RRepoGEO

REPOGEO REPORT · LITE

daturkel/learning-papers

Default branch master · commit 61be7d4b · scanned 6/12/2026, 12:42:51 PM

GitHub: 725 stars · 48 forks

AI VISIBILITY SCORE
35 /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
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 daturkel/learning-papers, 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
  • hightopics#1
    Add more specific topics for discoverability

    Why:

    CURRENT
    machine-learning, papers
    COPY-PASTE FIX
    machine-learning, papers, curated-list, foundational-papers, ml-history, research-papers, deep-learning-papers
  • highreadme#2
    Reposition README opening to highlight curated resource nature

    Why:

    CURRENT
    ### Landmark Papers in Machine Learning

*This document attempts to collect the papers which developed important techniques in machine learning.
    COPY-PASTE FIX
    ### Landmark Papers in Machine Learning: A Curated Collection for Researchers and Students

*This repository is a curated collection of landmark academic papers in machine learning, designed to facilitate learning and research by highlighting foundational techniques and significant contributions.*
  • mediumhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/daturkel/learning-papers

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 daturkel/learning-papers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Papers With Code
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Papers With Code · recommended 1×
  2. Google Scholar · recommended 1×
  3. The Hundred-Page Machine Learning Book by Andriy Burkov · recommended 1×
  4. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville · recommended 1×
  5. Distill.pub · recommended 1×
  • CATEGORY QUERY
    What are the foundational research papers every machine learning engineer should know?
    you: not recommended
    Show full AI answer
  • CATEGORY QUERY
    Where can I find a curated list of influential machine learning papers for historical context?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. Google Scholar
    3. The Hundred-Page Machine Learning Book by Andriy Burkov
    4. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
    5. Distill.pub
    6. Towards Data Science
    7. Medium

    AI recommended 7 alternatives but never named daturkel/learning-papers. 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 daturkel/learning-papers?
    pass
    AI named daturkel/learning-papers explicitly

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

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

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

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