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          Github項(xiàng)目推薦 | 深度學(xué)習(xí)資源,包括一系列架構(gòu)、模型與建議

          項(xiàng)目地址:https://github.com/rasbt/deeplearning-models 

          Jupyter筆記本中TensorFlow和PyTorch的各種深度學(xué)習(xí)架構(gòu),模型和技巧的集合。

          傳統(tǒng)機(jī)器學(xué)習(xí)

          • 感知機(jī) Perceptron [TensorFlow 1] [PyTorch]

          • 邏輯回歸 Logistic Regression [TensorFlow 1] [PyTorch]

          • Softmax回歸(多項(xiàng)邏輯回歸) Softmax Regression (Multinomial Logistic Regression) [TensorFlow 1] [PyTorch]

          多層感知機(jī)

          • 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]

          卷積神經(jīng)網(wǎng)絡(luò)

          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]

          完全卷積

          • 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]

          度量學(xué)習(xí)

          • Siamese Network with Multilayer Perceptrons [TensorFlow 1]

          自編碼器

          完全連接的自編碼器

          • Autoencoder [TensorFlow 1] [PyTorch]

          卷積自編碼器

          • 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]

          變分自編碼器

          • Variational Autoencoder [PyTorch]

          • Convolutional Variational Autoencoder [PyTorch]

          條件變分自編碼器

          • 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]

          生成對抗網(wǎng)絡(luò)(GAN)

          • Fully Connected GAN on MNIST [TensorFlow 1] [PyTorch]

          • Convolutional GAN on MNIST [TensorFlow 1] [PyTorch]

          • Convolutional GAN on MNIST with Label Smoothing [PyTorch]

          遞歸神經(jīng)網(wǎng)絡(luò)(RNN)

          多對一:情感分析/分類

          • 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]

          多對多/序列到序列

          • A simple character RNN to generate new text (Charles Dickens) [PyTorch]

          順序回歸

          • 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]

          技巧和竅門

          • Cyclical Learning Rate [PyTorch]

          PyTorch工作流程和機(jī)制

          自定義數(shù)據(jù)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]

          訓(xùn)練和預(yù)處理

          • 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]

          并行計(jì)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工作流程和機(jī)制

          自定義數(shù)據(jù)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]

          訓(xùn)練和預(yù)處理

          • Saving and Loading Trained Models -- from TensorFlow Checkpoint Files and NumPy NPZ Archives [TensorFlow 1]

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