深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

Reinforcement Learning Agents in Javascript (Dynamic Programming, Temporal Difference, Deep Q-Learning, Stochastic/Deterministic Policy Gradients)

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

A deep Q learning demonstration using Google Tensorflow

Stock Trading Bot using Deep Q-Learning

Theano-based implementation of Deep Q-learning

Tensorflow + Keras + OpenAI Gym implementation of 1-step Q Learning from "Asynchronous Methods for Deep Reinforcement Learning"

32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

Deep Q-learning driven stock trader bot

深度学习面试问题 回答对应的DeepLearning中文版页码

This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.

Simple deep Q-learning agent.

A curated list of Monte Carlo tree search papers with implementations.

A PyTorch library for building deep reinforcement learning agents.

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

Playing Flappy Bird Using Deep Reinforcement Learning (Based on Deep Q Learning DQN using Tensorflow)

Deep Q-learning for playing flappy bird game

AI Agent that learns how to play Snake with Deep Q-Learning

tensorflow and theano cnn code for insurance QA(question Answer matching)

Deep Q-learning for playing tetris game

A framework where a deep Q-Learning Reinforcement Learning agent tries to choose the correct traffic light phase at an intersection to maximize traffic efficiency.

DQN Zoo is a collection of reference implementations of reinforcement learning agents developed at DeepMind based on the Deep Q-Network (DQN) agent.

No description available

Deep Q-Learning Network in pytorch (not actively maintained)

RAD: Reinforcement Learning with Augmented Data

This code is for the book

Deep Q-learning (DQN) for Multi-agent Reinforcement Learning (RL)