RL learning resource using OpenAI Gym and TensorFlow
Top 44.1% on sourcepulse
This repository provides code examples for the "Hands-On Reinforcement Learning with Python" book, targeting machine learning developers and AI enthusiasts. It aims to teach fundamental and advanced reinforcement learning (RL) and deep RL algorithms using OpenAI Gym and TensorFlow.
How It Works
The book's approach involves understanding core RL concepts like Markov Decision Processes and Bellman's optimality, then applying them to practical problems. It covers algorithms such as TD learning and multi-armed bandits, progressing to deep learning models like RNNs, LSTMs, and CNNs for RL applications. The code is structured by chapter, demonstrating agent training and algorithm implementation.
Quick Start & Requirements
Chapter02
).Highlighted Details
Maintenance & Community
The repository is associated with author Sudharsan Ravichandiran, a data scientist and AI enthusiast with a focus on RL and deep learning implementations.
Licensing & Compatibility
The repository's license is not specified in the README. Compatibility for commercial use or closed-source linking is not detailed.
Limitations & Caveats
The README does not specify a license, which may impact commercial use or integration into proprietary projects. Specific version requirements for Anaconda or Python are not listed.
2 years ago
Inactive