RRepoGEO

REPOGEO REPORT · LITE

udacity/deep-reinforcement-learning

Default branch master · commit 561eec3a · scanned 5/26/2026, 1:48:13 AM

GitHub: 5,165 stars · 2,379 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 udacity/deep-reinforcement-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

3 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 clarify its educational purpose

    Why:

    CURRENT
    This repository contains material related to Udacity's Deep Reinforcement Learning Nanodegree program.
    COPY-PASTE FIX
    This repository provides the official code, projects, and learning materials for Udacity's Deep Reinforcement Learning Nanodegree program, designed for students and aspiring AI engineers to learn and implement DRL algorithms from scratch.
  • mediumtopics#2
    Add more specific educational and learning-oriented topics

    Why:

    CURRENT
    cross-entropy, ddpg, deep-reinforcement-learning, dqn, dynamic-programming, hill-climbing, ml-agents, neural-networks, openai-gym, openai-gym-solutions, ppo, pytorch, pytorch-rl, reinforcement-learning, reinforcement-learning-algorithms, rl-algorithms
    COPY-PASTE FIX
    cross-entropy, ddpg, deep-reinforcement-learning, dqn, dynamic-programming, hill-climbing, ml-agents, neural-networks, openai-gym, openai-gym-solutions, ppo, pytorch, pytorch-rl, reinforcement-learning, reinforcement-learning-algorithms, rl-algorithms, deep-learning-course, reinforcement-learning-tutorial, educational-resource, learning-path, ai-nanodegree
  • lowreadme#3
    Add a dedicated section to the README clarifying the target audience and purpose

    Why:

    COPY-PASTE FIX
    ## Who is this repository for?
    This repository is ideal for students, aspiring AI engineers, and anyone looking to gain hands-on experience with deep reinforcement learning. It serves as the primary resource for the Udacity Deep Reinforcement Learning Nanodegree, offering structured projects and code implementations to build a strong foundation in DRL.

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-reinforcement-learning
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Python
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Python · recommended 1×
  2. NumPy · recommended 1×
  3. Matplotlib · recommended 1×
  4. Seaborn · recommended 1×
  5. PyTorch · recommended 1×
  • CATEGORY QUERY
    How can I learn and implement deep reinforcement learning algorithms from scratch?
    you: not recommended
    AI recommended (in order):
    1. Python
    2. NumPy
    3. Matplotlib
    4. Seaborn
    5. PyTorch
    6. TensorFlow
    7. Keras API
    8. Gymnasium
    9. OpenAI Gym
    10. PettingZoo
    11. Weights & Biases (W&B)
    12. TensorBoard

    AI recommended 12 alternatives but never named udacity/deep-reinforcement-learning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best Python libraries for building deep reinforcement learning models?
    you: not recommended
    AI recommended (in order):
    1. RLlib
    2. Stable Baselines3
    3. Tianshou
    4. Acme
    5. CleanRL
    6. Keras-RL

    AI recommended 6 alternatives but never named udacity/deep-reinforcement-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
    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 udacity/deep-reinforcement-learning?
    pass
    AI named udacity/deep-reinforcement-learning explicitly

    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-reinforcement-learning in production, what risks or prerequisites should they evaluate first?
    pass
    AI named udacity/deep-reinforcement-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-reinforcement-learning solve, and who is the primary audience?
    pass
    AI named udacity/deep-reinforcement-learning explicitly

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

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