Penny de Byl
What if you could build a character that could learn while it played? Think about the types of gameplay you could develop where the enemies started to outsmart the player. This is what machine learning in games is all about. In this course, we will discover the fascinating world of artificial intelligence beyond the simple stuff and examine the increasingly popular domain of machines that learn to think for themselves.
In this course, Penny introduces the popular machine learning techniques of genetic algorithms and neural networks using her internationally acclaimed teaching style and knowledge from a Ph.D in game character AI and over 25 years experience working with games and computer graphics. In addition she’s written two award winning books on games AI and two others best sellers on Unity game development. Throughout the course you will follow along with hands–on workshops designed to teach you about the fundamental machine learning techniques, distilling the mathematics in a way that the topic becomes accessible to the most noob of novices.
Learn how to program and work with:
genetic algorithms
neural networks
human player captured training sets
reinforcement learning
Unity’s ML–Agent plugin
Tensorflow
Contents and Overview
The course starts with a thorough examination of genetic algorithms that will ease you into one of the simplest machine learning techniques that is capable of extraordinary learning. You’ll develop an agent that learns to camouflage, a Flappy Bird inspired application in which the birds learn to make it through a maze and environment–sensing bots that learn to stay on a platform.
Instructor Details
Courses : 16
Specification: A Beginner’s Guide To Machine Learning with Unity
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17 reviews for A Beginner’s Guide To Machine Learning with Unity
Add a review
| Price | $15.99 |
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| Provider | |
| Duration | 13 hours |
| Year | 2021 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$15.99
Dan Williams –
its a good time to learn!
Brooke Hedrick –
Slides almost all entirely washed out in first video at Sydney Unite 2019. The speaker is understand and the subject matter is good. The visuals a very poor.
Santosh SINGH –
Great lesson with examples. with the help of this lesson , i can start to giving new direction to my carrier.
Kusol Kiatsommart –
seems interesting so far. topics so far are pretty simple and are pretty what you learnt by reading wikipedia. I’m hoping to see more hands on stuff in upcoming lectures
Miguel Alberto L rraga Prado –
At first, she wants you to really be interested into machine learning. She teachs about: how and where can apply machine learning in the real world with some examples.
Pascal Guay –
Good enough I just hope that the ML Agents is updated to the latest version.
Adesola Adedewe –
great, i wish i could see more of the screen tho
Imanolgo –
I love genetic algorithms!
Holosim –
The content is important to me right now. Video #6 is hard to see much of the slide content on screen. Based on other videos from this instructor, I’m confident it will get better.
Juan Carlos Granados Cardona –
so far it has filed my expectations
John Kirk –
EXACT FIT to a major part of my project
Harry Snipe –
Initially was frustrated because it’s was extremely slow and repetitive, but slowly it is building up I’m hopefully there will be something useful later on but I would recommend getting a different course if you already have some background knowledge because it assumes absolutely zero knowledge and most of the course is repetition.
Robert Slunjski –
I easily followed all the examples and coding.
Conti Tiziano –
Very clearly exposed and simply developed ’till now. A lot of information received and a lot to discover
Deyvi Damar –
Absolutely
calvin John –
This course is a god send
Brent Williams –
Very informative and helpful