Treffer: Neural Network Programming with Java

About This BookLearn to build amazing projects using neural networks including forecasting the weather and pattern recognitionExplore the Java multi-platform feature to run your personal neural networks everywhereThis step-by-step guide will help you solve real-world problems and links neural network theory to their applicationWho This Book Is ForThis book is for developers or computing students with just basic Java programming knowledge. No previous knowledge of neural networks is required as this book covers the concepts from scratch.What You Will LearnGet to grips with the basics of neural networks and what they are used forDevelop neural networks using hands-on examplesExplore and code the most widely-used learning algorithms to make your neural network learn from most types of dataDiscover the power of a neural network's unsupervised learning process to extract the intrinsic knowledge hidden behind the dataApply the code generated in practical examples, including weather forecasting and pattern recognitionUnderstand how to make the best choice of learning parameters to ensure you have a more effective applicationSelect and split data sets into training, test, and validation, and explore validation strategiesDiscover how to improve and optimize your neural networkIn DetailNeural networks have become a powerful technique to extract useful knowledge from large amounts of raw, seemingly unrelated data. One of the most suitable tools for implementing neural networks is the Java language. Besides being a very popular programming language, there are many API's and packages that help in the development, not mentioning its'write once,run everywhere'portability.This book gives you a complete walkthrough of the process of developing neural networks with Java, from the very basic to the advanced practical examples.First, you will learn the basics of neural networks and their process of learning. We then focus on perceptrons and their features. Next, you will implement self-organizing maps using the concepts you've learned. Furthermore, you will learn about some of the applications such as weather forecasting, disease diagnosis, customer profiling, and optical character recognition (OCR). Finally, you will learn methods to optimize and adapt neural networks in real time.All the examples generated in the book are provided in the form of illustrative source code, which merges object-oriented programming (OOP) concepts and neural network features to enhance your learning experience.