首页
学习
活动
专区
工具
TVP
发布
社区首页 >专栏 >Github项目推荐 | 深度学习资源,包括一系列架构、模型与建议

Github项目推荐 | 深度学习资源,包括一系列架构、模型与建议

作者头像
AI研习社
发布2019-07-04 15:08:32
8320
发布2019-07-04 15:08:32
举报
文章被收录于专栏:AI研习社AI研习社

项目地址:https://github.com/rasbt/deeplearning-models

Jupyter笔记本中TensorFlow和PyTorch的各种深度学习架构,模型和技巧的集合。

传统机器学习

  • 感知机 Perceptron [TensorFlow 1] [PyTorch]
  • 逻辑回归 Logistic Regression [TensorFlow 1] [PyTorch]
  • Softmax回归(多项逻辑回归) Softmax Regression (Multinomial Logistic Regression) [TensorFlow 1] [PyTorch]

多层感知机

  • Multilayer Perceptron [TensorFlow 1] [PyTorch]
  • Multilayer Perceptron with Dropout [TensorFlow 1] [PyTorch]
  • Multilayer Perceptron with Batch Normalization [TensorFlow 1] [PyTorch]
  • Multilayer Perceptron with Backpropagation from Scratch [TensorFlow 1] [PyTorch]

卷积神经网络

基本
  • Convolutional Neural Network [TensorFlow 1] [PyTorch]
  • Convolutional Neural Network with He Initialization [PyTorch]
概念
  • Replacing Fully-Connnected by Equivalent Convolutional Layers [PyTorch]
完全卷积
  • Fully Convolutional Neural Network [PyTorch]
AlexNet
  • AlexNet on CIFAR-10 [PyTorch]
VGG
  • Convolutional Neural Network VGG-16 [TensorFlow 1] [PyTorch]
  • VGG-16 Gender Classifier Trained on CelebA [PyTorch]
  • Convolutional Neural Network VGG-19 [PyTorch]
ResNet
  • ResNet and Residual Blocks [PyTorch]
  • ResNet-18 Digit Classifier Trained on MNIST [PyTorch]
  • ResNet-18 Gender Classifier Trained on CelebA [PyTorch]
  • ResNet-34 Digit Classifier Trained on MNIST [PyTorch]
  • ResNet-34 Gender Classifier Trained on CelebA [PyTorch]
  • ResNet-50 Digit Classifier Trained on MNIST [PyTorch]
  • ResNet-50 Gender Classifier Trained on CelebA [PyTorch]
  • ResNet-101 Gender Classifier Trained on CelebA [PyTorch]
  • ResNet-152 Gender Classifier Trained on CelebA [PyTorch]
Network in Network
  • Network in Network CIFAR-10 Classifier [PyTorch]

度量学习

  • Siamese Network with Multilayer Perceptrons [TensorFlow 1]

自编码器

完全连接的自编码器
  • Autoencoder [TensorFlow 1] [PyTorch]
卷积自编码器
  • Convolutional Autoencoder with Deconvolutions / Transposed Convolutions[TensorFlow 1] [PyTorch]
  • Convolutional Autoencoder with Deconvolutions (without pooling operations) [PyTorch]
  • Convolutional Autoencoder with Nearest-neighbor Interpolation [TensorFlow 1] [PyTorch]
  • Convolutional Autoencoder with Nearest-neighbor Interpolation -- Trained on CelebA [PyTorch]
  • Convolutional Autoencoder with Nearest-neighbor Interpolation -- Trained on Quickdraw [PyTorch]
变分自编码器
  • Variational Autoencoder [PyTorch]
  • Convolutional Variational Autoencoder [PyTorch]
条件变分自编码器
  • Conditional Variational Autoencoder (with labels in reconstruction loss) [PyTorch]
  • Conditional Variational Autoencoder (without labels in reconstruction loss) [PyTorch]
  • Convolutional Conditional Variational Autoencoder (with labels in reconstruction loss) [PyTorch]
  • Convolutional Conditional Variational Autoencoder (without labels in reconstruction loss) [PyTorch]

生成对抗网络(GAN)

  • Fully Connected GAN on MNIST [TensorFlow 1] [PyTorch]
  • Convolutional GAN on MNIST [TensorFlow 1] [PyTorch]
  • Convolutional GAN on MNIST with Label Smoothing [PyTorch]

递归神经网络(RNN)

