Overview
- Explains neural network development in the Java environment
- Shows examples of manual network processing
- Discusses solutions to unconventional neural network processing
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Table of contents (12 chapters)
Keywords
About this book
The next big topic discussed in the book is using Java for neural network processing. You will use the Encog Java framework and discover how to do rapid development with Encog, allowing you to create large-scale neural network applications.
The book also discusses the inability of neural networks to approximate complex non-continuous functions, and it introduces the micro-batch method that solves this issue. The step-by-step approach includes plenty of examples, diagrams, and screen shots to help you grasp the concepts quickly and easily.
What You Will Learn
- Prepare your data for many different tasks
- Carry out some unusual neural network tasks
- Create neural network to process non-continuous functions
- Select and improve the development model
Who This Book Is For
Intermediate machine learning and deep learning developers who are interested in switching to Java.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Artificial Neural Networks with Java
Book Subtitle: Tools for Building Neural Network Applications
Authors: Igor Livshin
DOI: https://doi.org/10.1007/978-1-4842-4421-0
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Igor Livshin 2019
eBook ISBN: 978-1-4842-4421-0Published: 12 April 2019
Edition Number: 1
Number of Pages: XIX, 566
Number of Illustrations: 95 b/w illustrations
Topics: Java, Artificial Intelligence, Open Source