RRepoGEO

REPOGEO REPORT · LITE

zhengjingwei/machine-learning-interview

Default branch master · commit 51323ebe · scanned 7/1/2026, 12:18:22 PM

GitHub: 1,678 stars · 218 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 zhengjingwei/machine-learning-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
  • highreadme#1
    Add a clear, concise introductory sentence to the README

    Why:

    CURRENT
    The README currently starts with `[TOC] # 一、机器学习相关`.
    COPY-PASTE FIX
    本仓库是为算法工程师和机器学习工程师精心整理的面试题总结，涵盖机器学习、深度学习等核心概念，并提供详细解答，助您高效备战技术面试。
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root, for example, using the MIT License or CC-BY-SA-4.0 for content, to clearly define usage terms.
  • mediumhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    If a relevant external website or blog post exists that complements this repository, add its URL to the 'Homepage' field in the repository settings.

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 zhengjingwei/machine-learning-interview
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SMOTE
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. SMOTE · recommended 1×
  2. ADASYN · recommended 1×
  3. Random Oversampling · recommended 1×
  4. Random Undersampling · recommended 1×
  5. Tomek Links · recommended 1×
  • CATEGORY QUERY
    What are common machine learning interview questions and answers for algorithm engineers?
    you: not recommended
    AI recommended (in order):
    1. SMOTE
    2. ADASYN
    3. Random Oversampling
    4. Random Undersampling
    5. Tomek Links
    6. Edited Nearest Neighbors (ENN)
    7. Support Vector Machines
    8. XGBoost
    9. LightGBM
    10. scikit-learn
    11. Random Forest
    12. AdaBoost
    13. Gradient Boosting Machines (GBM)
    14. CatBoost
    15. ReLU
    16. Sigmoid
    17. Tanh
    18. YOLO
    19. Faster R-CNN
    20. U-Net
    21. Mask R-CNN
    22. ImageNet
    23. CIFAR-10
    24. Adam
    25. SGD
    26. Batch Normalization
    27. Residual Connections
    28. LSTMs
    29. GRUs
    30. SHAP
    31. LIME

    AI recommended 31 alternatives but never named zhengjingwei/machine-learning-interview. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find explanations of core machine learning concepts for interview preparation?
    you: not recommended
    AI recommended (in order):
    1. Machine Learning Cheatsheet (Stanford CS229)
    2. Towards Data Science (Medium)
    3. Analytics Vidhya
    4. Krish Naik (YouTube Channel)
    5. StatQuest with Josh Starmer (YouTube Channel)
    6. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (Aurélien Géron)
    7. GeeksforGeeks (Machine Learning Section)

    AI recommended 7 alternatives but never named zhengjingwei/machine-learning-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
    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 zhengjingwei/machine-learning-interview?
    pass
    AI named zhengjingwei/machine-learning-interview explicitly

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

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

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

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zhengjingwei/machine-learning-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