RRepoGEO

REPOGEO REPORT · LITE

duoan/TorchCode

Default branch master · commit 63cae3bc · scanned 5/10/2026, 3:08:07 AM

GitHub: 3,886 stars · 317 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 duoan/TorchCode, 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 emphasize 'LeetCode for PyTorch interviews'

    Why:

    CURRENT
    # 🔥 TorchCode

**Crack the PyTorch interview.**

Practice implementing operators and architectures from scratch — the exact skills top ML teams test for.

*Like LeetCode, but for tensors. Self-hosted. Jupyter-based. Instant feedback.*
    COPY-PASTE FIX
    # 🔥 TorchCode: LeetCode for PyTorch Interviews

**Practice implementing PyTorch operators and architectures from scratch with instant auto-grading.** This platform is designed to help you **crack the PyTorch interview** by building the exact skills top ML teams test for.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumabout#3
    Refine the 'About' description for clarity on purpose

    Why:

    CURRENT
    🔥 LeetCode for PyTorch — practice implementing softmax, attention, GPT-2 and more from scratch with instant auto-grading. Jupyter-based, self-hosted or try online.
    COPY-PASTE FIX
    🔥 **ML Interview Prep:** LeetCode-style platform for PyTorch. Practice implementing softmax, attention, GPT-2 from scratch with instant auto-grading. Self-hosted or try online.

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 duoan/TorchCode
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Documentation and Tutorials
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Documentation and Tutorials · recommended 1×
  2. Fast.ai's 'Practical Deep Learning for Coders' Course · recommended 1×
  3. 'Deep Learning from Scratch' by Seth Weidman · recommended 1×
  4. pytorch/examples · recommended 1×
  5. Kaggle Notebooks · recommended 1×
  • CATEGORY QUERY
    How can I practice implementing PyTorch models and algorithms from scratch for ML interviews?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Documentation and Tutorials
    2. Fast.ai's 'Practical Deep Learning for Coders' Course
    3. 'Deep Learning from Scratch' by Seth Weidman
    4. PyTorch Examples Repository (pytorch/examples)
    5. Kaggle Notebooks
    6. 'Dive into Deep Learning'
    7. Hugging Face Transformers Library (huggingface/transformers)

    AI recommended 7 alternatives but never named duoan/TorchCode. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a LeetCode-style platform to practice deep learning operations and architectures with instant feedback.
    you: not recommended
    AI recommended (in order):
    1. DeepLearning.AI's TensorFlow in Practice Specialization
    2. Kaggle Learn
    3. Google's Machine Learning Crash Course
    4. PyTorch Tutorials
    5. Coursera
    6. edX
    7. Andrew Ng's Deep Learning Specialization
    8. TensorFlow (tensorflow/tensorflow)
    9. Keras (keras-team/keras)
    10. PyTorch (pytorch/pytorch)
    11. Hugging Face Transformers Course

    AI recommended 11 alternatives but never named duoan/TorchCode. 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 duoan/TorchCode?
    pass
    AI named duoan/TorchCode explicitly

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

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

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

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duoan/TorchCode — 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