A Beginner’s Guide To Machine Learning with Unity
A Beginner’s Guide To Machine Learning with Unity Course
Advanced games AI with genetic algorithms, neural networks & Q-learning in C# and Tensorflow for Unity
The Machine Learning with Unity 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.
Following this, you’ll dive right into creating your very own neural network in C# from scratch. With this basic neural network, you will find out how to train behaviour, capture and use human player data to train an agent and teach a bot to drive. In the same section you’ll have the Q-learning algorithm explained, before integrating it into your own applications.
By this stage, you’ll feel confident with the terminology and techniques used throughout the deep learning community and be ready to tackle Unity’s experimental ML-Agents. Together with Tensorflow, you’ll be throwing agents in the deep-end and reinforcing their knowledge to stay alive in a variety of game environment scenarios.
By the end of the Machine Learning with Unity Course, you’ll have a well-equipped toolset of basic and solid machine learning algorithms and applications, that will see you able to decipher the latest research publications and integrate the latest developments into your work, while keeping abreast of Unity’s ML-Agents as they evolve from experimental to production release.
What you’ll learn in Machine Learning with Unity Course
- Build a genetic algorithm from scratch in C#.
- Build a neural network from scratch in C#.
- Setup and explore the Unity ML-Agents plugin.
- Setup and use Tensorflow to train game characters.
- Apply newfound knowledge of machine learning to integrate contemporary research ideas in the field into their own projects.
- Distill the mathematics and statistic behind machine learning to working program code.
- Use a Proximal Policy Optimisation to train a neural network.
Best Machine Learning Course
Complete A.I. & Machine Learning, Data Science Bootcamp
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Who this Machine Learning course is for:
- Anyone wanting to learn about the potential of machine learning in games.
- Anyone wanting a deeper understanding of the algorithms and theories underlying Unity’s ML-Agents.
- Anyone wanting to know how to setup and work with ML-Agents.
Taught by Penny de Byl and Penny @Holistic3D.com
