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Description
Learn the basics of neural networks and discover the different types of neural networks, using Unity as a platform. In this book, you will start by exploring backpropagation and unsupervised neural networks using Unity and C#. 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 will 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
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