RRepoGEO

REPOGEO REPORT · LITE

leehanchung/awesome-full-stack-machine-learning-courses

Default branch master · commit 521c80df · scanned 6/12/2026, 6:32:54 PM

GitHub: 526 stars · 109 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 leehanchung/awesome-full-stack-machine-learning-courses, 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 README's opening to emphasize 'awesome list' nature

    Why:

    CURRENT
    This is a curated list of publicly accessible machine learning courses from top universities such as Berkeley, Harvard, Stanford, and MIT. It also includes machine learning project case studies from large and experienced companies.
    COPY-PASTE FIX
    This awesome list curates publicly accessible machine learning engineering courses from top universities like Berkeley, Harvard, Stanford, and MIT, along with machine learning project case studies from experienced companies.
  • highhomepage#2
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/leehanchung/awesome-full-stack-machine-learning-courses
  • mediumtopics#3
    Add 'awesome-list' and 'mlops' to topics

    Why:

    CURRENT
    berkeley, berkeley-ai, berkeley-reinforcement-learning, caltech, columbia-university, computer-science, deep-learning, deep-neural-networks, edx-columbiax, machine-learning, reinforcement-learning, stanford, udemy
    COPY-PASTE FIX
    awesome-list, mlops, berkeley, berkeley-ai, berkeley-reinforcement-learning, caltech, columbia-university, computer-science, deep-learning, deep-neural-networks, edx-columbiax, machine-learning, reinforcement-learning, stanford, udemy

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 leehanchung/awesome-full-stack-machine-learning-courses
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Python
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Python · recommended 2×
  2. Coursera · recommended 1×
  3. Google · recommended 1×
  4. TensorFlow · recommended 1×
  5. MIT OpenCourseWare · recommended 1×
  • CATEGORY QUERY
    Where can I find free online machine learning engineering courses from top universities?
    you: not recommended
    AI recommended (in order):
    1. Coursera
    2. Google
    3. TensorFlow
    4. Python
    5. MIT OpenCourseWare
    6. fast.ai
    7. PyTorch
    8. Stanford's website
    9. YouTube

    AI recommended 9 alternatives but never named leehanchung/awesome-full-stack-machine-learning-courses. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for comprehensive full-stack machine learning course recommendations to build practical skills.
    you: not recommended
    AI recommended (in order):
    1. Python
    2. Flask
    3. Docker
    4. Google Cloud
    5. Vertex AI
    6. BigQuery ML
    7. Amazon Web Services (AWS)
    8. Amazon SageMaker
    9. Lambda
    10. EC2

    AI recommended 10 alternatives but never named leehanchung/awesome-full-stack-machine-learning-courses. 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 leehanchung/awesome-full-stack-machine-learning-courses?
    pass
    AI did not name leehanchung/awesome-full-stack-machine-learning-courses — 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 leehanchung/awesome-full-stack-machine-learning-courses in production, what risks or prerequisites should they evaluate first?
    pass
    AI named leehanchung/awesome-full-stack-machine-learning-courses 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 leehanchung/awesome-full-stack-machine-learning-courses solve, and who is the primary audience?
    pass
    AI did not name leehanchung/awesome-full-stack-machine-learning-courses — 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 leehanchung/awesome-full-stack-machine-learning-courses. 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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