RRepoGEO

REPOGEO REPORT · LITE

louisfb01/start-machine-learning

Default branch master · commit a87e8e2a · scanned 7/1/2026, 6:12:55 PM

GitHub: 5,261 stars · 699 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
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 louisfb01/start-machine-learning, 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 H1/H2 to explicitly state it's a learning roadmap/guide

    Why:

    CURRENT
    # Start Machine Learning in 2026 - Become an expert for free!

## A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2026 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
    COPY-PASTE FIX
    # The Complete Machine Learning & AI Learning Roadmap (2026)

## Your free, comprehensive guide to start and improve in Machine Learning (ML) and Artificial Intelligence (AI) in 2026, designed for beginners with no background, to help you stay up-to-date with the latest techniques and become an expert!
  • mediumtopics#2
    Add more specific 'roadmap' or 'curated list' related topics

    Why:

    CURRENT
    artificial-intelligence, cheat-sheets, course, coursera, coursera-machine-learning, data-science, deep-learning, learn-to-code, learning, learning-python, linear-algebra, machine-learning, neural-networks, practice, probability-statistics, read-articles, tutorial, tutorials, youtube, youtube-playlist
    COPY-PASTE FIX
    artificial-intelligence, cheat-sheets, course, coursera, coursera-machine-learning, data-science, deep-learning, learn-to-code, learning, learning-python, linear-algebra, machine-learning, neural-networks, practice, probability-statistics, read-articles, tutorial, tutorials, youtube, youtube-playlist, learning-roadmap, curated-resources, beginner-friendly, career-path, study-guide
  • lowreadme#3
    Add a 'Why this guide?' section to the README

    Why:

    COPY-PASTE FIX
    ### Why this guide?

Unlike generic resource lists, this repository offers a structured, opinionated, and practical learning roadmap for Machine Learning and AI beginners. It prioritizes hands-on experience and provides specific resource recommendations with clear rationale, guiding you step-by-step to become an expert without needing any prior background. All resources are free or offer free alternatives, making advanced learning accessible to everyone.

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 louisfb01/start-machine-learning
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 2×
  2. TensorFlow · recommended 2×
  3. Scikit-Learn · recommended 2×
  4. Keras · recommended 2×
  5. Kaggle Learn · recommended 2×
  • CATEGORY QUERY
    Where can I find a comprehensive guide to begin learning machine learning and AI?
    you: not recommended
    AI recommended (in order):
    1. Coursera's 'Machine Learning' by Andrew Ng
    2. Octave/MATLAB
    3. fast.ai's 'Practical Deep Learning for Coders'
    4. PyTorch
    5. Google's Machine Learning Crash Course
    6. TensorFlow
    7. edX's 'CS50's Introduction to Artificial Intelligence with Python'
    8. 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow' by Aurélien Géron
    9. Scikit-Learn
    10. Keras
    11. 'Deep Learning' by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
    12. Kaggle Learn
    13. Python
    14. Pandas

    AI recommended 14 alternatives but never named louisfb01/start-machine-learning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good learning paths and resources for improving AI and ML skills?
    you: not recommended
    AI recommended (in order):
    1. Coursera
    2. Deep Learning Specialization by Andrew Ng (DeepLearning.AI)
    3. Machine Learning Specialization by Andrew Ng (Stanford University/DeepLearning.AI)
    4. IBM AI Engineering Professional Certificate
    5. Google Advanced Machine Learning Specialization
    6. edX
    7. MITx MicroMasters Program in Statistics and Data Science
    8. HarvardX Professional Certificate in Data Science
    9. Udacity
    10. Machine Learning Engineer Nanodegree
    11. Deep Learning Nanodegree
    12. TensorFlow
    13. PyTorch
    14. Kaggle
    15. Kaggle Learn
    16. fast.ai
    17. fastai library
    18. "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
    19. Scikit-Learn
    20. Keras
    21. "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
    22. PyTorch Documentation & Tutorials
    23. PyTorch Lightning
    24. TensorFlow Documentation & Tutorials
    25. TensorFlow Lite

    AI recommended 25 alternatives but never named louisfb01/start-machine-learning. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 louisfb01/start-machine-learning?
    pass
    AI did not name louisfb01/start-machine-learning — 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 louisfb01/start-machine-learning in production, what risks or prerequisites should they evaluate first?
    pass
    AI named louisfb01/start-machine-learning 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 louisfb01/start-machine-learning solve, and who is the primary audience?
    pass
    AI did not name louisfb01/start-machine-learning — 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 louisfb01/start-machine-learning. 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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louisfb01/start-machine-learning — 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