aymericdamien/TopDeepLearning

What it is

TopDeepLearning is a simple curated list of popular GitHub projects related to deep learning. It's not software you install or run — it's a reference document that collects well-known open-source projects and ranks them by how many stars they have on GitHub.

How it's organized

The README is a single table with three columns: Project Name, Stars, and Description. Each row is one GitHub project. The list is explicitly "ranked by stars," so the projects appear in descending order of popularity (from 383k stars down to 51k at the point where the README cuts off). The README notes a last update date of 2026.07.14.

What's in the list

The projects span a wide range of deep-learning-adjacent topics, including:

• Classic machine-learning frameworks (TensorFlow, PyTorch, Keras, scikit-learn)
• Large language model tools and frameworks (transformers, llama.cpp, vLLM, Ollama)
• AI agent and coding-assistant tools (AutoGPT, Claude Code, OpenHands, LangChain)
• Image generation and computer vision (Stable Diffusion WebUI, ComfyUI, OpenCV, YOLO)
• Speech and audio (Whisper, GPT-SoVITS, Real-Time-Voice-Cloning)
• Educational resources (courses like "Generative AI for Beginners," "ML for Beginners," and books like "动手学深度学习")
• Various utilities like OCR tools, web scrapers, and workflow automation platforms

What it doesn't do

The README contains no instructions, no code, no analysis, and no commentary. It's purely a listing — the value is in the curation and the star counts, which give a quick sense of which deep-learning projects are most popular in the GitHub community. The descriptions in the table are copied from each project's own one-line summary.

Bottom line

If you want a quick, at-a-glance snapshot of the most-starred deep-learning-related repositories on GitHub, this list gives you that in one table. It's a starting point for discovery rather than a tutorial or a tool.