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In this book, you will start by exploring backpropagation and unsupervised neural networks using Unity and C#

Description Learn the basics of neural networks and discover the different types of neural networks, using Unity as your platform.

You will then move on to activation functions such as sigmoid functions, step functions, etc

The author also explains all the variations of neural networks such as feedforward, recurrent, and radial.

Once you have acquired the basics, you will 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 using 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 enthusiasts, and deep learning enthusiasts