Springer - Machine Learning in Industry Book

Bridge the gap between theoretical AI and practical application with Machine Learning in Industry (Management and Industrial Engineering) by Springer. This comprehensive resource provides a deep dive into essential machine learning techniques, including artificial neural networks, support vector machines, rough set theory, and deep learning. Designed for both academic researchers and industry professionals, the book explains the specific differences between various techniques and identifies which methods are most suitable for different industrial applications. By understanding these distinctions, users can select the right tools for their specific engineering or management challenges. Beyond theory, this book focuses on real-world utility. It details how machine learning can be applied to solve complex industrial problems through numerous case studies. Whether you are a student in computer science or an engineer looking to implement smart technologies in a production environment, this book serves as a practical guide for using machine learning to solve practical industrial problems.