REPOGEO REPORT · LITE
sudharsan13296/Hands-On-Reinforcement-Learning-With-Python
Default branch master · commit 5440811d · scanned 6/2/2026, 6:37:57 AM
GitHub: 866 stars · 323 forks
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 sudharsan13296/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
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Prominently clarify this repo's edition and direct to the new repo
Why:
CURRENT## Check out the completely revised and updated second editon of this book which covers basic to advanced deep RL algorithms with extensive math. Check out the new repo here.
COPY-PASTE FIX**IMPORTANT: This repository contains the code examples for the *first edition* of the book "Hands-On Reinforcement Learning With Python". For the completely revised and updated second edition, which covers basic to advanced deep RL algorithms with extensive math, please refer to the [official repository for the second edition here](YOUR_NEW_REPO_LINK).**
- highlicense#2Add a LICENSE file to the repository
Why:
COPY-PASTE FIXCreate a LICENSE file in the root of the repository, clearly stating the terms under which the code is distributed (e.g., MIT, Apache-2.0, or a custom license if applicable).
- mediumreadme#3Reposition the README's opening to clearly state its educational purpose
Why:
CURRENT# Hands-On Reinforcement Learning With Python ### Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
COPY-PASTE FIXThis repository serves as the official code companion for the book "Hands-On Reinforcement Learning With Python". It provides practical, hands-on examples and implementations for mastering reinforcement and deep reinforcement learning algorithms using OpenAI Gym and TensorFlow, targeting students and practitioners.
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.
- TensorFlow · recommended 3×
- PyTorch · recommended 3×
- OpenAI Gym · recommended 2×
- Farama Foundation Gymnasium · recommended 2×
- DLR-RM/stable-baselines3 · recommended 1×
- CATEGORY QUERYWhat are good resources for implementing deep reinforcement learning algorithms in Python?you: not recommendedAI recommended (in order):
- Stable Baselines3 (SB3) (DLR-RM/stable-baselines3)
- RLlib (part of Ray) (ray-project/ray)
- CleanRL (vwxyzjn/cleanrl)
- Tianshou (thu-ml/tianshou)
- DeepMind's Acme (deepmind/acme)
- Keras-RL (keras-rl/keras-rl)
- PyTorch-RL (various community projects)
AI recommended 7 alternatives but never named sudharsan13296/Hands-On-Reinforcement-Learning-With-Python. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking practical examples to learn advanced deep reinforcement learning techniques and concepts.you: not recommendedAI recommended (in order):
- OpenAI Gym
- Farama Foundation Gymnasium
- Stable Baselines3
- DeepMind Lab
- DeepMind Control Suite
- Keras
- TensorFlow
- PyTorch
- Unity ML-Agents Toolkit
- Unity
- Minigrid
- MiniWorld
- PyTorch
- TensorFlow
- OpenAI Gym
- Farama Foundation Gymnasium
- Ray RLlib
- Atari Learning Environment (ALE)
- PyTorch
- TensorFlow
- Google Dopamine
AI recommended 21 alternatives but never named sudharsan13296/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 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 sudharsan13296/Hands-On-Reinforcement-Learning-With-Python?passAI did not name sudharsan13296/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 sudharsan13296/Hands-On-Reinforcement-Learning-With-Python in production, what risks or prerequisites should they evaluate first?passAI did not name sudharsan13296/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?
- In one sentence, what problem does the repo sudharsan13296/Hands-On-Reinforcement-Learning-With-Python solve, and who is the primary audience?passAI did not name sudharsan13296/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?
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sudharsan13296/Hands-On-Reinforcement-Learning-With-Python — 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