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
Project on design and implement neural network that maximises driving speed of self-driving car through reinforcement learning.
A Deep Reinforcement Learning Framework for Stock Market Trading
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.
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
Simulation of a self-driving car game using a Deep Q Learning AI
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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