RRepoGEO

REPOGEO REPORT · LITE

visionNoob/CS231N_17_KOR_SUB

Default branch master · commit 6844d9c9 · scanned 6/1/2026, 6:43:12 PM

GitHub: 700 stars · 212 forks

AI VISIBILITY SCORE
28 /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
2 / 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 visionNoob/CS231N_17_KOR_SUB, 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's opening to clearly state its purpose

    Why:

    CURRENT
    # Korean Subtitles for CS231n Spring 2017
# CS231n 한글번역

Translation project of CS231n 2017 lecture video
    COPY-PASTE FIX
    # Korean Subtitles for Stanford CS231n Spring 2017 Lectures

This project offers a complete set of Korean subtitles for the official Stanford CS231n 2017 course videos, specifically designed for Korean-speaking learners interested in computer vision and deep learning.
  • highhomepage#2
    Add the official CS231n website as the repository homepage

    Why:

    COPY-PASTE FIX
    http://cs231n.stanford.edu/2017/
  • mediumtopics#3
    Add more specific topics to improve categorization

    Why:

    CURRENT
    cs231n, subtitle
    COPY-PASTE FIX
    cs231n, subtitle, korean-translation, deep-learning, computer-vision, neural-networks, stanford-course, educational-resource

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 visionNoob/CS231N_17_KOR_SUB
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Naver D2 Campus
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Naver D2 Campus · recommended 1×
  2. FastCampus · recommended 1×
  3. Inflearn · recommended 1×
  4. Google Translate · recommended 1×
  5. DeepL · recommended 1×
  • CATEGORY QUERY
    Where can I find Korean translated materials for advanced deep learning courses?
    you: not recommended
    AI recommended (in order):
    1. Naver D2 Campus
    2. FastCampus
    3. Inflearn
    4. Google Translate
    5. DeepL

    AI recommended 5 alternatives but never named visionNoob/CS231N_17_KOR_SUB. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking resources to learn computer vision with university lecture subtitles in Korean.
    you: not recommended
    AI recommended (in order):
    1. Stanford CS231n: Convolutional Neural Networks for Visual Recognition
    2. KAIST CS492: Introduction to Artificial Intelligence
    3. SNU 4190.310: Computer Vision (Seoul National University)
    4. Coursera
    5. edX
    6. Deep Learning Specialization by Andrew Ng
    7. KOCW (Korea Open CourseWare)

    AI recommended 7 alternatives but never named visionNoob/CS231N_17_KOR_SUB. 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 visionNoob/CS231N_17_KOR_SUB?
    pass
    AI named visionNoob/CS231N_17_KOR_SUB explicitly

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

  • If a team adopts visionNoob/CS231N_17_KOR_SUB in production, what risks or prerequisites should they evaluate first?
    pass
    AI named visionNoob/CS231N_17_KOR_SUB 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 visionNoob/CS231N_17_KOR_SUB solve, and who is the primary audience?
    pass
    AI did not name visionNoob/CS231N_17_KOR_SUB — 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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visionNoob/CS231N_17_KOR_SUB — 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