ordinal
Deep Learning Models
A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks.
Traditional Machine Learning
Multilayer Perceptrons
Convolutional Neural Networks
Basic
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Convolutional Neural Network | TBD | TBD | |
| CNN with He Initialization | TBD | TBD |
Concepts
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Replacing Fully-Connnected by Equivalent Convolutional Layers | TBD | TBD |
AlexNet
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| AlexNet Trained on CIFAR-10 | TBD | TBD | |
| AlexNet with Grouped Convolutions Trained on CIFAR-10 | TBD | TBD |
DenseNet
| Title | Description | Daset | Notebooks |
|---|---|---|---|
| DenseNet-121 Digit Classifier Trained on MNIST | TBD | TBD | |
| DenseNet-121 Image Classifier Trained on CIFAR-10 | TBD | TBD |
Fully Convolutional
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| "All Convolutionl Net" -- A Fully Convolutional Neural Network | TBD | TBD |
LeNet
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| LeNet-5 on MNIST | TBD | TBD | |
| LeNet-5 on CIFAR-10 | TBD | TBD | |
| LeNet-5 on QuickDraw | TBD | TBD |
MobileNet
| Title | Description | Datasets | Notebooks |
|---|---|---|---|
| MobileNet-v2 on Cifar-10 | TBD | TBD | |
| MobileNet-v3 small on Cifar-10 | TBD | TBD | |
| MobileNet-v3 large on Cifar-10 | TBD | TBD |
Network in Network
| Title | Description | Datasets | Notebooks |
|---|---|---|---|
| Network in Network Trained on CIFAR-10 | TBD | TBD |
VGG
ResNet
Ordinal Regression and Deep Learning
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| CORAL multilayer perceptron | Cement | Implementation of Rank Consistent Ordinal Regression for Neural Networks with Application to Age Estimation 2020 | |
| CORN multilayer perceptron | Cement | Implementation of Deep Neural Networks for Rank-Consistent Ordinal Regression Based On Conditional Probabilities 2022 | |
| Reformulated squared-error multilayer perceptron | Cement | Implementation of A simple squared-error reformulation for ordinal classification 2016 |
Normalization Layers
Metric Learning
| Title | Description | Datasets | Notebooks |
|---|---|---|---|
| Siamese Network with Multilayer Perceptrons | TBD | TBD |
Autoencoders
Fully-connected Autoencoders
| Title | Description | Datasets | Notebooks |
|---|---|---|---|
| Autoencoder (MNIST) | TBD | TBD | |
| Autoencoder (MNIST) + Scikit-Learn Random Forest Classifier | TBD | TBD |
Convolutional Autoencoders
Variational Autoencoders
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Variational Autoencoder | TBD | TBD | |
| Convolutional Variational Autoencoder | TBD | TBD |
Conditional Variational Autoencoders
Generative Adversarial Networks (GANs)
Graph Neural Networks (GNNs)
Recurrent Neural Networks (RNNs)
Many-to-one: Sentiment Analysis / Classification
Many-to-Many / Sequence-to-Sequence
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| A simple character RNN to generate new text (Charles Dickens) | TBD | TBD |
Tips and Tricks
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Cyclical Learning Rate | TBD | TBD | |
| Annealing with Increasing the Batch Size (w. CIFAR-10 & AlexNet) | TBD | TBD | |
| Gradient Clipping (w. MLP on MNIST) | TBD | TBD |
Transfer Learning
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Transfer Learning Example (VGG16 pre-trained on ImageNet for Cifar-10) | TBD | TBD |
Visualization and Interpretation
PyTorch Workflows and Mechanics
PyTorch Lightning Examples
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| MLP in Lightning with TensorBoard -- continue training the last model | TBD | TBD | |
| MLP in Lightning with TensorBoard -- checkpointing best model | TBD | TBD |
Custom Datasets
Training and Preprocessing
Improving Memory Efficiency
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Gradient Checkpointing Demo (Network-in-Network trained on CIFAR-10) | TBD | TBD |
Parallel Computing
| Title | Description | Notebooks |
|---|---|---|
| Using Multiple GPUs with DataParallel -- VGG-16 Gender Classifier on CelebA | TBD | |
| Distribute a Model Across Multiple GPUs with Pipeline Parallelism (VGG-16 Example) | TBD |
Other
Autograd
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Getting Gradients of an Intermediate Variable in PyTorch | TBD | TBD |
TensorFlow Workflows and Mechanics
Custom Datasets
Training and Preprocessing
| Title | Description | Dataset | Notebooks |
|---|---|---|---|
| Saving and Loading Trained Models -- from TensorFlow Checkpoint Files and NumPy NPZ Archives | TBD | TBD |
Related Libraries
| Title | Description | Notebooks |
|---|---|---|
| TorchMetrics | How do we use it, and what's the difference between .update() and .forward()? |
Description
多种深度学习架构与模型的代码集合。|GitHub 镜像 ⭐ 17.6k · 🍴 4.1k
https://github.com/rasbt/deeplearning-models
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