Isbn: 9783659977282 - machine learning applications in mechanical engineering

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine Learning Applications in Mechanical Engineering is a comprehensive guide exploring the transformative role of machine learning (ML) across key domains in mechanical engineering. It combines theoretical insights and practical applications to address design optimization, predictive maintenance, robotics, material discovery, and energy systems, making it invaluable for students, researchers, and professionals.The book begins with an introduction to ML, highlighting its relevance and challenges in mechanical engineering. It explores learning models like supervised, unsupervised, and semi-supervised learning, alongside neural networks, Bayesian techniques, and support vector machines. Chapters delve into ML-driven innovations in material design, predictive maintenance, and meta surface optimization, showcasing tools like deep learning and generative models.This book equips readers to leverage ML in tackling engineering challenges, paving the way for intelligent, data-driven solutions in mechanical engineering.…

Machine Learning Applications in Mechanical Engineering

Jiyaul Mustafa

Lingua: Inglese

Editore: LAP LAMBERT Academic Publishing Nov 2024, 2024

3659977284 / 9783659977282

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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Machine Learning Applications in Mechanical Engineering is a comprehensive guide exploring the transformative role of machine learning (ML) across key domains in mechanical engineering. It combines theoretical insights and practical applications to address design optimization, predictive maintenance, robotics, material discovery, and energy systems, making it invaluable for students, researchers, and professionals.The book begins with an introduction to ML, highlighting its relevance and challenges in mechanical engineering. It explores learning models like supervised, unsupervised, and semi-supervised learning, alongside neural networks, Bayesian techniques, and support vector machines. Chapters delve into ML-driven innovations in material design, predictive maintenance, and meta surface optimization, showcasing tools like deep learning and generative models.This book equips readers to leverage ML in tackling engineering challenges, paving the way for intelligent, data-driven solutions in mechanical engineering.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch.…

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Machine Learning Applications in Mechanical Engineering

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Machine Learning Applications in Mechanical Engineering

Machine Learning Applications in Mechanical Engineering

Machine Learning Applications in Mechanical Engineering

Machine Learning Applications in Mechanical Engineering

Machine Learning Applications in Mechanical Engineering