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.
