RRepoGEO

REPOGEO REPORT · LITE

lynnlangit/learning-cloud

Default branch master · commit bc0031bc · scanned 6/14/2026, 12:57:30 AM

GitHub: 698 stars · 240 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 lynnlangit/learning-cloud, 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 README opening to emphasize "curated learning resource hub"

    Why:

    CURRENT
    This Repo contains links to **100+ resources** I've created for you to learn to work on AI in the public cloud.
    COPY-PASTE FIX
    This repository serves as a comprehensive, curated hub of **100+ learning resources** I've created, designed to guide you through building AI solutions across major public cloud providers (AWS, Azure, GCP, and more).
  • mediumtopics#2
    Add "learning-path" or "resource-hub" related topics

    Why:

    CURRENT
    aws, aws-cloud, azure, cloud, cloud-architecture, cloudcomputing, gcp, genai, google-cloud-platform, googlecloud, ibm-cloud, microsoft-azure, quantum-computing, serverless
    COPY-PASTE FIX
    aws, aws-cloud, azure, cloud, cloud-architecture, cloudcomputing, gcp, genai, google-cloud-platform, googlecloud, ibm-cloud, microsoft-azure, quantum-computing, serverless, learning-path, cloud-learning, ai-learning-resources
  • lowabout#3
    Refine description to emphasize learning over direct adoption of code

    Why:

    CURRENT
    Courses, sample code, articles & screencasts - AWS, Azure, & GCP
    COPY-PASTE FIX
    A curated collection of courses, articles, screencasts, and illustrative sample code to help you learn and build AI solutions across AWS, Azure, & GCP.

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 lynnlangit/learning-cloud
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Amazon SageMaker
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Amazon SageMaker · recommended 2×
  2. Azure Machine Learning · recommended 2×
  3. Coursera · recommended 1×
  4. Google Cloud · recommended 1×
  5. AWS · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive learning resources for building AI solutions across major cloud providers?
    you: not recommended
    AI recommended (in order):
    1. Coursera
    2. Google Cloud
    3. AWS
    4. Microsoft Azure
    5. edX
    6. AWS Training and Certification
    7. Amazon SageMaker
    8. Amazon Rekognition
    9. Amazon Comprehend
    10. Google Cloud Skills Boost
    11. Google Cloud AI Platform
    12. Vertex AI
    13. BigQuery ML
    14. Microsoft Learn
    15. Azure Machine Learning
    16. Azure Cognitive Services
    17. Azure Databricks
    18. Pluralsight
    19. Udemy
    20. O'Reilly Online Learning

    AI recommended 20 alternatives but never named lynnlangit/learning-cloud. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking practical guidance and architectural patterns for deploying machine learning applications on public clouds.
    you: not recommended
    AI recommended (in order):
    1. Docker
    2. Kubernetes (K8s)
    3. Amazon Elastic Container Service (ECS)
    4. Google Kubernetes Engine (GKE)
    5. Azure Kubernetes Service (AKS)
    6. Amazon SageMaker
    7. Google Cloud AI Platform (Vertex AI)
    8. Azure Machine Learning
    9. AWS Lambda
    10. Google Cloud Functions
    11. Azure Functions
    12. Amazon S3 (Simple Storage Service)
    13. Google Cloud Storage
    14. Azure Blob Storage
    15. Amazon DynamoDB
    16. Google Cloud Bigtable
    17. Prometheus
    18. Grafana
    19. Amazon CloudWatch
    20. Google Cloud Monitoring (formerly Stackdriver)
    21. Azure Monitor
    22. MLflow

    AI recommended 22 alternatives but never named lynnlangit/learning-cloud. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 lynnlangit/learning-cloud?
    pass
    AI named lynnlangit/learning-cloud explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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