RRepoGEO

REPOGEO REPORT · LITE

d2l-ai/d2l-zh-pytorch-slides

Default branch main · commit 341c193b · scanned 6/15/2026, 9:12:36 AM

GitHub: 805 stars · 179 forks

AI VISIBILITY SCORE
10 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
0 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface d2l-ai/d2l-zh-pytorch-slides, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 and add a clarifying sentence

    Why:

    CURRENT
    # d2l-ai/d2l-zh-pytorch-slides
    COPY-PASTE FIX
    # Dive into Deep Learning (D2L) PyTorch Chinese Slides

This repository provides presentation slides in Chinese for the "Dive into Deep Learning" textbook, specifically for the PyTorch implementation.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    deep-learning, pytorch, education, slides, machine-learning, d2l, chinese, jupyter-notebooks, presentation
  • highlicense#3
    Add a clear license statement to the README

    Why:

    COPY-PASTE FIX
    ## License

This repository's content, including all slides and notebooks, is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0), aligning with the educational nature of the Dive into Deep Learning project. Please refer to the official D2L website for specific licensing details of the main textbook.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface d2l-ai/d2l-zh-pytorch-slides
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Colaboratory
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Colaboratory · recommended 1×
  2. Kaggle Learn · recommended 1×
  3. Jupyter Notebooks · recommended 1×
  4. DeepLearning.AI · recommended 1×
  5. pytorch/pytorch · recommended 1×
  • CATEGORY QUERY
    Where can I find interactive code examples for learning deep neural networks?
    you: not recommended
    AI recommended (in order):
    1. Google Colaboratory
    2. Kaggle Learn
    3. Jupyter Notebooks
    4. DeepLearning.AI
    5. PyTorch (pytorch/pytorch)
    6. TensorFlow (tensorflow/tensorflow)

    AI recommended 6 alternatives but never named d2l-ai/d2l-zh-pytorch-slides. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help create engaging presentations from machine learning notebooks?
    you: not recommended
    AI recommended (in order):
    1. Voilà (jupyter/voila)
    2. Mercury (mljar/mercury)
    3. nbconvert (jupyter/nbconvert)
    4. Reveal.js (hakimel/reveal.js)
    5. LaTeX/Beamer
    6. Streamlit (streamlit/streamlit)
    7. Gradio (gradio-app/gradio)
    8. Panel (holoviz/panel)
    9. Dash (plotly/dash)

    AI recommended 9 alternatives but never named d2l-ai/d2l-zh-pytorch-slides. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of d2l-ai/d2l-zh-pytorch-slides?
    pass
    AI did not name d2l-ai/d2l-zh-pytorch-slides — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts d2l-ai/d2l-zh-pytorch-slides in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name d2l-ai/d2l-zh-pytorch-slides — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo d2l-ai/d2l-zh-pytorch-slides solve, and who is the primary audience?
    pass
    AI did not name d2l-ai/d2l-zh-pytorch-slides — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of d2l-ai/d2l-zh-pytorch-slides. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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d2l-ai/d2l-zh-pytorch-slides — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite