How to Read this Book
This book is not meant to compete with all the research that made it possible for more and more innovative machines to be developed. Our aim is to simply help the reader put into practice the theories presented in the next pages through the useful applications found in the last part of the text. The content of the book revolves around the lifecycle of a generic system (Figure 1) and addresses how Neural Networks can be called into actions in different phases of a system development.
The text is structured in three parts with the first part focused on systems engineering while the second will present a number of exercises through the use of two programming languages, Python and Visual Basic. This will allow readers of different academic backgrounds to interact with neural networks. Part 3 covers the theory of Neural Networks and its key components.
Chapter 3 is particularly interesting, as we will delve further into the link between the theory of Systems Engineering and Analytic Foresight. An innovative approach will be used to show how to apply neural networks to the sports business. A quirky example is the one related to LEGO® sorting machines - as unusual as it may sound, sorting machines are at the basis of industrial engineering, from automotive applications to food technology.
The journey to understanding neural networks is a fascinating one though it can be perceived as arduous to the inexperienced reader. This topic requires an academic knowledge ...