RRepoGEO

REPOGEO REPORT · LITE

nndl/nndl-discussion

Default branch master · commit 2dbd16aa · scanned 6/10/2026, 5:07:57 AM

GitHub: 787 stars · 85 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
30 /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
3 / 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 nndl/nndl-discussion, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 and opening paragraph to specify textbook discussion

    Why:

    CURRENT
    # 蒲公英书系列讨论区

蒲公英书系列（邱锡鹏 的神经网络与深度学习系列教材）的社区讨论入口。
    COPY-PASTE FIX
    # 《神经网络与深度学习》教材讨论区：课后习题答案与概念交流

本仓库是邱锡鹏教授《神经网络与深度学习》系列教材的官方社区讨论入口，专注于课后习题答案分享、概念理解问答以及深度学习学习路径交流。
  • highlicense#2
    Add a LICENSE file to clarify usage terms

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with the text for a Creative Commons Attribution-ShareAlike 4.0 International License (CC-BY-SA-4.0), suitable for educational content and discussions.

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 nndl/nndl-discussion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Reddit
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Reddit · recommended 2×
  2. Stack Overflow / Stack Exchange · recommended 1×
  3. Discord · recommended 1×
  4. Kaggle · recommended 1×
  5. GitHub · recommended 1×
  • CATEGORY QUERY
    Where can I find a community discussing solutions to neural network textbook exercises?
    you: not recommended
    AI recommended (in order):
    1. Stack Overflow / Stack Exchange
    2. Reddit
    3. Discord
    4. Kaggle
    5. GitHub
    6. Fast.ai
    7. Coursera/edX/Udacity

    AI recommended 7 alternatives but never named nndl/nndl-discussion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an online forum to discuss deep learning concepts and study materials.
    you: not recommended
    AI recommended (in order):
    1. Kaggle Forums
    2. Reddit
    3. Stack Overflow
    4. fast.ai Forums
    5. Analytics Vidhya Community
    6. Towards Data Science

    AI recommended 6 alternatives but never named nndl/nndl-discussion. 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 nndl/nndl-discussion?
    pass
    AI named nndl/nndl-discussion explicitly

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

  • If a team adopts nndl/nndl-discussion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named nndl/nndl-discussion 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 nndl/nndl-discussion solve, and who is the primary audience?
    pass
    AI named nndl/nndl-discussion explicitly

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

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nndl/nndl-discussion — 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