RRepoGEO

REPOGEO REPORT · LITE

PacktPublishing/Hands-On-Reinforcement-Learning-with-Python

Default branch master · commit 21c815b2 · scanned 6/5/2026, 2:47:49 AM

GitHub: 849 stars · 337 forks

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 PacktPublishing/Hands-On-Reinforcement-Learning-with-Python, 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
  • mediumabout#1
    Expand the 'About' description to clarify its purpose

    Why:

    CURRENT
    Hands-On Reinforcement Learning with Python, published by Packt
    COPY-PASTE FIX
    Companion code repository for "Hands-On Reinforcement Learning with Python" by Packt. Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow through practical examples.
  • lowhomepage#2
    Add the book's official homepage URL

    Why:

    COPY-PASTE FIX
    https://www.packtpub.com/big-data-and-business-intelligence/hands-reinforcement-learning-python

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 PacktPublishing/Hands-On-Reinforcement-Learning-with-Python
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Gym
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Gym · recommended 1×
  2. Gymnasium · recommended 1×
  3. Stable Baselines3 · recommended 1×
  4. PyTorch · recommended 1×
  5. TensorFlow · recommended 1×
  • CATEGORY QUERY
    How can I get started with reinforcement learning using Python and popular libraries?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym
    2. Gymnasium
    3. Stable Baselines3
    4. PyTorch
    5. TensorFlow
    6. Keras
    7. RLlib
    8. Ray
    9. Acme

    AI recommended 9 alternatives but never named PacktPublishing/Hands-On-Reinforcement-Learning-with-Python. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good resources for mastering deep reinforcement learning with TensorFlow and OpenAI Gym?
    you: not recommended
    AI recommended (in order):
    1. Deep Reinforcement Learning Hands-On (Second Edition) by Maxim Lapan
    2. TensorFlow Agents (TF-Agents)
    3. Spinning Up in Deep RL by OpenAI
    4. "Deep Reinforcement Learning" course by David Silver (UCL)
    5. "Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto
    6. Practical Reinforcement Learning by O'Reilly
    7. TensorFlow Documentation and Tutorials (Official)

    AI recommended 7 alternatives but never named PacktPublishing/Hands-On-Reinforcement-Learning-with-Python. 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 PacktPublishing/Hands-On-Reinforcement-Learning-with-Python?
    pass
    AI did not name PacktPublishing/Hands-On-Reinforcement-Learning-with-Python — 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 PacktPublishing/Hands-On-Reinforcement-Learning-with-Python in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PacktPublishing/Hands-On-Reinforcement-Learning-with-Python 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 PacktPublishing/Hands-On-Reinforcement-Learning-with-Python solve, and who is the primary audience?
    pass
    AI did not name PacktPublishing/Hands-On-Reinforcement-Learning-with-Python — 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

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