Artificial Neural Networks with Java
Tools for Building Neural Network Applications
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Beschreibung
Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of neural network processing. Artificial Neural Networks with Java also teaches you how to prepare the data to be used in neural network development and suggests various techniques of data preparation for many unconventional tasks.
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.
You will:
- 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
Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of neural network processing. Artificial Neural Networks with Java also teaches you how to prepare the data to be used in neural network development and suggests various techniques of data preparation for many unconventional tasks.
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.
Explains neural network development in the Java environment
Shows examples of manual network processing
Discusses solutions to unconventional neural network processing
Autor*in
Igor Livshin
Themen in »Artificial Neural Networks with Java«
Artificial Intelligence Neural Networks Java Neural Network Processing Encog Data Preparation Neural Network Architecture AI deep learning computing methodology programming source code