RRepoGEO

REPOGEO REPORT · LITE

GoogleCloudPlatform/cloudml-samples

Default branch main · commit efddc4a9 · scanned 6/30/2026, 2:11:51 PM

GitHub: 1,551 stars · 842 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
27 /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
1 / 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 GoogleCloudPlatform/cloudml-samples, 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
  • highhomepage#1
    Update homepage to point to Vertex AI samples

    Why:

    CURRENT
    https://cloud.google.com/ai-platform/docs/
    COPY-PASTE FIX
    https://github.com/GoogleCloudPlatform/vertex-ai-samples
  • mediumtopics#2
    Add topics to clarify legacy status and Vertex AI relationship

    Why:

    CURRENT
    cloudml, cloudml-samples, gcp, keras, keras-tensorflow, samples
    COPY-PASTE FIX
    cloudml, cloudml-samples, gcp, keras, keras-tensorflow, samples, ai-platform, legacy, vertex-ai-migration, archived
  • lowreadme#3
    Add a concise statement about the repo's legacy status to the README's opening

    Why:

    CURRENT
    Welcome to the AI Platform Training and Prediction sample code repository. This repository contains samples for how to use AI Platform for model training and serving.
    COPY-PASTE FIX
    Welcome to the **legacy** AI Platform Training and Prediction sample code repository. This repository contains samples for how to use AI Platform for model training and serving. **For current samples, please visit the new Vertex AI samples repo.**

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 GoogleCloudPlatform/cloudml-samples
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Vertex AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Vertex AI · recommended 2×
  2. Azure Machine Learning · recommended 2×
  3. Amazon SageMaker · recommended 1×
  4. Databricks Machine Learning · recommended 1×
  5. Hugging Face Inference Endpoints · recommended 1×
  • CATEGORY QUERY
    What managed service helps train and deploy machine learning models at scale?
    you: not recommended
    AI recommended (in order):
    1. Amazon SageMaker
    2. Google Cloud Vertex AI
    3. Azure Machine Learning
    4. Databricks Machine Learning
    5. Hugging Face Inference Endpoints
    6. Weights & Biases (W&B)

    AI recommended 6 alternatives but never named GoogleCloudPlatform/cloudml-samples. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I run Keras or TensorFlow training jobs efficiently on a cloud infrastructure?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Vertex AI
    2. AWS SageMaker Training
    3. Azure Machine Learning
    4. Google Colaboratory Pro/Pro+
    5. RunPod.io
    6. Lambda Labs Cloud
    7. Paperspace Gradient

    AI recommended 7 alternatives but never named GoogleCloudPlatform/cloudml-samples. 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 GoogleCloudPlatform/cloudml-samples?
    pass
    AI did not name GoogleCloudPlatform/cloudml-samples — 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 GoogleCloudPlatform/cloudml-samples in production, what risks or prerequisites should they evaluate first?
    pass
    AI named GoogleCloudPlatform/cloudml-samples 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 GoogleCloudPlatform/cloudml-samples solve, and who is the primary audience?
    pass
    AI did not name GoogleCloudPlatform/cloudml-samples — 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?

Embed your GEO score

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

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GoogleCloudPlatform/cloudml-samples — 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