RRepoGEO

REPOGEO REPORT · LITE

dair-ai/ML-Course-Notes

Default branch main · commit 15fd0a13 · scanned 6/20/2026, 2:57:39 PM

GitHub: 6,597 stars · 888 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 dair-ai/ML-Course-Notes, 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
    Strengthen README opening to highlight Andrew Ng course alignment

    Why:

    CURRENT
    A place to collaborate and share lecture notes on all topics related to machine learning, NLP, and AI.
    COPY-PASTE FIX
    A collaborative repository for comprehensive lecture notes and curated summaries, primarily focused on Andrew Ng's highly popular and foundational Machine Learning courses (e.g., Coursera's Machine Learning Specialization, Stanford CS229), covering topics in machine learning, NLP, and AI.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://dair-ai.notion.site/
  • lowreadme#3
    Clarify the repository's license in the README

    Why:

    COPY-PASTE FIX
    This repository's content is licensed under [Specify License(s) here, e.g., CC BY-NC 4.0 for educational content]. Please refer to the LICENSE file for full details.

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 dair-ai/ML-Course-Notes
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google's Machine Learning Crash Course
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google's Machine Learning Crash Course · recommended 2×
  2. Coursera - Machine Learning by Andrew Ng (Stanford University) · recommended 1×
  3. fast.ai - Practical Deep Learning for Coders · recommended 1×
  4. Stanford University CS229: Machine Learning (Autumn Quarter) · recommended 1×
  5. scikit-learn/scikit-learn · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive lecture notes and resources for learning machine learning concepts?
    you: not recommended
    AI recommended (in order):
    1. Coursera - Machine Learning by Andrew Ng (Stanford University)
    2. fast.ai - Practical Deep Learning for Coders
    3. Stanford University CS229: Machine Learning (Autumn Quarter)
    4. scikit-learn Documentation (scikit-learn/scikit-learn)
    5. Google's Machine Learning Crash Course
    6. MIT OpenCourseWare - 6.036 Introduction to Machine Learning
    7. An Introduction to Statistical Learning with Applications in R

    AI recommended 7 alternatives but never named dair-ai/ML-Course-Notes. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for curated study materials or course summaries for deep learning and NLP topics.
    you: not recommended
    AI recommended (in order):
    1. fast.ai's Practical Deep Learning for Coders (v5)
    2. fast.ai's Practical Deep Learning for Coders (v3) with NLP
    3. Stanford CS224N: Natural Language Processing with Deep Learning
    4. Coursera's Deep Learning Specialization by Andrew Ng (deeplearning.ai)
    5. Hugging Face 🤗 Transformers Documentation & Course
    6. Google's Machine Learning Crash Course
    7. MIT 6.S191: Introduction to Deep Learning
    8. "Speech and Language Processing" by Jurafsky and Martin

    AI recommended 8 alternatives but never named dair-ai/ML-Course-Notes. 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 dair-ai/ML-Course-Notes?
    pass
    AI did not name dair-ai/ML-Course-Notes — 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 dair-ai/ML-Course-Notes in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dair-ai/ML-Course-Notes 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 dair-ai/ML-Course-Notes solve, and who is the primary audience?
    pass
    AI did not name dair-ai/ML-Course-Notes — 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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dair-ai/ML-Course-Notes — 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