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Description
Learn the basic concepts of neural networks and discover 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#. Then you 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 begin programming Unity with C#. In this chapter, the author discusses building neural networks for unsupervised learning, mapping a neural network to data structures in C#, and replicating a neural network in Unity as a simulation. Finally, you will set up backpropagation using Unity C# before building the project.
What you will learn
Discover the concepts of neural networks
Working with Unity and C#
See the difference between fully connected and convolutional neural networks
Core Neural Network Processing for Windows 10 UWP.
Who is this book for?
Gaming professionals, machine learning and deep learning enthusiasts
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