RRepoGEO

REPOGEO REPORT · LITE

zslucky/awesome-AI-books

Default branch master · commit 5852f6a2 · scanned 5/12/2026, 4:37:38 AM

GitHub: 1,712 stars · 392 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 zslucky/awesome-AI-books, 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 the README's opening sentence to emphasize it's a curated collection

    Why:

    CURRENT
    Some awesome AI related books and pdfs for downloading and learning.
    COPY-PASTE FIX
    A curated collection of awesome AI-related books and PDFs for learning and self-study, organized by topic.
  • highabout#2
    Clarify the repository description to remove ambiguity

    Why:

    CURRENT
    Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning
    COPY-PASTE FIX
    A curated collection of awesome AI-related books and PDFs for learning and self-study, with resources for various AI topics including machine learning, deep learning, and quantum computing.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/zslucky/awesome-AI-books

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 zslucky/awesome-AI-books
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google's Machine Learning Crash Course · recommended 1×
  2. Deep Learning Book · recommended 1×
  3. An Introduction to Statistical Learning with Applications in R · recommended 1×
  4. The Elements of Statistical Learning · recommended 1×
  5. fast.ai's Practical Deep Learning for Coders · recommended 1×
  • CATEGORY QUERY
    Where can I find free AI, machine learning, and deep learning books for self-study?
    you: not recommended
    AI recommended (in order):
    1. Google's Machine Learning Crash Course
    2. Deep Learning Book
    3. An Introduction to Statistical Learning with Applications in R
    4. The Elements of Statistical Learning
    5. fast.ai's Practical Deep Learning for Coders
    6. fast.ai's Practical Machine Learning for Coders
    7. Stanford CS229 Lecture Notes
    8. Dive into Deep Learning
    9. Mathematics for Machine Learning

    AI recommended 9 alternatives but never named zslucky/awesome-AI-books. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources for learning quantum computing and artificial intelligence concepts?
    you: not recommended
    AI recommended (in order):
    1. IBM Quantum Experience
    2. Qiskit Textbook
    3. Qiskit
    4. Microsoft Quantum Development Kit (QDK)
    5. Q# Documentation
    6. Q#
    7. Quantum Computing for Everyone" by Chris Bernhardt
    8. Quantum Computing: A Very Short Introduction" by Scott Aaronson
    9. Quantum Computation and Quantum Information" by Michael A. Nielsen and Isaac L. Chuang
    10. MIT OpenCourseWare - 8.04 Quantum Physics I, II, III
    11. Quantum Algorithms" by Ronald de Wolf
    12. Google AI Education
    13. Machine Learning Crash Course
    14. Coursera
    15. AI for Everyone" by Andrew Ng
    16. DeepLearning.AI
    17. edX
    18. Introduction to Artificial Intelligence (CS50's AI)" by Harvard University
    19. Machine Learning" by Andrew Ng
    20. Octave
    21. MATLAB
    22. DeepLearning.AI Specializations
    23. Deep Learning Specialization
    24. TensorFlow
    25. Natural Language Processing Specialization
    26. TensorFlow in Practice Specialization
    27. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
    28. Scikit-Learn
    29. Keras
    30. Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
    31. fast.ai
    32. Practical Deep Learning for Coders
    33. PyTorch

    AI recommended 33 alternatives but never named zslucky/awesome-AI-books. 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 zslucky/awesome-AI-books?
    pass
    AI did not name zslucky/awesome-AI-books — 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 zslucky/awesome-AI-books in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zslucky/awesome-AI-books 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 zslucky/awesome-AI-books solve, and who is the primary audience?
    pass
    AI did not name zslucky/awesome-AI-books — 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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