1,324-exercise fitness dataset — animation GIFs, 180×180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.
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Updated
Jul 16, 2026 - HTML
1,324-exercise fitness dataset — animation GIFs, 180×180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
🏋 Modern open-source fitness coaching platform. Create workout plans, track progress, and access a comprehensive exercise database.
Self hosted FLOSS fitness/workout, nutrition and weight tracker
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
[NeurIPS 2025 Spotlight] Reasoning Environments for Reinforcement Learning with Verifiable Rewards
High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
Evaluate and improve models and agents using environments
Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments
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