REPOGEO REPORT · LITE

mbadry1/CS231n-2017-Summary

Default branch master · commit 89042d34 · scanned 5/11/2026, 4:32:39 PM

GitHub: 1,576 stars · 456 forks

AI VISIBILITY SCORE

15 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 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 mbadry1/CS231n-2017-Summary, 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 the README's opening paragraph to clarify its purpose

Why:

CURRENT

After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to me.

COPY-PASTE FIX

This repository contains my personal, concise summary notes from the entire Stanford CS231n 2017 course on Convolutional Neural Networks for Visual Recognition. It's designed as a quick reference for students and self-learners who want a distilled overview of the key concepts, distinct from the full course lectures.

mediumtopics#2

Add more specific topics to improve categorization

Why:

CURRENT

cs231n, deep-learning, neural-network, notes

COPY-PASTE FIX

cs231n, deep-learning, neural-networks, computer-vision, image-recognition, course-notes, study-guide, stanford-university

lowhomepage#3
Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
http://cs231n.stanford.edu/2017/
```

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 mbadry1/CS231n-2017-Summary

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Stanford CS231n: Convolutional Neural Networks for Visual Recognition

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Stanford CS231n: Convolutional Neural Networks for Visual Recognition · recommended 1×
Deep Learning Book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville · recommended 1×
fast.ai Practical Deep Learning for Coders · recommended 1×
Machine Learning Yearning by Andrew Ng · recommended 1×
Coursera Deep Learning Specialization by Andrew Ng · recommended 1×

CATEGORY QUERY
I need a concise overview of deep learning concepts for computer vision beginners.
you: not recommended
Show full AI answer
CATEGORY QUERY
Where can I find structured notes explaining neural networks and their training for image recognition?
you: not recommended
AI recommended (in order):
1. Stanford CS231n: Convolutional Neural Networks for Visual Recognition
2. Deep Learning Book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
3. fast.ai Practical Deep Learning for Coders
4. Machine Learning Yearning by Andrew Ng
5. Coursera Deep Learning Specialization by Andrew Ng
6. Towards Data Science
7. Google's Machine Learning Crash Course
AI recommended 7 alternatives but never named mbadry1/CS231n-2017-Summary. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
warn
Suggestion:
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 mbadry1/CS231n-2017-Summary?
pass
AI did not name mbadry1/CS231n-2017-Summary — 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 mbadry1/CS231n-2017-Summary in production, what risks or prerequisites should they evaluate first?
pass
AI did not name mbadry1/CS231n-2017-Summary — 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 mbadry1/CS231n-2017-Summary solve, and who is the primary audience?
pass
AI did not name mbadry1/CS231n-2017-Summary — 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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Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite