RRepoGEO

REPOGEO REPORT · LITE

lcylmhlcy/Awesome-algorithm-interview

Default branch master · commit fa69e636 · scanned 5/16/2026, 12:27:57 AM

GitHub: 3,013 stars · 455 forks

AI VISIBILITY SCORE
10 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 lcylmhlcy/Awesome-algorithm-interview, 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
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    algorithm-interview, computer-vision, machine-learning, deep-learning, interview-preparation, awesome-list, chinese-resources, job-interview, career-development
  • highreadme#2
    Clarify the README's opening description in English

    Why:

    CURRENT
    > 算法工程师(人工智能cv方向)面试问题及相关资料的网站收集
    COPY-PASTE FIX
    > This is an awesome list of curated resources and interview questions for Algorithm Engineers specializing in Artificial Intelligence and Computer Vision (CV). It collects interview questions and related materials for algorithm engineers (AI CV direction).
  • highlicense#3
    Add a LICENSE file to clarify usage rights

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root to specify the terms of use for this collection of resources.

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 lcylmhlcy/Awesome-algorithm-interview
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LeetCode
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LeetCode · recommended 2×
  2. Computer Vision: Algorithms and Applications · recommended 1×
  3. Deep Learning · recommended 1×
  4. OpenCV-Python Tutorials · recommended 1×
  5. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow · recommended 1×
  • CATEGORY QUERY
    Seeking comprehensive resources for computer vision algorithm engineer interview preparation and practice.
    you: not recommended
    AI recommended (in order):
    1. Computer Vision: Algorithms and Applications
    2. Deep Learning
    3. OpenCV-Python Tutorials
    4. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
    5. Papers With Code
    6. LeetCode
    7. Kaggle Competitions

    AI recommended 7 alternatives but never named lcylmhlcy/Awesome-algorithm-interview. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good collections of machine learning and deep learning interview questions for engineers?
    you: not recommended
    AI recommended (in order):
    1. Cracking the Coding Interview
    2. Machine Learning Interviews
    3. Deep Learning Interviews
    4. Elements of Statistical Learning
    5. LeetCode
    6. Towards Data Science
    7. Glassdoor / Levels.fyi

    AI recommended 7 alternatives but never named lcylmhlcy/Awesome-algorithm-interview. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 lcylmhlcy/Awesome-algorithm-interview?
    pass
    AI did not name lcylmhlcy/Awesome-algorithm-interview — 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 lcylmhlcy/Awesome-algorithm-interview in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name lcylmhlcy/Awesome-algorithm-interview — 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 lcylmhlcy/Awesome-algorithm-interview solve, and who is the primary audience?
    pass
    AI did not name lcylmhlcy/Awesome-algorithm-interview — 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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lcylmhlcy/Awesome-algorithm-interview — 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