RRepoGEO

REPOGEO REPORT · LITE

WengLean/hands-on-research-tutorial

Default branch main · commit 1d5bc21c · scanned 6/16/2026, 12:56:48 AM

GitHub: 566 stars · 23 forks

AI VISIBILITY SCORE
17 /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
1 / 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 WengLean/hands-on-research-tutorial, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-research, deep-learning, machine-learning, research-methodology, beginner-guide, tutorial, education, python, pytorch
  • highlicense#2
    Add a LICENSE file to clarify usage terms

    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 template.
  • mediumreadme#3
    Strengthen README's initial positioning for AI research beginners

    Why:

    CURRENT
    1. **介绍** ：本项目是一套完整的科研计划，旨在帮助大家少走弯路，循序渐进掌握科研工具 ，关注作者
    COPY-PASTE FIX
    《动手做科研》面向科研初学者，一步一步地展示如何入门人工智能科研。本项目是一套完整的科研计划，旨在帮助大家少走弯路，循序渐进掌握科研工具。

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 WengLean/hands-on-research-tutorial
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Khan Academy
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Khan Academy · recommended 1×
  2. 3Blue1Brown · recommended 1×
  3. Mathematics for Machine Learning · recommended 1×
  4. Python.org · recommended 1×
  5. Codecademy · recommended 1×
  • CATEGORY QUERY
    What are the essential steps for a beginner to start an AI research project?
    you: not recommended
    AI recommended (in order):
    1. Khan Academy
    2. 3Blue1Brown
    3. Mathematics for Machine Learning
    4. Python.org
    5. Codecademy
    6. freeCodeCamp
    7. Coursera's "Machine Learning" by Andrew Ng
    8. fast.ai's "Practical Deep Learning for Coders"
    9. Deep Learning by Ian Goodfellow et al.
    10. Python
    11. PyTorch (pytorch/pytorch)
    12. TensorFlow (tensorflow/tensorflow)
    13. Keras API (keras-team/keras)
    14. JAX (google/jax)
    15. NumPy (numpy/numpy)
    16. Pandas (pandas-dev/pandas)
    17. Matplotlib (matplotlib/matplotlib)
    18. Seaborn (mwaskom/seaborn)
    19. Jupyter Notebooks/JupyterLab
    20. VS Code (microsoft/vscode)
    21. Kaggle
    22. UCI Machine Learning Repository
    23. Google Dataset Search
    24. Hugging Face Datasets (huggingface/datasets)
    25. SHAP (shap/shap)
    26. LIME (marcotcr/lime)

    AI recommended 26 alternatives but never named WengLean/hands-on-research-tutorial. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I find a comprehensive guide for beginners to learn AI research methodologies?
    you: not recommended
    AI recommended (in order):
    1. The Hundred-Page Machine Learning Book
    2. Deep Learning
    3. Machine Learning Engineering
    4. Coursera
    5. edX
    6. YouTube
    7. Pattern Recognition and Machine Learning
    8. Dive into Deep Learning
    9. Elements of Statistical Learning

    AI recommended 9 alternatives but never named WengLean/hands-on-research-tutorial. 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 WengLean/hands-on-research-tutorial?
    pass
    AI did not name WengLean/hands-on-research-tutorial — 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 WengLean/hands-on-research-tutorial in production, what risks or prerequisites should they evaluate first?
    pass
    AI named WengLean/hands-on-research-tutorial 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 WengLean/hands-on-research-tutorial solve, and who is the primary audience?
    pass
    AI did not name WengLean/hands-on-research-tutorial — 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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WengLean/hands-on-research-tutorial — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
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