RRepoGEO

REPOGEO REPORT · LITE

tanishqkumar/beyond-nanogpt

Default branch main · commit e9eb95c7 · scanned 5/19/2026, 3:02:52 AM

GitHub: 1,310 stars · 108 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 tanishqkumar/beyond-nanogpt, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumhomepage#1
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/tanishqkumar/beyond-nanogpt
  • lowabout#2
    Enhance the repository description for better keyword density

    Why:

    CURRENT
    Minimal and annotated implementations of key ideas from modern deep learning research.
    COPY-PASTE FIX
    From-scratch, annotated implementations of 100+ modern deep learning techniques: LLMs (KV caching, speculative decoding), Vision Transformers, Diffusion Models, Flow Matching, PPO, A3C, AlphaZero, GPU communication, and more. Bridge nanoGPT to research-level AI.

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 tanishqkumar/beyond-nanogpt
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Deep Learning from Scratch: Building Neural Networks with Python from First Principles by Seth Weidman
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Deep Learning from Scratch: Building Neural Networks with Python from First Principles by Seth Weidman · recommended 1×
  2. Stanford CS231n: Convolutional Neural Networks for Visual Recognition (Course Materials) · recommended 1×
  3. fast.ai's "Deep Learning for Coders" Course · recommended 1×
  4. The Annotated Transformer by Alexander Rush · recommended 1×
  5. karpathy/minGPT · recommended 1×
  • CATEGORY QUERY
    Where can I find thoroughly explained, from-scratch implementations of advanced deep learning algorithms?
    you: not recommended
    AI recommended (in order):
    1. Deep Learning from Scratch: Building Neural Networks with Python from First Principles by Seth Weidman
    2. Stanford CS231n: Convolutional Neural Networks for Visual Recognition (Course Materials)
    3. fast.ai's "Deep Learning for Coders" Course
    4. The Annotated Transformer by Alexander Rush
    5. karpathy/minGPT (karpathy/minGPT)
    6. Machine Learning Mastery by Jason Brownlee

    AI recommended 6 alternatives but never named tanishqkumar/beyond-nanogpt. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking educational resources to understand modern AI research topics, from LLMs to reinforcement learning.
    you: not recommended
    AI recommended (in order):
    1. DeepLearning.AI
    2. Deep Learning Specialization
    3. Natural Language Processing Specialization
    4. Reinforcement Learning Specialization
    5. Hugging Face
    6. Hugging Face Course
    7. transformers Library (huggingface/transformers)
    8. fast.ai
    9. Practical Deep Learning for Coders
    10. OpenAI
    11. Spinning Up in Deep RL (openai/spinningup)
    12. MIT 6.S191
    13. Dive into Deep Learning (d2l-ai/d2l-en)
    14. PyTorch (pytorch/pytorch)
    15. TensorFlow (tensorflow/tensorflow)
    16. JAX (google/jax)
    17. Reinforcement Learning: An Introduction

    AI recommended 17 alternatives but never named tanishqkumar/beyond-nanogpt. 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 tanishqkumar/beyond-nanogpt?
    pass
    AI named tanishqkumar/beyond-nanogpt explicitly

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

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

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

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tanishqkumar/beyond-nanogpt — 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