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
Deep Q-learning for playing flappy bird game
Deep Q-learning for playing tetris game
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
A PyTorch library for building deep reinforcement learning agents.
RAD: Reinforcement Learning with Augmented Data
A curated list of Monte Carlo tree search papers with implementations.
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.
Train a DQN Agent to play CarRacing 2d using TensorFlow and Keras.
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
DQN, DDDQN, A3C, PPO, Curiosity applied to the game DOOM
A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
Simulation of a self-driving car game using a Deep Q Learning AI
This project is a Stock Trader trained to trade stocks from the S&P 500. It was made using a Deep Q-Learning model and libraries such as TensorFlow, Keras, and OpenAI Gym. It was trained on data from 2006-2016, cross validated on data from 2016-2018, and tested on data from 2018-2021
Exercices and assignments from the Udacity deep reinforcement learning nanodegree
Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework
A tensorflow implementation of hindsight experience replay
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