └── 50.pdf ├── lesson51-LSTM原理 └── 51.pdf ├── lesson52-LSTM-Layer使用 └── 52.pdf ├── lesson53-情感分类实战 ├── 53.pdf ├── lstm.ipynb └── lstm.py ├── lesson54-AutoEncoder自编码器 ├── .gitignore └── AutoEncoders.pdf ├── lesson55-VAE实战 ├── ae.py ├── main.py └── vae.py ├── lesson56-GAN原理 ├── GAN样片.jpg └── 深度学习：GAN.pdf ├── lesson57-WGAN实战 ├── gan.py └── wgan_gp.py ├── lesson58-图卷积网络GCN ├── .gitignore ├── .idea │ ├── encodings.xml │ ├── lesson66-图卷积网络GCN.iml │ ├── misc.xml │ ├── modules.xml │ ├── vcs.xml │ └── workspace.xml ├── README.MD ├── layers.py ├── models.py ├── res │ └── figure.png ├── train.py └── utils.py ├── lesson63-迁移学习-自定义数据集实战 ├── pokemon.py ├── resnet.py ├── train_scratch.py ├── train_transfer.py ├── utils.py └── 宝可梦数据集.pdf ├── lesson选看-人工智能发展史 └── 人工智能发展史.pdf ├── res ├── ad_banner.png ├── cover.png ├── outline.png └── 版权声明.png └── 课程介绍 ├── 2019-01-12 (6).png └── 2019-01-13.png /.gitignore: -------------------------------------------------------------------------------- 1 | data 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/dragen1860/Deep-Learning-with-PyTorch-Tutorials/HEAD/README.md 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