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REPOGEO REPORT · LITE

davidADSP/Generative_Deep_Learning_2nd_Edition

Default branch main · commit 9b1048db · scanned 6/21/2026, 5:52:52 PM

GitHub: 1,517 stars · 583 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
20 /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
0 / 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 introduction to emphasize pedagogical purpose and intended use

    Why:

    CURRENT
    # 🦜 Generative Deep Learning - 2nd Edition Codebase

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
    # 🦜 Generative Deep Learning - 2nd Edition Codebase

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 comprehensive, hands-on code examples for every chapter, designed as a structured learning resource to help you master advanced generative AI techniques. Please note: This repository is intended for educational purposes and experimentation, not as a production-ready library or framework.
  • mediumtopics#2
    Add 'book-companion' topic

    Why:

    CURRENT
    chatgpt, dalle2, data-science, deep-learning, diffusion-models, generative-adversarial-network, gpt-3, machine-learning, python, stable-diffusion, tensorflow
    COPY-PASTE FIX
    book-companion, chatgpt, dalle2, data-science, deep-learning, diffusion-models, generative-adversarial-network, gpt-3, machine-learning, python, stable-diffusion, tensorflow
  • mediumreadme#3
    Add a 'What You'll Learn' section to summarize learning outcomes

    Why:

    COPY-PASTE FIX
    ### What You'll Learn
This repository provides practical implementations for understanding and building a wide range of generative models, including Variational Autoencoders, Generative Adversarial Networks, Autoregressive Models, Normalizing Flows, Energy-Based Models, Diffusion Models, and Transformers. You'll gain hands-on experience with techniques applicable to tasks like image generation, text synthesis, and music composition.

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
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. Hugging Face Diffusers · recommended 1×
  3. Hugging Face Courses · recommended 1×
  4. PyTorch Lightning · recommended 1×
  5. Keras · recommended 1×
  • CATEGORY QUERY
    How can I learn to build generative AI models for creative text and image tasks?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Hugging Face Diffusers
    3. Hugging Face Courses
    4. PyTorch Lightning
    5. Keras
    6. fast.ai
    7. RunwayML
    8. TensorFlow

    AI recommended 8 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 Python resources for understanding and implementing advanced deep generative techniques?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Examples (pytorch/examples)
    2. Hugging Face Diffusers (huggingface/diffusers)
    3. Keras Examples (keras-team/keras-io)
    4. TF-GAN (tensorflow/gan)
    5. OpenAI Jukebox
    6. DALL-E
    7. Haiku (deepmind/dm-haiku)
    8. JAX (google/jax)

    AI recommended 8 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 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?

  • If a team adopts davidADSP/Generative_Deep_Learning_2nd_Edition in production, what risks or prerequisites should they evaluate first?
    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?

  • 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?

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davidADSP/Generative_Deep_Learning_2nd_Edition — 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