d2l-ai/d2l-zh
Rank not captured·Top 100·All-time stars·Cached ranking snapshot·
《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。
First read
Real package usage exists, but freshness needs a closer look
d2l-ai/d2l-zh shows signs of reuse beyond stars, yet recent activity is softer. Read the repository as a potentially durable dependency, but verify maintenance rhythm before treating it as a default choice.
Visible
79.7K public stars in the current GitStar snapshot.
Recognizable in the ecosystem
Active
Last commit Jul 30, 2024.
Stale activity
Adopted
pypi gives the strongest production-style signal.
8M/week
Confidence
One or more key signals are partial, so GitStar keeps the interpretation conservative.
Partial snapshot
Snapshot facts
- 79.7K stars
- 12.3K forks
- Last commit Jul 30, 2024
- pypi 8M/week
Compare lens
huggingface/transformers and ultralytics/ultralytics are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.
Signal trail
Trajectory
Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.
Daily momentum
Recent momentum is not captured
Weekly momentum
Recent momentum is not captured
Monthly momentum
Recent momentum is not captured
Last commit
Jul 30, 2024
Package reality
GitStar found pypi:notebook. Package traffic can help separate visible repositories from dependencies that are quietly used in real workflows.
Hype vs Reality
Balanced
Package mapping
pypi · notebook
Cross-links
Standalone repo read
Validation note
GitStar can summarize public signals for d2l-ai/d2l-zh, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.
Package signal
Install & Package Signals
GitStar uses the strongest linked package signal below when it reads Hype vs Reality for this repository.
Balanced
Recent attention and package usage are moving in the same direction.
PyPI package
notebook
8M downloads/week
pip install notebook
🛡️ Editorial Context
GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.
Why this rank
This repository stands out because it combines package adoption and stable visibility.
Package adoptionStable visibility
📈 Momentum & Adoption Signals
Approximate star trajectory
Reconstructed from current stars and cached daily/weekly/monthly deltas.
Now: 79.7K
Daily momentum
No signal
Weekly momentum
No signal
Monthly momentum
No signal
Signal mix (log-scaled for readability)
Current stars79.7K
Weekly package downloads8M
🧭 Hype vs Reality
BalancedRecent attention and package usage are moving in the same direction.
This usually means the project has both mindshare and a measurable production footprint, which makes it a stronger validation candidate.
Status
Balanced
Package footprint
PyPI · 8M/week
Method note
Balanced means GitStar sees both meaningful package adoption and enough current star velocity or scale to avoid reading the repo as purely niche. Compare it against other Python repos before treating stars as a moat.
Related alternative
huggingface/transformers
Shares the learning category footprint with d2l-ai/d2l-zh, so the comparison is closer to a same-problem decision than a same-language coincidence.
Related alternative
ultralytics/ultralytics
Shares the learning category footprint with d2l-ai/d2l-zh, so the comparison is closer to a same-problem decision than a same-language coincidence.
Related alternative
roboflow/supervision
Shares the learning category footprint with d2l-ai/d2l-zh, so the comparison is closer to a same-problem decision than a same-language coincidence.
Related alternative
rohitg00/ai-engineering-from-scratch
Shares the learning category footprint with d2l-ai/d2l-zh, so the comparison is closer to a same-problem decision than a same-language coincidence.
Research links
Cross-links
Compare against related repos
GitStar picked transformers + ultralytics as the closest next comparison from the related repository set.
Repo utility
Embed Badge
Preview:
Markdown
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Wider nearby ecosystem
Python
164.1K starshuggingface/transformers
🤗 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.
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60.6K starsultralytics/ultralytics
Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Python
49.4K starsroboflow/supervision
We write your reusable computer vision tools. 💜
Python
46.7K starsrohitg00/ai-engineering-from-scratch
Learn it. Build it. Ship it for others.
Python
33.8K starsexplosion/spaCy
💫 Industrial-strength Natural Language Processing (NLP) in Python
Python
21.8K starshuggingface/datasets
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Next step after the validation read
Move into a compare preset, organization view, or the heuristic notes once this first fold tells you whether the repo looks visible, active, adopted, and credible enough to keep researching.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
About This Page
This page provides a quick overview of d2l-ai/d2l-zh based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.
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