Neural Networks in Unity: C# Programming for Windows 10
Autor Abhishek Nandy, Manisha Biswasen Limba Engleză Paperback – 15 iul 2018
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.
What You'll 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 and deep learning enthusiasts.
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Specificații
ISBN-13: 9781484236727
ISBN-10: 1484236726
Pagini: 145
Ilustrații: XI, 158 p. 107 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.25 kg
Ediția:1st ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
ISBN-10: 1484236726
Pagini: 145
Ilustrații: XI, 158 p. 107 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.25 kg
Ediția:1st ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
Cuprins
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.
Notă biografică
Abhishek Nandy is B.Tech in IT and he is a constant learner.He is Microsoft MVP at Windows Platform,Intel Black belt Developer as well as Intel Software Innovator he has keen interest on AI,IoT and Game Development
Currently serving as a Application Architect in an IT Firm as well as consulting AI,IoT as well doing projects on AI,ML and Deep learning.He also is an AI trainer and driving the technical part of Intel AI Student developer program.He was involved in the first Make in India initiative where he was among top 50 innovators and got trained in IIMA.
Manisha Biswas is BTech in Information Technology and currently working as Data Scientist at Prescriber360,in kolkata, India.She is involved with several areas of technology including Web Development, IoT,Soft Computing and Artificial Intelligence.She is an Intel Software Innovator and was also awarded the SHRI DEWANG MEHTA IT AWARDS 2016 by NASSCOM,a certificate of excellence for top academic scores. She is founder of WOMEN IN TECHNOLOGY,Kolkata a tech community to empower women to learn and explore new technologies.She always like to invent things,create something new,or to invent a new look for the old things. When not in front of my terminal, She is an explorer,a traveller,a foodie, a doodler and a dreamer.She is always very passionate to share her knowledge and ideas with others.She is following her passion and doing the same currently by sharing her experiences to the community so that others can learn and give shape to her ideas in a new way this lead her to become Google Women Techmakers Kolkata Chapter Lead.
Textul de pe ultima copertă
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#
- Seethe difference between fully connected and convolutional neural networks
- Master neural network processing for Windows 10 UWP
Caracteristici
A great way to learn neural networks for the beginner Covers back propagation and unsupervised neural networks with Unity C# Introduces different types of neural networks in Unity