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REPOGEO REPORT · LITE

davidADSP/Generative_Deep_Learning_2nd_Edition

Default branch main · commit 9b1048db · scanned 5/11/2026, 1:07:48 PM

GitHub: 1,493 stars · 580 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 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 davidADSP/Generative_Deep_Learning_2nd_Edition, 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 README opening to emphasize learning and implementation

    Why:

    CURRENT
    The official code repository for the second edition of the O'Reilly book *Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play*.
    COPY-PASTE FIX
    This is the official code repository for the second edition of the O'Reilly book *Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play*. It provides hands-on Python code and Jupyter notebooks to help you learn and implement various generative deep learning models covered in the book.
  • hightopics#2
    Add specific educational and learning-oriented topics

    Why:

    CURRENT
    chatgpt, dalle2, data-science, deep-learning, diffusion-models, generative-adversarial-network, gpt-3, machine-learning, python, stable-diffusion, tensorflow
    COPY-PASTE FIX
    chatgpt, dalle2, data-science, deep-learning, diffusion-models, generative-adversarial-network, gpt-3, machine-learning, python, stable-diffusion, tensorflow, generative-ai-tutorial, deep-learning-course, educational-resource, book-companion, hands-on-learning
  • mediumreadme#3
    Add a 'Who is this for?' section to clarify target audience

    Why:

    COPY-PASTE FIX
    ## Who is this for?

This repository is designed for students, researchers, and practitioners who want to gain practical experience implementing generative deep learning models. It serves as a hands-on companion to the "Generative Deep Learning, 2nd Edition" book.

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 davidADSP/Generative_Deep_Learning_2nd_Edition
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
tensorflow/tensorflow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. tensorflow/tensorflow · recommended 2×
  2. keras-team/keras · recommended 2×
  3. pytorch/pytorch · recommended 2×
  4. huggingface/transformers · recommended 2×
  5. fastai/fastai · recommended 2×
  • CATEGORY QUERY
    How can I learn to implement different generative deep learning models using Python?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow (tensorflow/tensorflow)
    2. Keras (keras-team/keras)
    3. PyTorch (pytorch/pytorch)
    4. Hugging Face Transformers (huggingface/transformers)
    5. GPT-2 (openai/gpt-2)
    6. GPT-3
    7. T5
    8. BART
    9. DeepLearning.AI Generative Adversarial Networks (GANs) Specialization
    10. Coursera
    11. fast.ai's Practical Deep Learning for Coders
    12. fastai (fastai/fastai)
    13. OpenAI Gym (openai/gym)
    14. Stable Diffusion (stability-ai/stable-diffusion)
    15. Diffusers Library (huggingface/diffusers)
    16. DALL-E 2

    AI recommended 16 alternatives but never named davidADSP/Generative_Deep_Learning_2nd_Edition. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources for understanding and building advanced generative AI applications?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library (huggingface/transformers)
    2. PyTorch (pytorch/pytorch)
    3. TensorFlow (tensorflow/tensorflow)
    4. OpenAI API
    5. LangChain (langchain-ai/langchain)
    6. LlamaIndex (run-llama/llama_index)
    7. Keras (keras-team/keras)
    8. Fast.ai Library (fastai/fastai)
    9. DeepLearning.AI Specializations

    AI recommended 9 alternatives but never named davidADSP/Generative_Deep_Learning_2nd_Edition. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 davidADSP/Generative_Deep_Learning_2nd_Edition?
    pass
    AI named davidADSP/Generative_Deep_Learning_2nd_Edition explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts davidADSP/Generative_Deep_Learning_2nd_Edition in production, what risks or prerequisites should they evaluate first?
    pass
    AI named davidADSP/Generative_Deep_Learning_2nd_Edition 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 davidADSP/Generative_Deep_Learning_2nd_Edition solve, and who is the primary audience?
    pass
    AI did not name davidADSP/Generative_Deep_Learning_2nd_Edition — 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 davidADSP/Generative_Deep_Learning_2nd_Edition. 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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