RRepoGEO

REPOGEO REPORT · LITE

ritchieng/deep-learning-wizard

Default branch master · commit e4ce284a · scanned 6/5/2026, 10:37:04 PM

GitHub: 872 stars · 236 forks

AI VISIBILITY SCORE
40 /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
3 / 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 ritchieng/deep-learning-wizard, 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 H1 and opening to highlight practical PyTorch deep learning tutorials

    Why:

    CURRENT
    # Deep Learning Materials by Deep Learning Wizard
    
    ## Start Learning Now
    
    Please head to www.deeplearningwizard.com to start learning! It is mobile/tablet friendly and open-source.
    COPY-PASTE FIX
    # Deep Learning Wizard: Practical PyTorch Tutorials & Guides (From Basics to Production)
    
    This repository contains the complete collection of open-source notebooks and markdown files that power the Deep Learning Wizard website. It offers comprehensive, code-centric tutorials for mastering deep learning and deep reinforcement learning with PyTorch, Python, and Apptainer, covering concepts from foundational models to production deployment.
  • mediumtopics#2
    Add more specific deep learning and learning-related topics

    Why:

    CURRENT
    apptainer, deep-learning, llamaindex, ollama, python3, pytorch
    COPY-PASTE FIX
    apptainer, deep-learning, deep-reinforcement-learning, machine-learning, llamaindex, ollama, python3, pytorch
  • mediumreadme#3
    Add a 'Core Differentiator' section to the README

    Why:

    COPY-PASTE FIX
    ## Core Differentiator
    
    Deep Learning Wizard stands out through its highly curated and structured aggregation of deep learning resources. We combine comprehensive, explanatory Jupyter notebooks and code examples with a clear course progression, making complex topics accessible for both beginners and intermediate learners.

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 ritchieng/deep-learning-wizard
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Documentation & Tutorials
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Documentation & Tutorials · recommended 1×
  2. pytorch/examples · recommended 1×
  3. Fast.ai's 'Practical Deep Learning for Coders' · recommended 1×
  4. Deep Learning with PyTorch: A 60 Minute Blitz · recommended 1×
  5. pyg-team/pytorch_geometric · recommended 1×
  • CATEGORY QUERY
    Where can I find practical deep learning tutorials using PyTorch for various models?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Documentation & Tutorials
    2. PyTorch Examples (pytorch/examples)
    3. Fast.ai's 'Practical Deep Learning for Coders'
    4. Deep Learning with PyTorch: A 60 Minute Blitz
    5. PyTorch Geometric (PyG) (pyg-team/pytorch_geometric)
    6. Hugging Face Transformers (huggingface/transformers)
    7. PyTorch Lightning (Lightning-AI/lightning)

    AI recommended 7 alternatives but never named ritchieng/deep-learning-wizard. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good open-source guides for mastering deep learning from basics to production deployment?
    you: not recommended
    AI recommended (in order):
    1. fastai (fastai/fastai)
    2. PyTorch (pytorch/pytorch)
    3. TensorFlow (tensorflow/tensorflow)
    4. Keras (keras-team/keras)
    5. TensorFlow Extended (TFX) (tensorflow/tfx)
    6. TorchScript
    7. ONNX (onnx/onnx)

    AI recommended 7 alternatives but never named ritchieng/deep-learning-wizard. 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 ritchieng/deep-learning-wizard?
    pass
    AI named ritchieng/deep-learning-wizard explicitly

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

  • If a team adopts ritchieng/deep-learning-wizard in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ritchieng/deep-learning-wizard 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 ritchieng/deep-learning-wizard solve, and who is the primary audience?
    pass
    AI named ritchieng/deep-learning-wizard explicitly

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

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ritchieng/deep-learning-wizard — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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