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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-in-game-design/
课程评论：没有评论
课程名称：游戏设计中的机器学习 课程概述：本课程将通过Unity和Python中的游戏设计向您介绍机器学习的基础知识。首先，您将学习机器学习（ML）和Python的基本概念，包括监督学习、回归和梯度下降等简单的机器学习概念。接下来，您将熟悉强化学习，并尝试理解和应用强化学习、深度神经网络及其他算法的组合，以帮助您的代理在Unity环境中完成复杂和动态的任务。最后，您将学习如何为您的游戏构建动态全功能的强化学习环境和代理，以便后续进行训练。您不仅可以从零开始创建自己的强化学习算法（如Q-learning、SARSA和PPO），还可以根据您环境的需要对其进行定制并在Unity中训练代理。您将获得在机器学习行业中广泛使用的工具和库的经验，例如：Unity3D、Pytorch、mlagents-learn、scikit-learn等。我们希望本课程能够帮助您更好地理解和为开发真正智能的代理和角色做好准备。让我们开始吧！
In this course you will be introduced to the basics of Machine Learning through game design in Unity and Python. First you will be introduced to the very basics of ML and python, you will learn such simple ML concepts such as supervised learning, regression and gradient descent. After that you will get acquainted with reinforcement learning and will try to understand and apply a combination of Reinforcement Learning, Deep Neural Networks and other algorithms in the Unity environment to help your agent accomplish complex and dynamic tasks. Lastly you will learn how to build dynamic full featured RL environments and agents for you to train later in your games. You will not only be able to create your own RL algorithms from scratch (such as Q-learning, SARSA and PPO), but also customize them to fit the needs of your environment and train your agents in Unity. You will gain experience with widely used tools and libraries in the industry of ML, such as: Unity3D, Pytorch, mlagents-learn, scikit-learn and more. We hope that this course will help you to better understand and prepare for your journey of developing truly intelligent agents and characters in your own games. Let's get started!
