Buch, Englisch, 298 Seiten, Format (B × H): 179 mm x 253 mm, Gewicht: 593 g
Buch, Englisch, 298 Seiten, Format (B × H): 179 mm x 253 mm, Gewicht: 593 g
ISBN: 978-1-4822-3339-1
Verlag: Taylor & Francis
The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations—making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical.
Exploring Neural Networks with C# presents the important properties of neural networks—while keeping the complex mathematics to a minimum. Explaining how to build and use neural networks, it presents complicated information about neural networks structure, functioning, and learning in a manner that is easy to understand.
Taking a "learn by doing" approach, the book is filled with illustrations to guide you through the mystery of neural networks. Examples of experiments are provided in the text to encourage individual research. Online access to C# programs is also provided to help you discover the properties of neural networks.
Following the procedures and using the programs included with the book will allow you to learn how to work with neural networks and evaluate your progress. You can download the programs as both executable applications and C# source code from http://home.agh.edu.pl/~tad//index.php?page=programy&lang=en
Zielgruppe
Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction to Natural and Artificial Neural Networks. A Neural Net Structure. Teaching the networks. Functioning of a Simplest Network. Teaching Simple Linear One Layer Neural Networks. Nonlinear Networks. Backpropagation. Forms of Neural Networks Learning. Self-Learning Neural Networks. Self-Organizing Neural Networks. Recurrent Networks.