多对一:情感分析/分类
  • A simple single-layer RNN (IMDB) [PyTorch]
  • A simple single-layer RNN with packed sequences to ignore padding characters (IMDB) [PyTorch]
  • RNN with LSTM cells (IMDB) [PyTorch]
  • RNN with LSTM cells (IMDB) and pre-trained GloVe word vectors [PyTorch]
  • RNN with LSTM cells and Own Dataset in CSV Format (IMDB) [PyTorch]
  • RNN with GRU cells (IMDB) [PyTorch]
  • Multilayer bi-directional RNN (IMDB) [PyTorch]
多对多/序列到序列
  • A simple character RNN to generate new text (Charles Dickens) [PyTorch]

顺序回归

  • Ordinal Regression CNN -- CORAL w. ResNet34 on AFAD-Lite [PyTorch]
  • Ordinal Regression CNN -- Niu et al. 2016 w. ResNet34 on AFAD-Lite [PyTorch]
  • Ordinal Regression CNN -- Beckham and Pal 2016 w. ResNet34 on AFAD-Lite [PyTorch]

技巧和窍门

  • Cyclical Learning Rate [PyTorch]

PyTorch工作流程和机制

自定义数据集
  • Using PyTorch Dataset Loading Utilities for Custom Datasets -- CSV files converted to HDF5 [PyTorch]
  • Using PyTorch Dataset Loading Utilities for Custom Datasets -- Face Images from CelebA [PyTorch]
  • Using PyTorch Dataset Loading Utilities for Custom Datasets -- Drawings from Quickdraw [PyTorch]
  • Using PyTorch Dataset Loading Utilities for Custom Datasets -- Drawings from the Street View House Number (SVHN) Dataset [PyTorch]
训练和预处理
  • Dataloading with Pinned Memory [PyTorch]
  • Standardizing Images [PyTorch]
  • Image Transformation Examples [PyTorch]
  • Char-RNN with Own Text File [PyTorch]
  • Sentiment Classification RNN with Own CSV File [PyTorch]
并行计算
  • Using Multiple GPUs with DataParallel -- VGG-16 Gender Classifier on CelebA [PyTorch]
其他
  • Sequential API and hooks [PyTorch]
  • Weight Sharing Within a Layer [PyTorch]
  • Plotting Live Training Performance in Jupyter Notebooks with just Matplotlib [PyTorch]
Autograd
  • Getting Gradients of an Intermediate Variable in PyTorch [PyTorch]

TensorFlow工作流程和机制

自定义数据集
  • Chunking an Image Dataset for Minibatch Training using NumPy NPZ Archives [TensorFlow 1]
  • Storing an Image Dataset for Minibatch Training using HDF5 [TensorFlow 1]
  • Using Input Pipelines to Read Data from TFRecords Files [TensorFlow 1]
  • Using Queue Runners to Feed Images Directly from Disk [TensorFlow 1]
  • Using TensorFlow's Dataset API [TensorFlow 1]
训练和预处理
  • Saving and Loading Trained Models -- from TensorFlow Checkpoint Files and NumPy NPZ Archives [TensorFlow 1]
本文参与 腾讯云自媒体分享计划,分享自微信公众号。
原始发表:2019-07-02,如有侵权请联系 cloudcommunity@tencent.com 删除

本文分享自 AI研习社 微信公众号,前往查看

如有侵权,请联系 cloudcommunity@tencent.com 删除。

本文参与 腾讯云自媒体分享计划  ,欢迎热爱写作的你一起参与!

评论
登录后参与评论
0 条评论
热度
最新
推荐阅读
目录
  • 传统机器学习
  • 多层感知机
  • 卷积神经网络
    • 基本
      • 概念
        • 完全卷积
          • AlexNet
            • VGG
              • ResNet
                • Network in Network
                • 自编码器
                  • 完全连接的自编码器
                    • 卷积自编码器
                      • 变分自编码器
                        • 条件变分自编码器
                        • 生成对抗网络(GAN)
                        • 递归神经网络(RNN)
                          • 多对一:情感分析/分类
                            • 多对多/序列到序列
                            • 顺序回归
                            • 技巧和窍门
                            • PyTorch工作流程和机制
                              • 自定义数据集
                                • 训练和预处理
                                  • 并行计算
                                    • 其他
                                      • Autograd
                                      • TensorFlow工作流程和机制
                                        • 自定义数据集
                                          • 训练和预处理
                                          相关产品与服务
                                          GPU 云服务器
                                          GPU 云服务器(Cloud GPU Service,GPU)是提供 GPU 算力的弹性计算服务,具有超强的并行计算能力,作为 IaaS 层的尖兵利器,服务于深度学习训练、科学计算、图形图像处理、视频编解码等场景。腾讯云随时提供触手可得的算力,有效缓解您的计算压力,提升业务效率与竞争力。
                                          领券
                                          问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档