【2022年】十大強化學習課程熱門排行推薦與優惠精選！

課程介紹

强化学习系列课程主要包括经典算法原理讲解与案例实战两大部分。通俗讲解当下主流强化学习算法思想，结合实例解读算法整理应用流程并结合案例展开代码实战。整体风格通俗易懂，适合准备入门强化学习并进阶提升的同学们。课程目录界面提供全部所需PPT,数据，代码！

…瞭解更多細節

哪些人適合這堂課？

• 人工智能方向的同学们

學習目標

• 掌握强化学习基本思想及其应用领域
• 掌握强化学习主流算法原理
• 掌握强化学习算法数学推导过程及其证明
• 熟练使用PyTorch框架构建强化学习模型
• 熟练使用Openai环境训练强化学习算法模型
• 熟练基本强化学习算法进行实际项目构建
• 掌握DQN，A3C等主流强化学习算法及其数学原理

課程介紹

Interested in the intersection of video games and artificial intelligence? If so, you will love Unity ML-Agents.

Reinforcement Learning with ML-Agents is naturally more intuitive than other machine learning approaches because you can watch your neur

…瞭解更多細節

哪些人適合這堂課？

• Intermediate software developers with an interest in AI in the Unity3d Game Engine
• Developers that want to use Reinforcement Learning, but don’t need to know the low level details
• Game developers interested in adding neural network AI to their games

學習目標

• Learn how to install, run, and train neural networks with Unity ML-Agents
• Train airplane agents to fly with Reinforcement Learning, specifically PPO
• Create a full, playable airplane racing game in Unity with incredibly challenging AI opponents
• Integrate trained neural networks in a game that can be built and deployed cross-platform
• Utilize Machine Learning at a high level (no need to write training algorithms)
• Lots of opportunities to customize the project and make it your own

課程介紹

In this advanced course on deep reinforcement learning, you will learn how to implement policy gradient, actor critic, deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and soft actor critic (SAC) algor

…瞭解更多細節

哪些人適合這堂課？

• Advanced students of artificial intelligence who want to implement state of the art academic research papers

學習目標

• How to code policy gradient methods in PyTorch
• How to code Deep Deterministic Policy Gradients (DDPG) in PyTorch
• How to code Twin Delayed Deep Deterministic Policy Gradients (TD3) in PyTorch
• How to code actor critic algorithms in PyTorch
• How to implement cutting edge artificial intelligence research papers in Python

課程介紹

UPDATE:

All the code and installation instructions have been updated and verified to work with Pytorch 1.6 !!

Artificial Intelligence is dynamically edging its way into our lives. It is already broadly available and we use it – sometimes even no

…瞭解更多細節

哪些人適合這堂課？

• Anyone interested in artificial intelligence, data science, machine learning, deep learning and reinforcement learning.

學習目標

• Reinforcement Learning basics
• Tabular methods
• Bellman equation
• Q Learning
• Deep Reinforcement Learning
• Learning from video input

課程介紹

Welcome to Deep Reinforcement Learning 2.0!

In this course, we will learn and implement a new incredibly smart AI model, called the Twin-Delayed DDPG, which combines state of the art techniques in Artificial Intelligence including continuous Double

…瞭解更多細節

哪些人適合這堂課？

• Data Scientists who want to take their AI Skills to the next level
• AI experts who want to expand on the field of applications
• Engineers who work in technology and automation
• Businessmen and companies who want to get ahead of the game
• Students in tech-related programs who want to pursue a career in Data Science, Machine Learning, or Artificial Intelligence
• Anyone passionate about Artificial Intelligence

學習目標

• Q-Learning
• Deep Q-Learning
• Policy Gradient
• Actor Critic
• Deep Deterministic Policy Gradient (DDPG)
• Twin-Delayed DDPG (TD3)
• The Foundation Techniques of Deep Reinforcement Learning
• How to implement a state of the art AI model that is over performing the most challenging virtual applications

課程介紹

In this course we learn the concepts and fundamentals of reinforcement learning, it’s relation to artificial intelligence and machine learning, and how we can formulate a problem in the context of reinforcement learning and Markov Decision Process. W

…瞭解更多細節

哪些人適合這堂課？

• Machine learning and AI enthusiasts and practitioners, data scientists, machine learning engineers.

學習目標

• The concepts and fundamentals of reinforcement learning
• The main algorithms including Q-Learning, SARSA as well as Deep Q-Learning.
• How to formulate a problem in the context of reinforcement learning and MDP.
• Apply the learned techniques to some hands-on experiments and real world projects.
• Develop artificial intelligence applications using reinforcement learning.

課程介紹

Welcome to Cutting-Edge AI!

This is technically Deep Learning in Python part 11 of my deep learning series, and my 3rd reinforcement learning course.

Deep Reinforcement Learning is actually the combination of 2 topics: Reinforcement Learning and

…瞭解更多細節

哪些人適合這堂課？

• Students and professionals who want to apply Reinforcement Learning to their work and projects
• Anyone who wants to learn cutting-edge Artificial Intelligence and Reinforcement Learning algorithms

學習目標

• Understand a cutting-edge implementation of the A2C algorithm (OpenAI Baselines)
• Understand and implement Evolution Strategies (ES) for AI
• Understand and implement DDPG (Deep Deterministic Policy Gradient)

課程介紹

Join the most comprehensive Reinforcement Learning course on Udemy and learn how to build Amazing Reinforcement Learning Applications!

Do you want to learn how to build cutting edge trading algorithms that leverage todays technology? Or do you want

…瞭解更多細節

哪些人適合這堂課？

• Python Developers
• Coding Enthusiast
• People Interested in Cutting-Edge Technology

學習目標

• Practical Reinforcement Learning
• Master Open AI Gyms
• Flappy Bird Agent
• Mario Agent
• Stocks Agents
• Car Agents
• Space Invaders Agent
• and Much More!!
• Build Reinforcement Learning Agents in Any Environment

課程介紹

This course is all about the application of deep learning and neural networks to reinforcement learning.

If you’ve taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with

…瞭解更多細節

哪些人適合這堂課？

• Professionals and students with strong technical backgrounds who wish to learn state-of-the-art AI techniques

學習目標

• Build various deep learning agents (including DQN and A3C)
• Apply a variety of advanced reinforcement learning algorithms to any problem
• Q-Learning with Deep Neural Networks
• Policy Gradient Methods with Neural Networks
• Reinforcement Learning with RBF Networks
• Use Convolutional Neural Networks with Deep Q-Learning

課程介紹

When people talk about artificial intelligence, they usually don’t mean supervised and unsupervised machine learning.

These tasks are pretty trivial compared to what we think of AIs doing – playing chess and Go, driving cars, and beating video games

…瞭解更多細節

哪些人適合這堂課？

• Anyone who wants to learn about artificial intelligence, data science, machine learning, and deep learning
• Both students and professionals

學習目標

• Apply gradient-based supervised machine learning methods to reinforcement learning
• Understand reinforcement learning on a technical level
• Understand the relationship between reinforcement learning and psychology
• Implement 17 different reinforcement learning algorithms