PyTorch-Tutorial

Why we included this project

Learning deep learning from documentation alone is rough, and this tutorial repo exists to smooth that path. It starts with the PyTorch core, covering tensors, activation functions, and autograd, then shows you how to build and train networks for regression and classification, with each lesson stored as a small runnable script you can adapt. From there it branches into the architectures that show up in real projects: convolutional and recurrent networks, autoencoders, DQN for reinforcement learning, and GANs including a conditional version. Because every example is self-contained, you can grab the snippet for a CNN or GAN and drop it into your own experiment without wading through a book. If you read Chinese, the same material comes with video and text lessons on the author's site, making it a practical bilingual resource.