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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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)
Self hosted FLOSS fitness/workout, nutrition and weight tracker
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Offline gym log for Android. No account, no ads, no internet.
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
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving