RRepoGEO

REPOGEO REPORT · LITE

harleyszhang/cv_note

Default branch master · commit 80820e4c · scanned 5/16/2026, 3:13:10 PM

GitHub: 2,627 stars · 390 forks

AI VISIBILITY SCORE
35 /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
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 harleyszhang/cv_note, 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 to clarify repo type

    Why:

    CURRENT
    <h1 align="center">
    CV 算法工程师成长之路
    </h1>
    COPY-PASTE FIX
    <h1 align="center">
    CV 算法工程师成长之路
    </h1>
    
    这是一个GitHub仓库,旨在记录计算机视觉算法工程师的成长之路,分享计算机视觉、模型压缩部署技术栈笔记,并提供大模型推理框架课程和面试准备资料。
  • mediumhomepage#2
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://harleyszhang.github.io/cv_note/
  • lowtopics#3
    Add specific topics related to large model inference and GPU acceleration

    Why:

    CURRENT
    computer-vision, cpp11, deep-learning, interview-questions, machine-learning-algorithms, python3
    COPY-PASTE FIX
    computer-vision, cpp11, deep-learning, interview-questions, machine-learning-algorithms, python3, large-language-models, llm-inference, gpu-acceleration, triton, flash-attention

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 harleyszhang/cv_note
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville · recommended 1×
  2. Computer Vision: Algorithms and Applications" by Richard Szeliski · recommended 1×
  3. fastai/fastai · recommended 1×
  4. Deep Learning Specialization" by Andrew Ng (Coursera) · recommended 1×
  5. Cracking the Coding Interview" by Gayle Laakmann McDowell · recommended 1×
  • CATEGORY QUERY
    Seeking comprehensive resources for computer vision algorithm engineer career development and interview prep.
    you: not recommended
    AI recommended (in order):
    1. Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
    2. Computer Vision: Algorithms and Applications" by Richard Szeliski
    3. Practical Deep Learning for Coders" by fast.ai (fastai/fastai)
    4. Deep Learning Specialization" by Andrew Ng (Coursera)
    5. Cracking the Coding Interview" by Gayle Laakmann McDowell
    6. LeetCode
    7. Kaggle

    AI recommended 7 alternatives but never named harleyszhang/cv_note. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to achieve high-performance, GPU-accelerated inference for large deep learning models?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO Toolkit
    3. ONNX Runtime
    4. PyTorch
    5. TorchScript
    6. CUDA
    7. TensorFlow
    8. TensorFlow Lite
    9. TensorFlow Serving
    10. DeepSpeed
    11. Triton Inference Server

    AI recommended 11 alternatives but never named harleyszhang/cv_note. 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 harleyszhang/cv_note?
    pass
    AI named harleyszhang/cv_note explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of harleyszhang/cv_note. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/harleyszhang/cv_note.svg)](https://repogeo.com/en/r/harleyszhang/cv_note)
HTML
<a href="https://repogeo.com/en/r/harleyszhang/cv_note"><img src="https://repogeo.com/badge/harleyszhang/cv_note.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

harleyszhang/cv_note — 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