mimoralea/gdrl resource

Health v2 · maintenance only

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1036 stars · 278 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Companion code repository for the Manning book 'Grokking Deep Reinforcement Learning' by Miguel Morales, containing Jupyter notebooks covering deep RL from mathematical foundations to advanced actor-critic methods. The code is designed to run in a preconfigured Docker container with optional NVIDIA GPU support.

Use cases

• learn deep reinforcement learning from scratch
• study DQN and value-based deep RL methods
• understand policy-gradient and actor-critic algorithms
• run RL notebook examples in a reproducible Docker environment
• get hands-on PyTorch and NumPy practice for RL agents
• follow along with the Grokking Deep Reinforcement Learning book exercises

When to choose

• you want a structured, book-guided path into deep reinforcement learning
• you prefer runnable Jupyter notebooks over reading theory alone
• you want a preconfigured Docker environment so setup just works
• you are learning value-based and actor-critic methods with PyTorch

When to avoid

• you need a production RL training framework or library
• you want actively updated code for the latest RL algorithms
• you cannot or prefer not to use Docker
• you need a lightweight pip-installable package rather than a notebook collection

Facets

learning-resource · maturity maintenance

deep-learning reinforcement-learning machine-learning reinforcement-learning deep-learning machine-learning artificial-intelligence tutorials python cross-platform jupyter-notebooks pytorch numpy book-companion-code nvidia-docker dqn policy-gradient actor-critic docker gpu

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