RRepoGEO

REPOGEO REPORT · LITE

llSourcell/LearnML

Default branch main · commit a1087ffa · scanned 6/14/2026, 12:43:21 AM

GitHub: 954 stars · 182 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 llSourcell/LearnML, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the MIT License (or another appropriate open-source license).
  • mediumreadme#2
    Refine README overview to emphasize its role as a video series companion

    Why:

    CURRENT
    This is the Curriculum for Learn Machine Learning in 3 months (PyTorch Curriculum) by Siraj Raval on Youtube.
    COPY-PASTE FIX
    This is the **official companion repository and study guide** for the 'Learn Machine Learning in 3 Months (PyTorch Curriculum)' video series by Siraj Raval on Youtube.

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 llSourcell/LearnML
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
fast.ai's Practical Deep Learning for Coders (v5)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. fast.ai's Practical Deep Learning for Coders (v5) · recommended 1×
  2. PyTorch Official Tutorials · recommended 1×
  3. DeepLearning.AI's PyTorch Deep Learning Specialization · recommended 1×
  4. freeCodeCamp's PyTorch Courses · recommended 1×
  5. PyTorch Fundamentals by Daniel Bourke · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive machine learning curriculum for Python beginners using PyTorch?
    you: not recommended
    AI recommended (in order):
    1. fast.ai's Practical Deep Learning for Coders (v5)
    2. PyTorch Official Tutorials
    3. DeepLearning.AI's PyTorch Deep Learning Specialization
    4. freeCodeCamp's PyTorch Courses
    5. PyTorch Fundamentals by Daniel Bourke
    6. Deep Learning with PyTorch (Manning Publications)

    AI recommended 6 alternatives but never named llSourcell/LearnML. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for project-based deep learning resources covering computer vision and NLP applications.
    you: not recommended
    AI recommended (in order):
    1. fast.ai Practical Deep Learning for Coders (v5) (fastai/fastai)
    2. DeepLearning.AI TensorFlow in Practice Specialization
    3. Hugging Face 🫂 Transformers Tutorials & Examples (huggingface/transformers)
    4. Kaggle Learn Courses
    5. PyTorch Examples & Tutorials (pytorch/pytorch)
    6. Applied Deep Learning with Keras
    7. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (ageron/handson-ml3)

    AI recommended 7 alternatives but never named llSourcell/LearnML. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 llSourcell/LearnML?
    pass
    AI did not name llSourcell/LearnML — 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 llSourcell/LearnML in production, what risks or prerequisites should they evaluate first?
    pass
    AI named llSourcell/LearnML 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 llSourcell/LearnML solve, and who is the primary audience?
    pass
    AI named llSourcell/LearnML explicitly

    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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MARKDOWN (README)
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llSourcell/LearnML — 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