RRepoGEO

REPOGEO REPORT · LITE

arbox/machine-learning-with-ruby

Default branch master · commit c8c2503b · scanned 5/28/2026, 11:17:51 PM

GitHub: 2,212 stars · 181 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 arbox/machine-learning-with-ruby, 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 README's opening statement to immediately clarify repo's nature

    Why:

    CURRENT
    > Curated List of Ruby Machine Learning Links and Resources

[Machine Learning][ml] is a field of [Computational Science][cs] - often nested under [AI][ai] research - with many practical applications due to the ability of resulting algorithms to systematically implement a specific solution without explicit programmer's instructions. Obviously many algorithms need a definition of [features][fe] to look at or a biggish [training set][ts] of data to derive the solution from.
    COPY-PASTE FIX
    This is a curated list of awesome libraries, data sources, tutorials, and presentations for Machine Learning utilizing the Ruby programming language.
  • hightopics#2
    Refine repository topics to accurately reflect a curated list

    Why:

    CURRENT
    awesome, awesome-list, list, machine-learning, ml, ruby, ruby-gem, rubyml, rubynlp
    COPY-PASTE FIX
    awesome, awesome-list, list, machine-learning, ml, ruby, rubyml, rubynlp, resources, links
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/arbox/machine-learning-with-ruby

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 arbox/machine-learning-with-ruby
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SciRuby
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. SciRuby · recommended 2×
  2. NMatrix · recommended 2×
  3. StatSample · recommended 2×
  4. Daru · recommended 2×
  5. TensorFlow.rb · recommended 2×
  • CATEGORY QUERY
    How can I find good resources for machine learning development using Ruby?
    you: not recommended
    AI recommended (in order):
    1. SciRuby
    2. NMatrix
    3. StatSample
    4. Daru
    5. Ruby-ML
    6. TensorFlow.rb
    7. Torch.rb
    8. PyCall
    9. scikit-learn
    10. NumPy
    11. Pandas
    12. TensorFlow
    13. PyTorch
    14. rb-libsvm
    15. Shogun

    AI recommended 15 alternatives but never named arbox/machine-learning-with-ruby. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best libraries and tools for building AI models in Ruby?
    you: not recommended
    AI recommended (in order):
    1. SciRuby
    2. NMatrix
    3. StatSample
    4. Daru
    5. rb-gsl
    6. Ruby-FFI
    7. TensorFlow.rb
    8. JRuby
    9. Deeplearning4j (DL4J)
    10. Weka
    11. Stanford CoreNLP
    12. RSRuby
    13. Machine Learning Ruby (ML-Ruby)

    AI recommended 13 alternatives but never named arbox/machine-learning-with-ruby. 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 arbox/machine-learning-with-ruby?
    pass
    AI named arbox/machine-learning-with-ruby explicitly

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

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