RRepoGEO

REPOGEO REPORT · LITE

MLNLP-World/DeepLearning-MuLi-Notes

Default branch main · commit 1e25f811 · scanned 5/24/2026, 7:17:38 AM

GitHub: 3,781 stars · 593 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 MLNLP-World/DeepLearning-MuLi-Notes, 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
    Add a clear English summary to the README's opening

    Why:

    COPY-PASTE FIX
    Add the following sentence immediately after the main title/badges in the README: 'This repository provides comprehensive community-contributed markdown notes and Jupyter code examples for the popular "Dive into Deep Learning" (D2L.ai) course by Mu Li, designed as a self-paced study companion.'
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root containing the full text of the MIT License.
  • mediumhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    In the repository settings, set the 'Website' field (homepage) to `https://d2l.ai/` (the official 'Dive into Deep Learning' course website).

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 MLNLP-World/DeepLearning-MuLi-Notes
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
fast.ai's Practical Deep Learning for Coders
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. fast.ai's Practical Deep Learning for Coders · recommended 1×
  2. Deep Learning with PyTorch: A 60 Minute Blitz (Official PyTorch Tutorials) · recommended 1×
  3. Stanford CS231n: Convolutional Neural Networks for Visual Recognition · recommended 1×
  4. Deep Learning Specialization by Andrew Ng (Coursera/DeepLearning.AI) · recommended 1×
  5. pytorch/examples · recommended 1×
  • CATEGORY QUERY
    How can I find comprehensive deep learning course notes with practical PyTorch examples?
    you: not recommended
    AI recommended (in order):
    1. fast.ai's Practical Deep Learning for Coders
    2. Deep Learning with PyTorch: A 60 Minute Blitz (Official PyTorch Tutorials)
    3. Stanford CS231n: Convolutional Neural Networks for Visual Recognition
    4. Deep Learning Specialization by Andrew Ng (Coursera/DeepLearning.AI)
    5. PyTorch Examples (pytorch/examples)
    6. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

    AI recommended 6 alternatives but never named MLNLP-World/DeepLearning-MuLi-Notes. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find structured self-paced deep learning tutorials including code and explanations?
    you: not recommended
    AI recommended (in order):
    1. fast.ai Practical Deep Learning for Coders
    2. DeepLearning.AI's Deep Learning Specialization
    3. PyTorch (pytorch/pytorch)
    4. TensorFlow (tensorflow/tensorflow)
    5. Kaggle Learn
    6. Google's Machine Learning Crash Course
    7. Hugging Face Transformers (huggingface/transformers)

    AI recommended 7 alternatives but never named MLNLP-World/DeepLearning-MuLi-Notes. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 MLNLP-World/DeepLearning-MuLi-Notes?
    pass
    AI did not name MLNLP-World/DeepLearning-MuLi-Notes — 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 MLNLP-World/DeepLearning-MuLi-Notes in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MLNLP-World/DeepLearning-MuLi-Notes explicitly

    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 MLNLP-World/DeepLearning-MuLi-Notes solve, and who is the primary audience?
    pass
    AI did not name MLNLP-World/DeepLearning-MuLi-Notes — 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

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MARKDOWN (README)
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MLNLP-World/DeepLearning-MuLi-Notes — 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