REPOGEO REPORT · LITE
dvgodoy/PyTorchStepByStep
Default branch master · commit d837dec7 · scanned 5/15/2026, 1:28:36 AM
GitHub: 1,450 stars · 502 forks
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.
- highreadme#1Reposition 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#2Add more specific educational and book-related topics
Why:
CURRENTcnn-pytorch, deep-learning, python, pytorch, pytorch-tutorial, rnn-pytorch
COPY-PASTE FIXcnn-pytorch, deep-learning, python, pytorch, pytorch-tutorial, rnn-pytorch, deep-learning-book, pytorch-book, jupyter-notebooks, educational-resource, beginner-friendly
- lowreadme#3Add 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.
- pytorch/examples · recommended 2×
- PyTorch Documentation · recommended 1×
- Deep Learning with PyTorch · recommended 1×
- fast.ai Practical Deep Learning for Coders Course · recommended 1×
- PyTorch Geometric · recommended 1×
- CATEGORY QUERYHow can I learn deep learning concepts with practical PyTorch code examples?you: not recommendedAI recommended (in order):
- PyTorch Documentation
- Deep Learning with PyTorch
- fast.ai Practical Deep Learning for Coders Course
- PyTorch Examples (pytorch/examples)
- PyTorch Geometric
- PyTorch Lightning
- Hugging Face Transformers
AI recommended 7 alternatives but never named dvgodoy/PyTorchStepByStep. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhere can I find guided tutorials for implementing CNNs and RNNs using PyTorch?you: not recommendedAI recommended (in order):
- PyTorch Official Tutorials
- Fast.ai
- DeepLearning.AI
- PyTorch Examples GitHub Repository (pytorch/examples)
- Analytics Vidhya
- Towards Data Science
- 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 completenesspass
- README presencepass
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?passAI 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?passAI 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?passAI 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?
Embed your GEO score
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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