REPOGEO REPORT · LITE
PacktPublishing/Deep-Reinforcement-Learning-Hands-On
Default branch master · commit 10cd8978 · scanned 6/29/2026, 4:22:42 PM
GitHub: 3,101 stars · 1,325 forks
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.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
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/Deep-Reinforcement-Learning-Hands-On, 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.
- highreadme#1Move repo description to the top of the README
Why:
COPY-PASTE FIXMove the existing content starting with `# Deep Reinforcement Learning Hands-On Code samples for Deep Reinforcement Learning Hands-On book` to the very beginning of the README, before any newsletter promotions.
- hightopics#2Add specific topics to improve categorization
Why:
CURRENT(none)
COPY-PASTE FIX["deep-reinforcement-learning", "reinforcement-learning", "pytorch", "gym", "machine-learning", "ai", "book-companion", "hands-on-learning"]
- mediumhomepage#3Add a homepage link to the associated book
Why:
CURRENT(none)
COPY-PASTE FIXAdd the official URL for the 'Deep Reinforcement Learning Hands-On' book to the repository's homepage field.
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.
- OpenAI Gym · recommended 1×
- Stable Baselines3 · recommended 1×
- Google Colaboratory (Colab) · recommended 1×
- Kaggle Notebooks · recommended 1×
- Unity ML-Agents · recommended 1×
- CATEGORY QUERYHow can I get hands-on experience with deep reinforcement learning algorithms and techniques?you: not recommendedAI recommended (in order):
- OpenAI Gym
- Stable Baselines3
- Google Colaboratory (Colab)
- Kaggle Notebooks
- Unity ML-Agents
- PyTorch
- TensorFlow
- Minigrid
- Gymnasium-Robotics
AI recommended 9 alternatives but never named PacktPublishing/Deep-Reinforcement-Learning-Hands-On. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat are good resources for implementing deep reinforcement learning models in real-world scenarios?you: not recommendedAI recommended (in order):
- Stable Baselines3 (DLR-RM/stable-baselines3)
- Ray RLlib (ray-project/ray)
- OpenAI Gym (openai/gym)
- Gymnasium (Farama-Foundation/Gymnasium)
- Unity ML-Agents (Unity-Technologies/ml-agents)
- TensorFlow Agents (tensorflow/agents)
- DeepMind's Acme (deepmind/acme)
- PyTorch (pytorch/pytorch)
- PyTorch Lightning (Lightning-AI/lightning)
AI recommended 9 alternatives but never named PacktPublishing/Deep-Reinforcement-Learning-Hands-On. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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/Deep-Reinforcement-Learning-Hands-On?passAI did not name PacktPublishing/Deep-Reinforcement-Learning-Hands-On — 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/Deep-Reinforcement-Learning-Hands-On in production, what risks or prerequisites should they evaluate first?passAI did not name PacktPublishing/Deep-Reinforcement-Learning-Hands-On — 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?
- In one sentence, what problem does the repo PacktPublishing/Deep-Reinforcement-Learning-Hands-On solve, and who is the primary audience?passAI did not name PacktPublishing/Deep-Reinforcement-Learning-Hands-On — 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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PacktPublishing/Deep-Reinforcement-Learning-Hands-On — 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