AI and Machine Learning for Mechanical and Electrical Engineering 1st Edition

AI and Machine Learning for Mechanical and Electrical Engineering, 1st Edition by Rajasanthosh Kumar, T. (Auerbach Publications, T&F) is a practical, rigorous guide that bridges modern data-driven methods with classical engineering practice. Designed for graduate students, researchers, and practicing engineers, this book explains core AI and machine-learning concepts and demonstrates their direct application to mechanical and electrical engineering challenges.

Key features:
– Clear introduction to machine-learning fundamentals and neural networks, tailored to engineering problems.
– Application-focused chapters on predictive maintenance, control systems, robotics, power systems, signal processing, and system modeling.
– Worked examples and engineering case studies that translate algorithms into real-world workflows.
– Emphasis on model selection, performance evaluation, and interpretability for safety-critical systems.
– Techniques for optimization, fault detection, sensor fusion, and real-time inference in embedded contexts.

Written in a concise, professional style, this first edition balances theory with actionable guidance so readers can implement AI solutions confidently. Whether seeking to modernize design, improve reliability, or enhance system intelligence, this book is a practical resource that equips engineers with the tools to apply AI effectively.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.