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Neural Networks and Deep Learning: A Textbook
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Neural Networks and Deep Learning: A Textbook

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail. The chapters of this book span three categories:
Detalles del producto
Editorial : Springer-Verlag GmbH; Second Edition 2023 (1 julio 2024)
Idioma : Inglés
Tapa blanda : 556 páginas
ISBN-10 : 3031296443
ISBN-13 : 978-3031296444
Peso del producto : 970 g
Dimensiones : 17.8 x 3 x 25.4 cm
Clasificación en los más vendidos de Amazon: nº143 en Estadística y probabilidad
nº169 en Bases de datos y big data
nº298 en Software y aplicaciones de negocio (Libros)
Opiniones de los clientes: 4,4
25 valoraciones

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