|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/artificial-intelligence-machine-learning-unity3d/
课程评论：没有评论
Coursera 课程总结：Unity3D 人工智能与机器学习速成班 本课程是关于使用 Unity3D 进行机器学习和人工智能的速成班。 **为什么选择 Unity3D 进行人工智能开发？** Unity3D 是训练自定义 AI 的理想环境。例如，训练自动驾驶汽车需要复杂且具有逼真物理交互的环境。从现实世界收集数据效率低下且耗时，而 Unity3D 能够提供逼真的虚拟环境数据。无论您是想为游戏创建 AI 的游戏开发者，还是想尝试机器学习的业余研究者，ML-Agents 工具包都是您创建自定义 AI 的绝佳起点。 **课程内容：** 本课程分为四个主要部分： 1. **引言：** * 快速入门 ML-Agents 工具包。 * 了解如何设置 ML-Agents 工具包（配合 TensorFlow）。 * 什么是神经网络？ * ML-Agents 工具包的关键组件。 2. **3D 滚球 AI：** * 在实践中初步体验 ML-Agents 工具包。 * 学习如何设置环境及训练 AI 所需的所有组件。 3. **AI 学习玩 Flappy Bird：** * 使用强化学习技术，让 AI 学习玩 Flappy Bird。 * 训练后的 AI 将能够在此游戏中获得无限分数。 4. **自动驾驶汽车：** * 涵盖自动驾驶汽车这一著名的人工智能应用。 * 使用模仿学习（Imitation Learning）技术来训练汽车。 * 模仿学习的特点是利用人类玩家的输入来训练神经网络。
This crash-course is about machine Learning & Artificial Intelligence with Unity3D.Why using Unity3D for Artificial Intelligence?Unity3D is the perfect environment in order to train your own AIs. Let's take the example of a Self-driving Car. What you need is complex environments where there are a lots of realistic physical interactions. You could provide these datas from interactions with the real world, but this is extreme inefficient and time consuming.Since games become more and more realistic you can provide these informations from virtual environments. And for that Unity is perfectly positioned.So, no matter if you are a game developer who wants to create AIs for games or if you are a hobby researcher who just want to play with machine Learning … The ML-Agents toolkit is the perfect start in order to create your own AIs.What do we learn in this crash-course?This course is structured into 4 major sections:IntroductionThis section covers everything in order to get a quick start with the ML-Agents Toolkit. You will learn:-Set up of the ML-Agents toolkit with Tensorflow-What is a neural-network?-The Key Components of the Ml-Agents toolkit3D Roller Ball AIThis lecture will give you a first impression of the Ml-Agents toolkit in practice. You will learn how to set up the environment and all the necessary components in order to train the AI.A.I. learns to play Flappy BirdInstead wasting your time with playing this game, we will code our own A.I. that learns to play Flappy Bird by using Reinforcement Learning.After training the AI is able to achieve an unlimited score in this game.Self-driving CarThe Self-driving Car is the probably the most famous example for Artificial Intelligence, so we will cover this as well. To train the Car we will use a technique called Imitation Learning.Imitation Learning is special, because this method uses the inputs from a human Player in order to train the neural network.
