RRepoGEO

REPOGEO REPORT · LITE

wandb/edu

Default branch main · commit dbf299fd · scanned 6/4/2026, 10:37:44 AM

GitHub: 677 stars · 289 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 wandb/edu, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm, large-language-models, prompt-engineering, rag, machine-learning-education, deep-learning, mlops, weights-and-biases, ai-academy
  • mediumabout#2
    Refine the 'About' description for specificity

    Why:

    CURRENT
    Educational materials on deep learning by Weights & Biases
    COPY-PASTE FIX
    Practical educational materials and courses on LLM engineering, prompt engineering, RAG, and MLOps, powered by Weights & Biases.
  • lowreadme#3
    Enhance the README's introductory sentence

    Why:

    CURRENT
    Welcome to the W&B AI Academy! This repository contains materials for learning AI, organized by topic. These materials are designed to complement our online courses but can also be useful on their own.
    COPY-PASTE FIX
    Welcome to the W&B AI Academy! This repository provides practical, hands-on educational materials and courses for mastering LLM engineering, prompt engineering, RAG, and MLOps, designed to complement our online courses and be useful on their own.

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 wandb/edu
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Generative AI with Large Language Models Specialization
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Generative AI with Large Language Models Specialization · recommended 1×
  2. openai/openai-cookbook · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. Full Stack LLM Bootcamp · recommended 1×
  5. LLM University · recommended 1×
  • CATEGORY QUERY
    Where can I find educational materials to learn about practical LLM engineering techniques?
    you: not recommended
    AI recommended (in order):
    1. Generative AI with Large Language Models Specialization
    2. OpenAI Cookbook (openai/openai-cookbook)
    3. Hugging Face Transformers Documentation and Tutorials (huggingface/transformers)
    4. Full Stack LLM Bootcamp
    5. LLM University
    6. Applied LLM Engineering by Eugene Yan
    7. Prompt Engineering Guide

    AI recommended 7 alternatives but never named wandb/edu. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good learning resources for prompt engineering and RAG implementation best practices?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. LangChain Expression Language (LCEL)
    4. Hugging Face Transformers
    5. Hugging Face Datasets
    6. Pinecone
    7. Weaviate

    AI recommended 7 alternatives but never named wandb/edu. 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 wandb/edu?
    pass
    AI named wandb/edu explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of wandb/edu. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/wandb/edu.svg)](https://repogeo.com/en/r/wandb/edu)
HTML
<a href="https://repogeo.com/en/r/wandb/edu"><img src="https://repogeo.com/badge/wandb/edu.svg" alt="RepoGEO" /></a>
Pro

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wandb/edu — 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
wandb/edu — RepoGEO report