Alessandro Migliaccio, Giovanni Iannone

Systems Engineering Neural Networks (eBook, PDF)

• Format: PDF

Produktbeschreibung

SYSTEMS ENGINEERING NEURAL NETWORKS A complete and authoritative discussion of systems engineering and neural networks In Systems Engineering Neural Networks, a team of distinguished researchers deliver a thorough exploration of the fundamental concepts underpinning the creation and improvement of neural networks with a systems engineering mindset. In the book, you'll find a general theoretical discussion of both systems engineering and neural networks accompanied by coverage of relevant and specific topics, from deep learning fundamentals to sport business applications. Readers will discover in-depth examples derived from many years of engineering experience, a comprehensive glossary with links to further reading, and supplementary online content. The authors have also included a variety of applications programmed in both Python 3 and Microsoft Excel. The book provides: * A thorough introduction to neural networks, introduced as key element of complex systems * Practical discussions of systems engineering and forecasting, complexity theory and optimization and how these techniques can be used to support applications outside of the traditional AI domains * Comprehensive explorations of input and output, hidden layers, and bias in neural networks, as well as activation functions, cost functions, and back-propagation * Guidelines for software development incorporating neural networks with a systems engineering methodology Perfect for students and professionals eager to incorporate machine learning techniques into their products and processes, Systems Engineering Neural Networks will also earn a place in the libraries of managers and researchers working in areas involving neural networks.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 240
• Erscheinungstermin: 9. Januar 2023
• Englisch
• ISBN-13: 9781119902003
• Artikelnr.: 67287910

Autorenporträt

Alessandro Migliaccio is a certified systems engineer and member of the INCOSE Artificial Intelligence Working Group. He is a graduate of the Delft University of Technology in Space Engineering, USA, and has second level master's degree in Robotics and Intelligent Systems. Giovanni Iannone is a mechanical engineer and a graduate of the University of Naples Federico II. Second level master's degree in Systems Engineering at Missouri University of Science and Technology, USA. He has been an active member of INCOSE for several years.