RRepoGEO

REPOGEO REPORT · LITE

dvgodoy/PyTorchStepByStep

Default branch master · commit d837dec7 · scanned 5/15/2026, 1:28:36 AM

GitHub: 1,450 stars · 502 forks

AI VISIBILITY SCORE
27 /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
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 dvgodoy/PyTorchStepByStep, 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's primary purpose statement

    Why:

    CURRENT
    # Deep Learning with PyTorch Step-by-Step

## New book: "A Hands-On Guide to Fine-Tuning LLMs"

<p align="center">
  
  <br>
  <strong><a href="https://www.amazon.com/dp/B0DV3Y1GMP">Kindle</a> | <a href="https://www.amazon.com/dp/B0DV4H7YW2">Paperback</a> | <a href="https://leanpub.com/finetuning">PDF [Leanpub]<a> | <a href="https://danielgodoy.gumroad.com/l/finetuning">PDF [Gumroad]<a></strong>
</p>

## Revised for PyTorch 2.x!
The revised version addresses changes in PyTorch, Torchvision, HuggingFace, and other libraries. The chapters most affected were Chapter 4 (in Volume II) and Chapter 11 (in Volume III).

Please check the PDFs below containing the changes (check the paragraphs highlighted in red):
- Changes to Volume I
- Changes to Volume II
- Changes to Volume III

[](https://pytorchstepbystep.com)

This is the official repository of my book "**Deep Learning with PyTorch Step-by-Step**". Here you will find **one Jupyter notebook** for every **chapter** in the book.
    COPY-PASTE FIX
    # Deep Learning with PyTorch Step-by-Step

This is the official repository for the book "**Deep Learning with PyTorch Step-by-Step: A Beginner's Guide**". It provides **one Jupyter notebook** for every **chapter** in the book, containing **all the code shown** to help you **reproduce the results** and learn PyTorch effectively.

## Revised for PyTorch 2.x!
The revised version addresses changes in PyTorch, Torchvision, HuggingFace, and other libraries. The chapters most affected were Chapter 4 (in Volume II) and Chapter 11 (in Volume III).

Please check the PDFs below containing the changes (check the paragraphs highlighted in red):
- Changes to Volume I
- Changes to Volume II
- Changes to Volume III

## New book: "A Hands-On Guide to Fine-Tuning LLMs"
<p align="center">
  <br>
  <strong><a href="https://www.amazon.com/dp/B0DV3Y1GMP">Kindle</a> | <a href="https://www.amazon.com/dp/B0DV4H7YW2">Paperback</a> | <a href="https://leanpub.com/finetuning">PDF [Leanpub]<a> | <a href="https://danielgodoy.gumroad.com/l/finetuning">PDF [Gumroad]<a></strong>
</p>
  • mediumtopics#2
    Add more specific educational and book-related topics

    Why:

    CURRENT
    cnn-pytorch, deep-learning, python, pytorch, pytorch-tutorial, rnn-pytorch
    COPY-PASTE FIX
    cnn-pytorch, deep-learning, python, pytorch, pytorch-tutorial, rnn-pytorch, deep-learning-book, pytorch-book, jupyter-notebooks, educational-resource, beginner-friendly
  • lowreadme#3
    Add a dedicated section clarifying the target audience and pedagogical approach

    Why:

    COPY-PASTE FIX
    ## Who is this repository for?
This repository is ideal for beginners in deep learning and PyTorch who want a structured, hands-on learning experience. Each chapter's notebook is designed to be followed step-by-step, allowing you to build foundational knowledge and confidence by running and understanding every line of code.

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 dvgodoy/PyTorchStepByStep
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pytorch/examples
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. pytorch/examples · recommended 2×
  2. PyTorch Documentation · recommended 1×
  3. Deep Learning with PyTorch · recommended 1×
  4. fast.ai Practical Deep Learning for Coders Course · recommended 1×
  5. PyTorch Geometric · recommended 1×
  • CATEGORY QUERY
    How can I learn deep learning concepts with practical PyTorch code examples?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Documentation
    2. Deep Learning with PyTorch
    3. fast.ai Practical Deep Learning for Coders Course
    4. PyTorch Examples (pytorch/examples)
    5. PyTorch Geometric
    6. PyTorch Lightning
    7. Hugging Face Transformers

    AI recommended 7 alternatives but never named dvgodoy/PyTorchStepByStep. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find guided tutorials for implementing CNNs and RNNs using PyTorch?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Official Tutorials
    2. Fast.ai
    3. DeepLearning.AI
    4. PyTorch Examples GitHub Repository (pytorch/examples)
    5. Analytics Vidhya
    6. Towards Data Science
    7. Yannic Kilcher

    AI recommended 7 alternatives but never named dvgodoy/PyTorchStepByStep. 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 dvgodoy/PyTorchStepByStep?
    pass
    AI did not name dvgodoy/PyTorchStepByStep — 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 dvgodoy/PyTorchStepByStep in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dvgodoy/PyTorchStepByStep 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 dvgodoy/PyTorchStepByStep solve, and who is the primary audience?
    pass
    AI did not name dvgodoy/PyTorchStepByStep — 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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dvgodoy/PyTorchStepByStep — 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