Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
| Date | Stars |
|---|---|
| 2026-07-24 | 29224 |
| 2026-07-25 | 29229 |
| 2026-07-28 | 29229 |
| 2026-07-30 | 29229 |
| 2026-07-31 | 29273 |
| 2026-08-06 | 29319 |
Today
+46 stars today
This week
+90 stars this week
This month
— stars this month
Momentum
24.0
growth rate 0.31%/day
<div align="left">
<img src="https://raw.githubusercontent.com/d2l-ai/d2l-en/master/static/logo-with-text.png" width="350">
</div>
# D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions
[](https://github.com/d2l-ai/d2l-en/actions/workflows/ci.yml)
[Book website](https://d2l.ai/) | [STAT 157 Course at UC Berkeley](http://courses.d2l.ai/berkeley-stat-157/index.html)
<h5 align="center"><i>The best way to understand deep learning is learning by doing.</i></h5>
<p align="center">
<img width="200" src="static/frontpage/_images/eq.jpg">
<img width="200" src="static/frontpage/_images/figure.jpg">
<img width="200" src="static/frontpage/_images/code.jpg">
<img width="200" src="static/frontpage/_images/notebook.gif">
</p>
This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code.
Our goal is to offer a resource that could
1. be freely available for everyone;
1. offer sufficient technical depth to provide a starting point on the path to actually becoming an applied machine learning scientist;
1. include runnable code, showing readers how to solve problems in practice;
1. allow for rapid updates, both by us and also by the community at large;
1. be complemented by a forum for interactive discussion of technical details and to answer questions.
## Universities Using D2L
<p align="center">
<img width="600" src="static/frontpage/_images/map.png">
</p>
If you find this book useful, please star (★) this repository or cite this book using the following bibtex entry:
```
@book{zhang2023dive,
title={Dive into Deep Learning},
author={Zhang, Aston and Lipton, Zachary C. and Li, Mu and Smola, Alexander J.},
publisher={Cambridge University Press},
note={\url{https://D2L.ai}},
year={2023}
}
```
## Endorsements
> <p>"In less than a decade, the AI revolution has swept from research labs to broad industries to every corner of our daily life. Dive into Deep Learning is an excellent text on deep learning and deserves attention from anyone who wants to learn why deep learning has ignited the AI revolution: the most powerful technology force of our time."</p>
> <b>— Jensen Huang, Founder and CEO, NVIDIA</b>
> <p>"This is a timely, fascinating book, providing with not only a comprehensive overview of deep learning principles but also detailed algorithms with hands-on programming code, and moreover, a state-of-the-art introduction to deep learning in computer vision and natural language processing. Dive into this book if you want to dive into deep learning!"</p>
> <b>— Jiawei Han, Michael Aiken Chair Professor, University of Illinois at Urbana-Champaign</b>
> <p>"This is a highly welcome addition to the machine learning literature, with a focus on hands-on experience implemented via the integration of Jupyter notebooks. Students of deep learning should find this invaluable to become proficient in this field."</p>
> <b>— Bernhard Schölkopf, Director, Max Planck Institute for Intelligent Systems</b>
> <p>"Dive into Deep Learning strikes an excellent balance between hands-on learning and in-depth explanation. I've used it in my deep learning course and recommend it to anyone who wants to develop a thorough and practical understanding of deep learning."</p>
> <b>— Colin Raffel, Assistant Professor, University of North Carolina, Chapel Hill</b>
## Contributing ([Learn How](https://d2l.ai/chapter_appendix-tools-for-deep-learning/contributing.html))
This open source book has benefited from pedagogical suggestions, typo corrections, and other improvements from community contributors. Your help is valuable for making the book better for everyExcerpt of 4,754 characters
Read on GitHub
Aston Zhang · Meta · United States
3.1k
Mu Li · Boson AI · United States
498
Alex Smola · Boson AI · United States
416
Anirudh Dagar · @aws @autogluon @d2l-ai · Germany
382
Zack Chase Lipton · CMU, Amazon · United States
185
Rachel Hu
163
Andrew Gordon Wilson
137
Matthias Seeger · Amazon · Germany
87
Aaron Klein · ELLIS Institute Tübingen
78
Yuan Tang · Red Hat · United States
68
Shuai Zhang · Amazon Web Services · United States
42
Cuong Nguyen · Vietnam
32
26
Abhinav Prakash · Dukaan · India
26
ShuShu
23
Mohamed Ali Jamaoui · Tunisia
23
Rasool Fakoor
18
Nodar Okroshiashvili · Georgia
16
Brent Werness · Amazon · United States
14
12
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6f247656ea1f7e0b, topic:deep-learning, topic:pytorch, topic:tensorflow