RRepoGEO

REPOGEO REPORT · LITE

cerlymarco/MEDIUM_NoteBook

Default branch master · commit 8496749e · scanned 5/17/2026, 6:28:07 PM

GitHub: 2,136 stars · 974 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
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 cerlymarco/MEDIUM_NoteBook, 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 H1 and opening sentence

    Why:

    CURRENT
    # MEDIUM_NoteBook
Repository containing notebooks of my posts on MEDIUM.
    COPY-PASTE FIX
    # MEDIUM_NoteBook: Practical Jupyter Notebooks for Data Science & ML Blog Posts
This repository provides the runnable Jupyter notebooks and practical code examples that accompany my articles published on Medium, focusing on advanced machine learning, data science, and AI techniques.
  • mediumtopics#2
    Add more specific topics to improve query matching

    Why:

    CURRENT
    artificial-intelligence, data-science, deep-learning, machine-learning, notebooks
    COPY-PASTE FIX
    artificial-intelligence, data-science, deep-learning, machine-learning, notebooks, jupyter-notebooks, time-series-forecasting, explainability, causal-inference, mlops, survival-analysis, blog-code, medium-posts
  • lowhomepage#3
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://medium.com/

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 cerlymarco/MEDIUM_NoteBook
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Prophet
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Prophet · recommended 1×
  2. XGBoost / LightGBM · recommended 1×
  3. PyTorch Forecasting · recommended 1×
  4. sktime · recommended 1×
  5. statsmodels · recommended 1×
  • CATEGORY QUERY
    What are good resources for advanced time series forecasting techniques using machine learning?
    you: not recommended
    AI recommended (in order):
    1. Prophet
    2. XGBoost / LightGBM
    3. PyTorch Forecasting
    4. sktime
    5. statsmodels
    6. GluonTS

    AI recommended 6 alternatives but never named cerlymarco/MEDIUM_NoteBook. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find practical machine learning notebooks for explainability or causal inference?
    you: not recommended
    AI recommended (in order):
    1. SHAP
    2. LIME
    3. InterpretML
    4. DoWhy
    5. EconML
    6. CausalML
    7. What-If Tool (WIT)

    AI recommended 7 alternatives but never named cerlymarco/MEDIUM_NoteBook. 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 cerlymarco/MEDIUM_NoteBook?
    pass
    AI did not name cerlymarco/MEDIUM_NoteBook — 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 cerlymarco/MEDIUM_NoteBook in production, what risks or prerequisites should they evaluate first?
    pass
    AI named cerlymarco/MEDIUM_NoteBook 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 cerlymarco/MEDIUM_NoteBook solve, and who is the primary audience?
    pass
    AI did not name cerlymarco/MEDIUM_NoteBook — 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?

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cerlymarco/MEDIUM_NoteBook — 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