Description Learn the basic concepts of neural networks and discover the different types of neural networks using Unity as your platform. In this book, you'll start by exploring backpropagation and unsupervised neural networks with Unity and C#. You will then move on to activation functions such as sigmoid functions, step functions, etc. The author also explains all variations of neural networks such as feed forward, recurrent and radial. Once you've got the basics down, you'll start programming Unity with C#. In this section, the author discusses building 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 will define backpropagation with Unity C# before compiling your project. What you will learn Discover the concepts behind neural networks Work with Unity and C# See the difference between fully connected and convolutional neural networks Main Neural Network Processing for Windows 10 UWP Who is this book for? Gaming professionals, machine learning and deep learning enthusiasts