Publisher's Synopsis
This book provides insights into how machine learning can enhance laser technology, focusing on possibilities rather than detailed coding instructions. It's not strictly a technical book, yet it isn't entirely non-technical either; readers with a basic understanding of lasers, machine learning, and data systems will find it easier to engage with the content. The book explores machine learning applications in various laser fields, including medical treatments, laser material processing, cutting, and welding. It presents case studies showing how machine learning could improve laser operations, diagnostics, and predictive maintenance.
Key applications, like Ti-sapphire-based Chirped Pulse Amplification (CPA) systems, illustrate how machine learning might enhance pulse stability and efficiency. The book emphasizes conceptual understanding with block diagrams and flowcharts, presenting possibilities for integrating machine learning into laser systems rather than promising definitive solutions. This approach is ideal for readers interested in the future of laser technology, offering ideas for potential advancements rather than step-by-step implementations.
