#python #baselines #gym #machine_learning #openai #pytorch #reinforcement_learning #reinforcement_learning_algorithms #robotics #sde #stable_baselines #toolbox

https://github.com/DLR-RM/stable-baselines3

#python #alphago #alphazero #deep_learning #deep_reinforcement_learning #gym #machine_learning #mcts #model_based_rl #monte_carlo_tree_search #muzero #muzero_general #neural_network #python3 #pytorch #reinforcement_learning #residual_network #rl #self_learning #tensorboard

https://github.com/werner-duvaud/muzero-general

#python #deep_reinforcement_learning #gym #hyperparameter_optimization #hyperparameter_search #hyperparameter_tuning #lab #openai #optimization #pybullet #pybullet_environments #pytorch #reinforcement_learning #rl #robotics #sde #stable_baselines #tuning_hyperparameters

https://github.com/DLR-RM/rl-baselines3-zoo

#python #a2c #actor_critic #advantage_actor_critic #ale #atari #deep_learning #deep_reinforcement_learning #gym #machine_learning #phasic_policy_gradient #ppo #proximal_policy_optimization #pytorch #reinforcement_learning #wandb

https://github.com/vwxyzjn/cleanrl

#python #api #gym #reinforcement_learning

https://github.com/Farama-Foundation/Gymnasium

#python #baselines #gsde #gym #machine_learning #openai #python #pytorch #reinforcement_learning #reinforcement_learning_algorithms #robotics #sb3 #sde #stable_baselines #toolbox

Stable Baselines3 (SB3) is a tool that makes it easy to use reinforcement learning algorithms with PyTorch. It provides reliable and tested implementations of these algorithms, which helps researchers and developers build projects quickly. SB3 offers many features like custom environments, policies, and integration with other tools like Tensorboard and Hugging Face. It also has detailed documentation and examples to help beginners get started. This tool assumes you have some knowledge of reinforcement learning but provides resources to learn more. Using SB3 can save time and effort by providing a stable base for your projects, allowing you to focus on new ideas and improvements.

https://github.com/DLR-RM/stable-baselines3

#python #django #fitness #gym #hacktoberfest #python #self_hosted #workout

Wger is a free and open-source web application that helps you manage your workouts, weight, and diet plans. It can also be used to manage a gym. You can access it through a website or download the mobile app from Google Play, Apple App Store, F-Droid, or Flathub. Wger offers a REST API for easy integration with other tools. You can try it out quickly using a demo or install your own instance using Docker. The app is highly customizable and has detailed documentation available. This tool benefits you by keeping all your fitness and diet plans organized in one place, making it easier to track your progress and stay motivated.

https://github.com/wger-project/wger

#python #gym #gym_environment #reinforcement_learning #reinforcement_learning_agent #reinforcement_learning_environments #rl_environment #rl_training

NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior.

https://github.com/NVIDIA-NeMo/Gym