RRepoGEO

REPOGEO REPORT · LITE

Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources

Default branch main · commit 6fe48e5c · scanned 6/3/2026, 1:42:58 PM

GitHub: 524 stars · 125 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 Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources, 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
    Clarify the README's opening to emphasize it's a curated list of resources

    Why:

    CURRENT
    # Compendium of free ML reading resources
    COPY-PASTE FIX
    # Compendium of Free Machine Learning Reading Resources: A Curated List for Self-Learners
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License or CC-BY-4.0 for content) in the repository root to clearly state usage terms.
  • mediumhomepage#3
    Add a homepage URL in the repository settings

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    Add a relevant URL (e.g., the GitHub repo URL itself, or a dedicated project page if one exists) to the repository's homepage field in the About section.

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 Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Scikit-Learn
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Scikit-Learn · recommended 1×
  2. Keras · recommended 1×
  3. TensorFlow · recommended 1×
  4. R · recommended 1×
  5. Coursera: Machine Learning by Andrew Ng (Stanford University) · recommended 1×
  • CATEGORY QUERY
    Where can I find a good collection of free online books for learning machine learning concepts?
    you: not recommended
    AI recommended (in order):
    1. Scikit-Learn
    2. Keras
    3. TensorFlow
    4. R

    AI recommended 4 alternatives but never named Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    I need free resources to understand core machine learning algorithms and statistical methods.
    you: not recommended
    AI recommended (in order):
    1. Coursera: Machine Learning by Andrew Ng (Stanford University)
    2. edX: Introduction to Probability and Statistics (MIT)
    3. Khan Academy: Statistics and Probability
    4. Google's Machine Learning Crash Course
    5. An Introduction to Statistical Learning with Applications in R (ISLR)
    6. The Elements of Statistical Learning: Data Mining, Inference, and Prediction (ESL)

    AI recommended 6 alternatives but never named Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources. 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 Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources?
    pass
    AI did not name Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources — 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 Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources 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 Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources solve, and who is the primary audience?
    pass
    AI did not name Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources — 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

Drop this badge into the README of Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources — 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