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Computational Intelligent Techniques welcomes a diverse audience to learn about technological innovation in the mechatronics system. This comprehensive resource is designed to empower readers with the knowledge and skills in the rapidly evolving world of mechatronics. Equipped with knowledge about mechatronic systems, and discussions on cutting-edge technologies in the latest innovations, this book is a learning gateway with tools to design, analyze, and implement mechatronic systems across various industries. Dive into 15 chapters covering the basics of mechatronics, computational intelligence approaches, simulation, and modeling concepts. This book will help research and development departments understand various branches of the engineering design process. Learn about challenges and opportunities in employing these techniques and how mechatronics proposes future research direction to optimize the system. Explore the components, challenges, and benefits of integrating AI in self-driving transportation systems. Lastly, read up on the latest mechatronics in altering current agriculture practices including productivity and sustainability.

The main goal of the book is to provide a comprehensive and accessible guide that empowers readers to understand, apply, and leverage machine learning algorithms and techniques effectively in real-world scenarios. Welcome to the exciting world of machine learning! In recent years, machine learning has rapidly transformed from a niche field within computer science to a fundamental technology shaping various aspects of our lives. Whether you realize it or not, machine learning algorithms are at work behind the scenes, powering recommendation systems, autonomous vehicles, virtual assistants, medical diagnostics, and much more. This book is designed to serve as your comprehensive guide to understanding the principles, algorithms, and applications of machine learning. Whether a student diving into this field for the first time, a seasoned professional looking to broaden your skillset, or an enthusiast eager to explore cutting-edge advancements, this book has something for you. The primary goal of Machine Learning for Industrial Applications is to demystify machine learning and make it accessible to a wide audience. It provides a solid foundation in the fundamental concepts of machine learning, covering both the theoretical underpinnings and practical applications. Whether you're interested in supervised learning, unsupervised learning, reinforcement learning, or innovative techniques like deep learning, you'll find comprehensive coverage here. Throughout the book, a hands-on approach is emphasized. As the best way to learn machine learning is by doing, the book includes numerous examples, exercises, and real-world case studies to reinforce your understanding and practical skills. Audience The book will enjoy a wide readership as it will appeal to all researchers, students, and technology enthusiasts wanting a hands-on guide to the new advances in machine learning.