RRepoGEO

REPOGEO REPORT · LITE

kuleshov/cornell-cs5785-2025-applied-ml

Default branch main · commit 80f7203a · scanned 6/15/2026, 12:47:58 PM

GitHub: 534 stars · 186 forks

AI VISIBILITY SCORE
17 /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
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 kuleshov/cornell-cs5785-2025-applied-ml, 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
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    machine-learning, applied-ml, course-materials, lecture-notes, cornell-university, cs5785, education, fall-2025
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with an appropriate open-source license (e.g., MIT, Apache-2.0) or add a clear statement about the intended license(s) directly in the README.md if a standard license is not applicable.
  • mediumhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    Add the official course page URL (e.g., `https://www.cs.cornell.edu/courses/cs5785/`) 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 kuleshov/cornell-cs5785-2025-applied-ml
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
scikit-learn/scikit-learn
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. scikit-learn/scikit-learn · recommended 2×
  2. keras-team/keras · recommended 2×
  3. tensorflow/tensorflow · recommended 2×
  4. Coursera · recommended 1×
  5. fast.ai · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive materials to learn applied machine learning concepts?
    you: not recommended
    AI recommended (in order):
    1. Coursera
    2. fast.ai
    3. Udemy
    4. Kaggle Learn
    5. Google's Machine Learning Crash Course
    6. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
    7. Scikit-Learn (scikit-learn/scikit-learn)
    8. Keras (keras-team/keras)
    9. TensorFlow (tensorflow/tensorflow)
    10. edX
    11. Microsoft Professional Program in Data Science
    12. MITx: Introduction to Computational Thinking and Data Science

    AI recommended 12 alternatives but never named kuleshov/cornell-cs5785-2025-applied-ml. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good resources for practical machine learning course notes and examples?
    you: not recommended
    AI recommended (in order):
    1. fastai (fastai/fastai)
    2. PyTorch (pytorch/pytorch)
    3. Octave
    4. MATLAB
    5. TensorFlow (tensorflow/tensorflow)
    6. scikit-learn (scikit-learn/scikit-learn)
    7. Keras (keras-team/keras)
    8. Kaggle
    9. Python (python/cpython)
    10. Pandas (pandas-dev/pandas)

    AI recommended 10 alternatives but never named kuleshov/cornell-cs5785-2025-applied-ml. 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 kuleshov/cornell-cs5785-2025-applied-ml?
    pass
    AI did not name kuleshov/cornell-cs5785-2025-applied-ml — 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 kuleshov/cornell-cs5785-2025-applied-ml in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kuleshov/cornell-cs5785-2025-applied-ml 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 kuleshov/cornell-cs5785-2025-applied-ml solve, and who is the primary audience?
    pass
    AI did not name kuleshov/cornell-cs5785-2025-applied-ml — 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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite