RRepoGEO

REPOGEO REPORT · LITE

udacity/deep-learning

Default branch master · commit 6d8bdf65 · scanned 5/9/2026, 9:18:38 PM

GitHub: 4,057 stars · 4,426 forks

AI VISIBILITY SCORE
28 /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
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 udacity/deep-learning, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening paragraph to emphasize hands-on learning and projects

    Why:

    CURRENT
    This repository contains material related to Udacity's Deep Learning Nanodegree Foundation program. It consists of a bunch of tutorial notebooks for various deep learning topics. In most cases, the notebooks lead you through implementing models such as convolutional networks, recurrent networks, and GANs. There are other topics covered such as weight intialization and batch normalization.
    COPY-PASTE FIX
    This repository provides comprehensive, hands-on tutorial notebooks and beginner-friendly projects for Udacity's Deep Learning Nanodegree Foundation program. Dive into implementing core deep learning models like convolutional networks, recurrent networks, and GANs, with practical examples covering TensorFlow, weight initialization, batch normalization, and more.
  • mediumabout#2
    Refine the repository description with more keywords

    Why:

    CURRENT
    Repo for the Deep Learning Nanodegree Foundations program.
    COPY-PASTE FIX
    Hands-on tutorials and projects for Udacity's Deep Learning Nanodegree Foundation, covering TensorFlow, neural networks, CNNs, RNNs, GANs, and more for beginners.

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 udacity/deep-learning
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow Tutorials
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow Tutorials · recommended 1×
  2. DeepLearning.AI TensorFlow in Practice Specialization · recommended 1×
  3. TensorFlow 2.0 Complete Guide · recommended 1×
  4. ageron/handson-ml2 · recommended 1×
  5. Keras Documentation · recommended 1×
  • CATEGORY QUERY
    Looking for hands-on guides to build convolutional and recurrent neural networks with TensorFlow.
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Tutorials
    2. DeepLearning.AI TensorFlow in Practice Specialization
    3. TensorFlow 2.0 Complete Guide
    4. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (ageron/handson-ml2)
    5. Keras Documentation
    6. Towards Data Science

    AI recommended 6 alternatives but never named udacity/deep-learning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good introductory deep learning project ideas for beginners with code examples?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow/Keras
    2. PyTorch
    3. NLTK
    4. spaCy
    5. scikit-learn
    6. NumPy
    7. Pandas

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

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

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite