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

Description Learn the basic concepts of neural networks and explore the different types of neural networks, using Unity as a 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 feed forward, recurrent, and radial.

Once you have 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 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 should read this book Gaming professionals, machine learning and deep learning enthusiasts