Neural Networks in Unity

Neural Networks in Unity Abhishek Nandy, Manisha Biswas
Learn the core concepts of neural networks and discover the different types of neural network, using Unity as your platform. In this book you will start by exploring back propagation and unsupervised neural networks with Unity and C#. You’ll then move onto activation functions, such as sigmoid functions, step functions, and so on. The author also explains all the variations of neural networks such as feed forward, recurrent, and radial.
Once you’ve gained the basics, you’ll start programming Unity with C#. In this section the author discusses constructing neural networks for unsupervised learning, representing a neural network in terms of data structures in C#, and replicating a neural network in Unity as a simulation. Finally, you’ll define back propagation with Unity C#, before compiling your project.
What You’ll Learn
Discover the concepts behind neural networks
Work with Unity and C# See the difference between fully connected and convolutional neural networks
Master neural network processing for Windows 10 UWP
Who This Book Is For
Gaming professionals, machine learning and deep learning enthusiasts.
Categories:
Computers – Operating Systems
Year:
2018
Edition:
1st ed.
Publisher:
Apress
Language:
english
Pages:
166
ISBN 10:
1484236734
ISBN 13:
9781484236734
File:
14 MB