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Neural networks in Unity = C# progra...
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SpringerLink (Online service)
Neural networks in Unity = C# programming for Windows 10 /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Neural networks in Unity/ by Abhishek Nandy, Manisha Biswas.
Reminder of title:
C# programming for Windows 10 /
Author:
Nandy, Abhishek.
other author:
Biswas, Manisha.
Published:
Berkeley, CA :Apress : : 2018.,
Description:
xi, 158 p. :digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Neural networks (Computer science) - Computer programs. -
Online resource:
http://dx.doi.org/10.1007/978-1-4842-3673-4
ISBN:
9781484236734
Neural networks in Unity = C# programming for Windows 10 /
Nandy, Abhishek.
Neural networks in Unity
C# programming for Windows 10 /[electronic resource] :by Abhishek Nandy, Manisha Biswas. - Berkeley, CA :Apress :2018. - xi, 158 p. :digital ;24 cm.
Chapter 1: Core Concepts of Neural Networks -- Chapter 2: Different types of Neural Network -- Chapter 3: Neural Network with Unity -- Chapter 4: Back propagation using Unity -- Chapter 5: Neural Network with Processing and Windows 10 UWP.
Learn the core concepts of neural networks and discover the different types of neural network, using Unity as your platform. In this book you will start by exploring back propagation and unsupervised neural networks with Unity and C#. You'll then move onto activation functions, such as sigmoid functions, step functions, and so on. The author also explains all the variations of neural networks such as feed forward, recurrent, and radial. Once you've gained 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, you'll define back propagation with Unity C#, before compiling your project. You will: 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.
ISBN: 9781484236734
Standard No.: 10.1007/978-1-4842-3673-4doiSubjects--Uniform Titles:
Unity (Electronic resource)
Subjects--Topical Terms:
1207890
Neural networks (Computer science)
--Computer programs.
LC Class. No.: QA76.87 / .N363 2018
Dewey Class. No.: 006.32
Neural networks in Unity = C# programming for Windows 10 /
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Learn the core concepts of neural networks and discover the different types of neural network, using Unity as your platform. In this book you will start by exploring back propagation and unsupervised neural networks with Unity and C#. You'll then move onto activation functions, such as sigmoid functions, step functions, and so on. The author also explains all the variations of neural networks such as feed forward, recurrent, and radial. Once you've gained 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, you'll define back propagation with Unity C#, before compiling your project. You will: 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.
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