PyTorch-Tutorial-2nd

Why we included this project

This second edition of the Practical PyTorch Tutorial is free to read online, with the full companion codebase included, and it is structured so a total beginner can start from environment setup and the core data, model, and visualization modules before touching applied projects. The middle sections cover eight computer vision tasks, five NLP tasks, and hands-on LLM deployment with open models such as Qwen, ChatGLM, Baichuan, and Yi, plus a GPT Academic integration. It closes with the engineering step most tutorials skip, exporting models to ONNX, TensorRT acceleration, and PTQ/QAT quantization, which is where the value of a trained model actually shows up in production. Because every chapter pairs theory with runnable code, the book works both as a structured self-study path and as a reference to flip open when you need a working example for a specific task.