RRepoGEO

REPOGEO REPORT · LITE

samwit/llm-tutorials

Default branch main · commit efc93116 · scanned 5/18/2026, 3:03:04 PM

GitHub: 1,107 stars · 292 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
18 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
0 pass · 1 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 samwit/llm-tutorials, 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
    Expand README to clarify content, audience, and unique value

    Why:

    CURRENT
    # llm-tutorials
A set of LLM Tutorials from my youtube channel https://www.youtube.com/@samwitteveenai
    COPY-PASTE FIX
    # LLM Tutorials: Hands-on Guides for Large Language Model Development

This repository provides a highly curated, practical, and consistently updated collection of executable Jupyter notebooks (often Colab-ready) for hands-on learning and experimentation with current LLM techniques and frameworks. These tutorials complement the content on my YouTube channel: https://www.youtube.com/@samwitteveenai
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with a standard open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that best suits your project's intent.
  • mediumtopics#3
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm, large-language-models, tutorials, jupyter-notebooks, machine-learning, deep-learning, ai, generative-ai, python, langchain, transformers

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 samwit/llm-tutorials
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 2×
  2. Hugging Face Transformers Course · recommended 1×
  3. DeepLearning.AI's "Generative AI with Large Language Models" · recommended 1×
  4. DeepLearning.AI's "LangChain for LLM Application Development" · recommended 1×
  5. langchain-ai/langchain · recommended 1×
  • CATEGORY QUERY
    Where can I find beginner-friendly tutorials to learn large language model development?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Course
    2. transformers (huggingface/transformers)
    3. DeepLearning.AI's "Generative AI with Large Language Models"
    4. DeepLearning.AI's "LangChain for LLM Application Development"
    5. LangChain (langchain-ai/langchain)
    6. Google's "Introduction to Generative AI" Learning Path
    7. Vertex AI
    8. freeCodeCamp's YouTube Tutorials
    9. OpenAI's Documentation and Cookbook (openai/openai-cookbook)
    10. GPT-3.5
    11. GPT-4

    AI recommended 11 alternatives but never named samwit/llm-tutorials. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    I need practical examples and guides for building applications with LLMs.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI Cookbook
    4. Hugging Face Transformers (huggingface/transformers)
    5. DeepLearning.AI
    6. Microsoft Azure AI

    AI recommended 6 alternatives but never named samwit/llm-tutorials. 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
    warn

    Suggestion:

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 samwit/llm-tutorials?
    pass
    AI did not name samwit/llm-tutorials — 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 samwit/llm-tutorials in production, what risks or prerequisites should they evaluate first?
    pass
    AI named samwit/llm-tutorials 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 samwit/llm-tutorials solve, and who is the primary audience?
    pass
    AI named samwit/llm-tutorials explicitly

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

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samwit/llm-tutorials — 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