Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Idioma: Inglés
Publicado por Springer Nature Switzerland AG, Cham, 2026
ISBN 10: 303200487X ISBN 13: 9783032004871
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 94,38
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Añadir al carritoHardcover. Condición: new. Hardcover. This book is designed for data scientists and machine learning engineers who are keen to dive deep into the complexities of deep learning. The book is particularly useful for professionals in industries where machine learning is applied. It serves as a comprehensive guide for those eager to explore and expand their knowledge in this domain. The book caters to aspirational practitioners, those who are enthusiastic about the field of deep learning in general, being also suitable for engineers and data scientists who are preparing for machine learning interviews. Furthermore, undergraduate and graduate students who possess a basic understanding of machine learning will find this book to be a valuable resource.Learning to create deep learning algorithms from scratch provides a deeper understanding of the underlying principles and mechanics, which can be beneficial in customizing and optimizing models for specific tasks. As such, this book will allow the readers to innovate, creating new architectures or techniques beyond what existing libraries offer. Moreover, it fosters a problem-solving mindset, as the learner navigates through the challenges of implementing complex algorithms. This knowledge will help readers and learners to debug and improve models using pre-built libraries.The author goes beyond just explaining the theory of deep learning, connecting theoretical ideas to their real-world implementations, and dives into how the theoretical aspects of deep learning can be applied in real-world scenarios. Through hands-on examples and case studies, the author demonstrates the application of deep learning principles in solving problems across diverse domains like computer vision, natural language processing, and business analytics. This book is designed for data scientists and machine learning engineers who are keen to dive deep into the complexities of deep learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 250 pages. 9.25x6.10x9.39 inches. In Stock.
EUR 74,89
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is designed for data scientists and machine learning engineers who are keen to dive deep into the complexities of deep learning. The book is particularly useful for professionals in industries where machine learning is applied. It serves as a comprehensive guide for those eager to explore and expand their knowledge in this domain. The book caters to aspirational practitioners, those who are enthusiastic about the field of deep learning in general, being also suitable for engineers and data scientists who are preparing for machine learning interviews. Furthermore, undergraduate and graduate students who possess a basic understanding of machine learning will find this book to be a valuable resource.Learning to create deep learning algorithms from scratch provides a deeper understanding of the underlying principles and mechanics, which can be beneficial in customizing and optimizing models for specific tasks. As such, this book will allow the readers to innovate, creating new architectures or techniques beyond what existing libraries offer. Moreover, it fosters a problem-solving mindset, as the learner navigates through the challenges of implementing complex algorithms. This knowledge will help readers and learners to debug and improve models using pre-built libraries.The author goes beyond just explaining the theory of deep learning, connecting theoretical ideas to their real-world implementations, and dives into how the theoretical aspects of deep learning can be applied in real-world scenarios. Through hands-on examples and case studies, the author demonstrates the application of deep learning principles in solving problems across diverse domains like computer vision, natural language processing, and business analytics.
Idioma: Inglés
Publicado por Springer-Verlag Gmbh Jan 2027, 2027
ISBN 10: 303200487X ISBN 13: 9783032004871
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 74,89
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is designed for data scientists and machine learning engineers who are keen to dive deep into the complexities of deep learning. The book is particularly useful for professionals in industries where machine learning is applied. It serves as a comprehensive guide for those eager to explore and expand their knowledge in this domain. The book caters to aspirational practitioners, those who are enthusiastic about the field of deep learning in general, being also suitable for engineers and data scientists who are preparing for machine learning interviews. Furthermore, undergraduate and graduate students who possess a basic understanding of machine learning will find this book to be a valuable resource.Learning to create deep learning algorithms from scratch provides a deeper understanding of the underlying principles and mechanics, which can be beneficial in customizing and optimizing models for specific tasks. As such, this book will allow the readers to innovate, creating new architectures or techniques beyond what existing libraries offer. Moreover, it fosters a problem-solving mindset, as the learner navigates through the challenges of implementing complex algorithms. This knowledge will help readers and learners to debug and improve models using pre-built libraries.The author goes beyond just explaining the theory of deep learning, connecting theoretical ideas to their real-world implementations, and dives into how the theoretical aspects of deep learning can be applied in real-world scenarios. Through hands-on examples and case studies, the author demonstrates the application of deep learning principles in solving problems across diverse domains like computer vision, natural language processing, and business analytics. 246 pp. Englisch.
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
Idioma: Inglés
Publicado por Springer, Springer Jan 2027, 2027
ISBN 10: 303200487X ISBN 13: 9783032004871
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 74,89
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is designed for data scientists and machine learning engineers who are keen to dive deep into the complexities of deep learning. The book is particularly useful for professionals in industries where machine learning is applied. It serves as a comprehensive guide for those eager to explore and expand their knowledge in this domain. The book caters to aspirational practitioners, those who are enthusiastic about the field of deep learning in general, being also suitable for engineers and data scientists who are preparing for machine learning interviews. Furthermore, undergraduate and graduate students who possess a basic understanding of machine learning will find this book to be a valuable resource.Learning to create deep learning algorithms from scratch provides a deeper understanding of the underlying principles and mechanics, which can be beneficial in customizing and optimizing models for specific tasks. As such, this book will allow the readers to innovate, creating new architectures or techniques beyond what existing libraries offer. Moreover, it fosters a problem-solving mindset, as the learner navigates through the challenges of implementing complex algorithms. This knowledge will help readers and learners to debug and improve models using pre-built libraries.The author goes beyond just explaining the theory of deep learning, connecting theoretical ideas to their real-world implementations, and dives into how the theoretical aspects of deep learning can be applied in real-world scenarios. Through hands-on examples and case studies, the author demonstrates the application of deep learning principles in solving problems across diverse domains like computer vision, natural language processing, and business analytics.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.
Librería: preigu, Osnabrück, Alemania
EUR 66,75
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Añadir al carritoBuch. Condición: Neu. Hands-on Deep Learning | Building Models from Scratch | Tanvir Islam | Buch | xiv | Englisch | 2026 | Springer | EAN 9783032004871 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.