Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
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Updated
May 2, 2023 - Jupyter Notebook
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
Stock Trading Bot using Deep Q-Learning
A PyTorch library for building deep reinforcement learning agents.
A curated list of Monte Carlo tree search papers with implementations.
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
Deep Q-learning for playing flappy bird game
Deep Q-learning for playing tetris game
RAD: Reinforcement Learning with Augmented Data
Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning
A Deep Reinforcement Learning Framework for Stock Market Trading
Project on design and implement neural network that maximises driving speed of self-driving car through reinforcement learning.
Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Train a DQN Agent to play CarRacing 2d using TensorFlow and Keras.
DQN, DDDQN, A3C, PPO, Curiosity applied to the game DOOM
PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQN
A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
Using deep reinforcement learning to tackle the game 2048.
Reinforcement Learning environment for Elixir
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