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Artificial Neural Networks with Java - Tools for Building Neural Network Applications (Paperback, 2nd ed.)
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Artificial Neural Networks with Java - Tools for Building Neural Network Applications (Paperback, 2nd ed.)
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Develop neural network applications using the Java environment.
After learning the rules involved in neural network processing,
this second edition shows you how to manually process your first
neural network example. The book covers the internals of front and
back propagation and helps you understand the main principles of
neural network processing. You also will learn how to prepare the
data to be used in neural network development and you will be able
to suggest various techniques of data preparation for many
unconventional tasks. This book discusses the practical aspects of
using Java for neural network processing. You will know how to use
the Encog Java framework for processing large-scale neural network
applications. Also covered is the use of neural networks for
approximation of non-continuous functions. In addition to using
neural networks for regression, this second edition shows you how
to use neural networks for computer vision. It focuses on image
recognition such as the classification of handwritten digits, input
data preparation and conversion, and building the conversion
program. And you will learn about topics related to the
classification of handwritten digits such as network architecture,
program code, programming logic, and execution. The step-by-step
approach taken in the book includes plenty of examples, diagrams,
and screenshots to help you grasp the concepts quickly and easily.
What You Will Learn Use Java for the development of neural network
applications Prepare data for many different tasks Carry out some
unusual neural network processing Use a neural network to process
non-continuous functions Develop a program that recognizes
handwritten digits Who This Book Is For Intermediate machine
learning and deep learning developers who are interested in
switching to Java
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