A resource for learning about Machine learning & Deep Learning
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
A Variational Autoencoder (VAE) implemented in PyTorch
A short tutorial on performing fine tuning or transfer learning in PyTorch.
Pytorch implementation of contractive autoencoder on MNIST dataset
Enhanced Super-Resolution Generative Adversarial Networks
Instructions on how to use PyTorch on AMD GPU with Linux
PyTorch 0.3.1 튜토리얼의 한국어 번역을 위한 저장소입니다. (Translate PyTorch v0.3.1 tutorials in Korean.)
RNN
A Generative Adverserial Network for modelling any distribution.
My content of CS294 Deep Reinforcement Learning course, conduced by Sergey Levine from UC Berkeley.
Pytorch basic tutorial for CNN
Pytorch Implementation of Various Machine Learning and Perceptron Algorithms
mnist mlp in pytorch and tensorflow
Building train/test datasets with HDF5 database for deeplearning
PyTorch tutorials hand-coded (not copy and pasted) from here https://pytorch.org/tutorials/beginner/pytorch_with_examples.html
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