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In this book, you’ll start by exploring backpropagation and unsupervised neural networks with Unity and C#
Description Learn the basic concepts of neural networks and discover different types of neural networks using Unity as your platform.
Then move on to activation functions like sigmoid functions, step functions, etc
The author also explains all the variations of neural networks such as feed-forward, recurrent and radial.
Once you’ve mastered 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, before compiling your project, you’ll define a redistribution using Unity C#
What you’ll learn Discover the concepts of neural networks Work with Unity and C# See the difference between fully connected and convolutional neural networks Learn neural network processing for Windows 10 UWP Who this book is for Game professionals, machine learning, and deep learning enthusiasts