Pinned Repositories
David-Silver-Reinforcement-learning
Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
fahriwm.github.io
larv_datasets
machine-learning-notes
This contains my machine learning notes in latex form
MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
Popular-RL-Algorithms
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
pytorch-DRL
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
RL-Adventure-2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
fahriwm's Repositories
fahriwm/larv_datasets
fahriwm/machine-learning-notes
This contains my machine learning notes in latex form
fahriwm/Popular-RL-Algorithms
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
fahriwm/RL-Adventure-2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
fahriwm/David-Silver-Reinforcement-learning
Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
fahriwm/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
fahriwm/fahriwm.github.io
fahriwm/MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
fahriwm/pytorch-DRL
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.