Learn the core concepts of neural networks and discover the different types of neural networks 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 on to activation functions, such as sigmoid functions and step functions. 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 and work with Unity and C#.