9783032209788 - computer engineering machine learning and neural networks: a computer engineering perspective de chen, yiran; li, hai; yang, huanrui (8 resultados)
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This is the first textbook focusing on practicality of machine learning (ML) and deep neural networks (DNN), by introducing methods that enable engineering applications of ML and DNN models. The authors describe many methodologies that are widely used in…designing, training, and deploying of these models and discuss their applicability under various contexts. Coverage begins with the basic knowledge of machine learning and deep neural networks and their applications in solving practical engineering problems. It then proceeds through a series of computer engineering methods commonly used in developing machine learning and deep neural network models. The book also explains how to improve the training and inference performance in terms of model accuracy, size, runtime, etc. by considering various requirements and availability of data in the applications. Techniques that are widely adopted in both industry and academia are discussed. Tutorials and projects designed to practice the introduced techniques are provided using popular development frameworks of machine learning.Emphasizes practice over theoretical foundations, making content accessible to engineering students and engineers;Includes in-depth discussion of popular DNN models and their applications;Discusses engineering methods and tricks widely adopted in practice for using ML and DNN to solve engineering problems.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is the first textbook focusing on practicality of machine learning (ML) and deep neural networks (DNN), by introducing methods that enable engineering applications of ML and DNN models. The authors describe many methodologies that are… widely used in designing, training, and deploying of these models and discuss their applicability under various contexts. Coverage begins with the basic knowledge of machine learning and deep neural networks and their applications in solving practical engineering problems. It then proceeds through a series of computer engineering methods commonly used in developing machine learning and deep neural network models. The book also explains how to improve the training and inference performance in terms of model accuracy, size, runtime, etc. by considering various requirements and availability of data in the applications. Techniques that are widely adopted in both industry and academia are discussed. Tutorials and projects designed to practice the introduced techniques are provided using popular development frameworks of machine learning.Emphasizes practice over theoretical foundations, making content accessible to engineering students and engineers;Includes in-depth discussion of popular DNN models and their applications;Discusses engineering methods and tricks widely adopted in practice for using ML and DNN to solve engineering problems. 312 pp. Englisch.
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This is the first textbook focusing on practicality of machine learning (ML) and deep neural networks (DNN), by introducing methods that enable engineering applications of ML and DNN models. The authors describe many methodologies that are wid…ely used in designing, training, and deploying of these models and discuss their applicability under various contexts. Coverage begins with the basic knowledge of machine learning and deep neural networks and their applications in solving practical engineering problems. It then proceeds through a series of computer engineering methods commonly used in developing machine learning and deep neural network models. The book also explains how to improve the training and inference performance in terms of model accuracy, size, runtime, etc. by considering various requirements and availability of data in the applications. Techniques that are widely adopted in both industry and academia are discussed. Tutorials and projects designed to practice the introduced techniques are provided using popular development frameworks of machine learning. Emphasizes practice over theoretical foundations, making content accessible to engineering students and engineers; Includes indepth discussion of popular DNN models and their applications; Discusses engineering methods and tricks widely adopted in practice for using ML and DNN to solve engineering problems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 336 pp. Englisch.
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Librería: preigu, Osnabrück, Alemaniapreigu
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Buch. Condición: Neu. Computer Engineering Machine Learning and Neural Networks | A Computer Engineering Perspective | Yiran Chen (u. a.) | Buch | xxiv | Englisch | 2026 | Springer | EAN 9783032209788 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[…dot]com | Anbieter: preigu Print on Demand.
