tensorflow
by tensorflowAn Open Source Machine Learning Framework for Everyone
In simple words: d2l-zh is a free book and learning collection — you read it, you do not install it, for learning new skills and knowledge at your own pace. It is completely free and open source — its code is public on GitHub, where 82,325 people have bookmarked it as worth using.
💡 A real-life example: A shop owner uses a tool like this to turn a long voice note into clean written text, then replies to customers much faster.
RepoEasy wrote this simple explanation from the project's public data — its category, topics and description — so a beginner can understand it before downloading anything. For exact technical details, the project's own README (linked below) is the final word.
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
This is the project's own description from GitHub — we show it as-is rather than inventing details.
This project is listed under AI Research Tools in Artificial Intelligence, a category made for creators, businesses, students and developers who want to use AI without getting lost in research papers.
Do I need coding knowledge? Coding Knowledge Recommended. (Estimate based on project type: A developer tool/library — setup usually follows the README with basic coding skills. Always confirm from the repo's README.)
The source code is released under the Apache-2.0 license. Open-source licenses like this usually allow free use, including commercial use — but always read the actual license file in the repository before relying on it. Note: the code being free does not mean hosted services, APIs or infrastructure around it are free.
Activity level: Quiet · Last code update: 30 Jul 2024 · Created: 23 Aug 2017 · Open issues: 130
Official links: Official Website ↗ · Releases ↗ · Documentation (README) ↗
We never publish installation steps we have not verified — the README above is the source of truth.
⭐ 82325 stars · 🍴 12479 forks · 🐛 130 open issues · 💻 Language: Python · 📄 License: Apache-2.0 · Default branch: master
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Stable Diffusion web UI
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Open Source Computer Vision Library