RRepoGEO

REPOGEO REPORT · LITE

business-science/awesome-generative-ai-data-scientist

Default branch main · commit 673d5ed2 · scanned 6/25/2026, 9:22:06 AM

GitHub: 1,562 stars · 257 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
22 /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
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 business-science/awesome-generative-ai-data-scientist, 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
    Strengthen README's opening sentence to emphasize problem-solving

    Why:

    CURRENT
    A curated list of 100+ resources to help you become a Generative AI Data Scientist.
    COPY-PASTE FIX
    Navigate the Generative AI landscape with this comprehensive, curated list of 100+ resources specifically for Data Scientists building and deploying LLM applications.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Add a `LICENSE` file to the repository root, choosing an appropriate open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that aligns with your project's goals.
  • mediumhomepage#3
    Add a homepage URL to the repository About section

    Why:

    COPY-PASTE FIX
    Add a relevant URL to the 'Homepage' field in the repository settings (e.g., a project website, a blog post about the list, or even the GitHub repo URL itself if no other site exists).

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 business-science/awesome-generative-ai-data-scientist
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. Generative AI for Everyone · recommended 1×
  3. Generative AI with Large Language Models Specialization · recommended 1×
  4. Practical Deep Learning for Coders · recommended 1×
  5. Generative AI Learning Path · recommended 1×
  • CATEGORY QUERY
    Where can I find resources to learn generative AI for data science applications?
    you: not recommended
    AI recommended (in order):
    1. Generative AI for Everyone
    2. Generative AI with Large Language Models Specialization
    3. Hugging Face Transformers Library (huggingface/transformers)
    4. Practical Deep Learning for Coders
    5. Generative AI Learning Path
    6. Generative Deep Learning
    7. PyTorch (pytorch/pytorch)
    8. TensorFlow (tensorflow/tensorflow)

    AI recommended 8 alternatives but never named business-science/awesome-generative-ai-data-scientist. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What resources are available for building and deploying LLM applications as a data scientist?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Hugging Face Transformers (huggingface/transformers)
    4. Accelerate (huggingface/accelerate)
    5. OpenAI API
    6. Azure OpenAI Service
    7. MLflow (mlflow/mlflow)
    8. Gradio (gradio-app/gradio)
    9. Streamlit (streamlit/streamlit)
    10. Kubernetes (kubernetes/kubernetes)
    11. Kubeflow (kubeflow/kubeflow)
    12. KServe (kserve/kserve)

    AI recommended 12 alternatives but never named business-science/awesome-generative-ai-data-scientist. 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 business-science/awesome-generative-ai-data-scientist?
    pass
    AI did not name business-science/awesome-generative-ai-data-scientist — 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 business-science/awesome-generative-ai-data-scientist in production, what risks or prerequisites should they evaluate first?
    pass
    AI named business-science/awesome-generative-ai-data-scientist 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 business-science/awesome-generative-ai-data-scientist solve, and who is the primary audience?
    pass
    AI did not name business-science/awesome-generative-ai-data-scientist — 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?

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business-science/awesome-generative-ai-data-scientist — 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