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Reinforcement-learning-with-tensorflow

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

TutorialsML/AI fundamentalsPython
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创建于 2017-05-06 · 更新于 2026-10-15 · 今日第 7073 名
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MorvanZhou/Reinforcement-learning-with-tensorflow 排名第 7,073,有 9,523 个星标。

同类别比较

MorvanZhou/Reinforcement-learning-with-tensorflow 排名第 7,073,此处有 8 个同类条目;huseinzol05/Stock-Prediction-Models 排名第 7,074。

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关键参数与规格
关键参数与规格
参数值
语言Python
类别Tutorials
子类别ML/AI fundamentals
关键词RL
星标数9,523
分叉数4,970
贡献者7
创建日期2017-05-06
更新日期2026-10-15
1 天星标数0
7 天星标数2
排名7,073
上次排名7,251
排名变化178
7 天星标排名7,485
上次 7 天星标排名9,020
7 天星标排名变化1,535
总星标排名1,520
上次总星标排名1,518
总星标排名变化-2
国家China
README 摘录

Reinforcement Learning Methods and Tutorials In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years. **If you speak Chinese, visit 莫烦 Python or my Youtube channel for more. ** **As many requests about making these tutorials available in English, please find them in this playlist:** ( Table of Contents Tutorials Some of my experiments Some RL Networks Deep Q Network Double DQN Dueling DQN Actor Critic Deep Deterministic Policy Gradient A3C Proximal

Policy Optimization (PPO) Curiosity Model Donation *If this does help you, please consider donating to support me for better tutorials. Any contribution is greatly appreciated!

常见问题

记录了多少星标和分叉?

MorvanZhou/Reinforcement-learning-with-tensorflow 有 9,523 个星标和 4,970 个分叉。

仓库排名是多少?

MorvanZhou/Reinforcement-learning-with-tensorflow 排名第 7,073。

记录的语言和类别是什么?

MorvanZhou/Reinforcement-learning-with-tensorflow 有 9,523 个星标,语言为 Python,类别为 Tutorials。

哪个仓库排名最接近?

MorvanZhou/Reinforcement-learning-with-tensorflow 与 huseinzol05/Stock-Prediction-Models 比较,后者排名第 7,074,有 9,504 个星标。

README
[![](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/blob/master/RL_cover.jpg)](https://www.youtube.com/watch?v=pieI7rOXELI&list=PLXO45tsB95cIplu-fLMpUEEZTwrDNh6Ba)

Reinforcement Learning Methods and Tutorials

In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.

If you speak Chinese, visit 莫烦 Python or my Youtube channel for more.

As many requests about making these tutorials available in English, please find them in this playlist: (https://www.youtube.com/playlist?list=PLXO45tsB95cIplu-fLMpUEEZTwrDNh6Ba)

Table of Contents

Some RL Networks

Deep Q Network

Double DQN

Dueling DQN

Actor Critic

Deep Deterministic Policy Gradient

A3C

Proximal Policy Optimization (PPO)

Curiosity Model

Donation

If this does help you, please consider donating to support me for better tutorials. Any contribution is greatly appreciated!

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