Exploring Neural Networks with C#

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10a Program
12a
A01=Nabendu Chaki
A01=Rituparna Chaki
A01=Ryszard Tadeusiewicz
Age Group_Uncategorized
Age Group_Uncategorized
Artificial intelligence
Author_Nabendu Chaki
Author_Rituparna Chaki
Author_Ryszard Tadeusiewicz
automatic-update
Brain science
C# programming
Category1=Non-Fiction
Category=UYQN
coefficient
computational neuroscience
COP=United States
Data Set
Delivery_Delivery within 10-20 working days
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Hamming Distance
hidden
Hidden Layer
Hidden Neurons
Hopfield Networks
input
Input Signal Space
Input Signals
Kohonen Network
Language_English
layer
Linear Networks
Linear Neurons
Machine learning
neural network programming experiments
Neural Networks
Neuron Neuron
Neuron Weights
Nonlinear Networks
Nonlinear Neurons
output
Output Layer
Output Signal
PA=Available
pattern recognition methods
Price_€50 to €100
program
PS=Active
recurrent neural models
Self-learning Process
Self-organizing Neural Network
Self-teaching Process
signal
softlaunch
space
supervised learning algorithms
synaptic plasticity
Tele Comm Unications
TNF R1
unsupervised learning techniques
weight
Weight Coefficients
Winner Neuron

Product details

  • ISBN 9781482233391
  • Weight: 578g
  • Dimensions: 178 x 254mm
  • Publication Date: 02 Sep 2014
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
  • Language: English
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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

Ryszard Tadeusiewicz, Rituparna Chaki, Nabendu Chaki

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