Introduction to Neural Networks with Java

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Unfortunately, the book delivers on neither of these intentions particularly well. I have only a very basic background in neural networking see "Neural Networks: A Comprehensive Foundation - 2nd edition" by Haykin and was expecting Mr. Heaton to provide some theoretical explanation of why various network architectures are relevant to particular types of problems, how training algorithms differ from each other and why this is important Instead, there's a brief chapter on matrix math, which in my opinion was not especially clear, and an occasional ball and stick diagram and almost no theoretical explanation of where any of it comes from or why it's important.

I learned next to nothing about neural networking from this book, and what I may have learned is probably available on wikipedia in the space of a few paragraphs. I could resign myself to the lack of neural networking explanation if the book instead presented a robust discussion of Java design as applied to neural networking architectures and algorithms.

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But, alas, this is not to be found either. The Java code is presented with no insight into the author's design decisions and therefore offers little in the way of educational material.

Unless you are truly a Java novice, the code in the book will seem obvious and underwhelming. While it's apparent that basic neural networks can be constructed with relatively simple code, the author's failure to provide any explanation of code design or to frame the code within the context of a larger neural networking library perhaps results in the Java coding how-to portion of the book failing to deliver as well.

In short, I read the first 6 chapters of this book and decided not to waste any further time with it.

If you want to understand neural networks, you won't find that here. If you want to learn to write Java code to build neural networks, you won't find that here either. You'll find code that the author has already written that you can use, but there won't be much educational value in it. The book truly is more of a user's manual or technical documentation for the author's neural networking Java classes and not much more.

Perhaps that is useful if you want something simple you can drop into a project and run with. My suggestion to those who wish to learn and understand how to build neural networks in Java is to learn a little about the networks themselves then hack out some Java code yourself. You'll understand what the code means and be in a much better position to extend that code.

An Introduction to Neural Networks in Java | Neural Network Structure | InformIT

And you'll definitely learn something along the way, which, unfortunately, I did not while reading this book. See all 6 reviews. Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers. Learn more about Amazon Giveaway. Introduction to Neural Networks for Java, 2nd Edition. Set up a giveaway.

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Get to Know Us. English Choose a language for shopping. Amazon Music Stream millions of songs. Amazon Drive Cloud storage from Amazon. Alexa Actionable Analytics for the Web. AmazonGlobal Ship Orders Internationally. For this article, we will teach the neural network to recognize only a very simple pattern. It is possible to use this same neural network class to learn much more complex patterns.

Introduction to Neural Networks with Java

The code presented here is reusable and can be used for any neural network that involves a single level of neurons. The pattern that we will teach the neural network to recognize is the XOR operator. A neural network is composed of layers of neurons. The most common neural networks have an input, output, and one or more hidden layers.

Neural Network Structure

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