ritchieng/the-incredible-pytorch

The Incredible PyTorch is a curated collection of links to tutorials, research papers, projects, libraries, videos, and communities focused on PyTorch, a widely used open-source framework for building machine learning models. The list is organized into dozens of topic categories so that someone working in a specific area can find relevant resources without searching from scratch. The categories span a wide range of machine learning topics. On the foundational side there are general PyTorch tutorials, books on deep learning math, and project templates. More specialized sections cover large language models, AI agents, image object detection, speech recognition, text generation, style transfer, reinforcement learning, and many more. Applied science sections include uses of neural networks in chemistry and physics, medical image analysis, and 3D data. There are also sections on practical engineering topics like model quantization, neural network compression, and performance optimization. The list is maintained by ritchieng, who accepts community contributions via pull request. It has grown to cover not just learning resources but also production-level tools and curated reading lists for researchers. A separate dedicated sub-list on AI agents has been spun off from the main list. This repository contains no runnable code. It is a reference index, meaning its value is in the links it collects and keeps organized. Someone new to deep learning who wants to know where to start, or an experienced practitioner looking for papers and implementations in a niche area, would use it as a starting point. PyTorch itself is an open-source machine learning framework originally created by Meta, now widely used across industry and academic research for training and running neural networks. The full README is longer than what was shown.