Dive into Deep Learning (D2L.ai)
@d2l-ai • Open source projects from d2l-ai. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
82%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
30 repos
Visible snapshot
0 repositories updated in the last 90 days.
Leading language
Jupyter Notebook
Portfolio mix
Jupyter Notebook (26), Python (3), Unknown (1)
Average size
77
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2023-08-18(1103d ago)GitHub API fallback30 repositories
82%
of the visible star count comes from this organization's top three repositories.
77
stars per repository in this same snapshot.
Jupyter Notebook
is the most common language here, with 0 repositories updated in the last 90 days.
Why this rank
This organization stands out because its public portfolio is relatively balanced across 30 repositories.
Balanced portfolio across 30 reposTop 3 share 82%
Organization pages work best when you separate portfolio breadth from flagship concentration. In Dive into Deep Learning (D2L.ai)'s case, the visible top three repositories account for about 82% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Jupyter Notebook (26), Python (3), Unknown (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | d2l-ai/d2l-zh-pytorch-slides Pytorch版代码幻灯片 | Jupyter Notebook | 821 |
| 2 | d2l-ai/courses-zh-v2 中文版 v2 课程 | Jupyter Notebook | 811 |
| 3 | d2l-ai/d2l-pytorch-slides Automatically Generated Notebook Slides | Jupyter Notebook | 267 |
| 4 | d2l-ai/d2l-pytorch-colab Automatically Generated Notebooks for Colab | Jupyter Notebook | 76 |
| 5 | d2l-ai/d2l-zh-pytorch-colab Automatically Generated d2l-zh PyTorch Notebooks for Colab | Jupyter Notebook | 70 |
| 6 | d2l-ai/d2l-pt Livro Interativo de Deep Learning com Multiplos Frameworks, Conceitos Matemáticos e Discussões | Python | 64 |
| 7 | d2l-ai/d2l-en-colab Automatically Generated Notebooks for Colab | Jupyter Notebook | 51 |
| 8 | d2l-ai/d2l-tensorflow-colab Automatically Generated Notebooks for Colab | Jupyter Notebook | 40 |
| 9 | d2l-ai/d2l-pytorch-sagemaker Automatically Generated Notebook for Sagemaker | Jupyter Notebook | 34 |
| 10 | d2l-ai/d2l-pytorch-sagemaker-studio-lab | Jupyter Notebook | 19 |
| 11 | d2l-ai/d2l-zh-colab Automatically Generated d2l-zh Notebooks for Colab | Jupyter Notebook | 18 |
| 12 | d2l-ai/d2l-zh-tensorflow-colab Automatically Generated d2l-zh TensorFlow Notebooks for Colab | Jupyter Notebook | 12 |
| 13 | d2l-ai/d2l-zh-pytorch-sagemaker Automatically Generated d2l-zh PyTorch Notebooks for SageMaker | Jupyter Notebook | 9 |
| 14 | d2l-ai/d2l-tensorflow-sagemaker | Jupyter Notebook | 6 |
| 15 | d2l-ai/d8 | Python | 4 |
| 16 | d2l-ai/d2l-pytorch-slides-classic Automatically Generated Notebook Slides for https://classic.d2l.ai/ | Jupyter Notebook | 3 |
| 17 | d2l-ai/d2l-de German version of d2l-en | Python | 3 |
| 18 | d2l-ai/d2l-jax-colab | Jupyter Notebook | 2 |
| 19 | d2l-ai/d2l-zh-paddle-colab Automatically Generated d2l-zh PyTorch Notebooks for Colab | Jupyter Notebook | 2 |
| 20 | d2l-ai/d2l-zh-tensorflow-sagemaker Automatically Generated d2l-zh TensorFlow Notebooks for SageMaker | Jupyter Notebook | 2 |
| 21 | d2l-ai/d2l-tensorflow-colab-classic Automatically Generated Colab Notebooks for https://classic.d2l.ai/ | Jupyter Notebook | 1 |
| 22 | d2l-ai/d2l-pytorch-colab-classic Automatically Generated Colab Notebooks for https://classic.d2l.ai/ | Jupyter Notebook | 1 |
| 23 | d2l-ai/d2l-zh-paddle-sagemaker Automatically Generated d2l-zh TensorFlow Notebooks for SageMaker | Jupyter Notebook | 1 |
| 24 | d2l-ai/d2l-zh-sagemaker Automatically Generated d2l-zh Notebooks for SageMaker | Jupyter Notebook | 1 |
| 25 | d2l-ai/d2l-jax-sagemaker | Jupyter Notebook | 0 |
| 26 | d2l-ai/d2l-tensorflow-sagemaker-classic Automatically Generated Sagemaker Notebooks for https://classic.d2l.ai/ | Jupyter Notebook | 0 |
| 27 | d2l-ai/d2l-pytorch-sagemaker-classic Automatically Generated Sagemaker Notebooks for https://classic.d2l.ai/ | Jupyter Notebook | 0 |
| 28 | d2l-ai/d2l-en-sagemaker-classic Automatically Generated Sagemaker Notebooks for https://classic.d2l.ai/ | Jupyter Notebook | 0 |
| 29 | d2l-ai/d2l-en-colab-classic Automatically Generated Colab Notebooks for https://classic.d2l.ai/ | Jupyter Notebook | 0 |
| 30 | d2l-ai/aws-hugo-them | 0 |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.