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Description
Learn the basics of neural networks and explore different types of neural networks using Unity as a platform. In this book, we start by exploring backpropagation and unsupervised neural networks using Unity and C#. It then moves on to activation functions such as sigma functions, step functions, etc. The author also explains all the variations of neural networks such as feedforward, recurrent, and radial.
Once you have learned the basics, you can start programming Unity with C#. In this section, the author discusses building neural networks for unsupervised learning, representing neural networks in C# in terms of data structures, and replicating a neural network as a simulation in the Unity program. Finally, you need to define backpropagation using Unity C# before building your project.
What will you learn?
Explore the concepts behind neural networks
Work 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?
Gamers, machine learning and deep learning enthusiasts

https://jstech.ir/2024/10/07/windows-11-x64-2023-22621-2123-pro-en-us-latest-22h2-activator-torrent/