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.
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Paperback. Etat : new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783659977282
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Taschenbuch. Etat : 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 120 pp. Englisch. N° de réf. du vendeur 9783659977282
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