Deep Learning: Foundations and Concepts
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Deep Learning: Foundations and Concepts
This essential book equips readers with a robust foundation for potential future specialization in deep learning.
Deep Learning: Foundations and Concepts
Articolo #: 106458626

Deep Learning: Foundations and Concepts

Articolo #: 106458626

€ 95

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This essential book equips readers with a robust foundation for potential future specialization in deep learning.
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Cosa salta all'occhio

Comprehensive Curriculum
Covers essential deep learning theories and practical applications, making it ideal for beginners and experienced practitioners alike, fostering a solid understanding of key concepts and techniques.
Expert Contributions
Written by leading researchers in the field, ensuring that readers receive cutting-edge insights and knowledge directly from pioneers, enhancing learning through real-world relevance and expertise.
Updated Information
Published at the forefront of AI advancements, this edition incorporates the latest trends and discoveries in deep learning, ensuring readers remain well-informed about current methodologies and technologies.

Dettagli del prodotto

Shop Deep Learning: Foundations and Concepts online at a best price in San Marino. 3031454677
  • This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time.The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study.A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value of techniques rather than on abstract theory. Complex concepts are therefore presented from multiple complementary perspectives including textual descriptions, diagrams, mathematical formulae, and pseudo-code.Chris Bishop is a Technical Fellow at Microsoft and is the Director of Microsoft Research AI4Science. He is a Fellow of Darwin College Cambridge, a Fellow of the Royal Academy of Engineering, and a Fellow of the Royal Society. Hugh Bishop is an Applied Scientist at Wayve, a deep learning autonomous driving company in London, where he designs and trains deep neural networks. He completed his MPhil in Machine Learning and Machine Intelligence at Cambridge University.“Chris Bishop wrote a terrific textbook on neural networks in 1995 and has a deep knowledge of the field and its core ideas. His many years of experience in explaining neural networks have made him extremely skillful at presenting complicated ideas in the simplest possible way and it is a delight to see these skills applied to the revolutionary new developments in the field.” -- Geoffrey HintonWith the recent explosion of deep learning and AI as a research topic, and the quickly growing importance of AI applications, a modern textbook on the topic was badly needed. The New Bishop masterfully fills the gap, covering algorithms for supervised and unsupervised learning, modern deep learning architecture families, as well as how to apply all of this to various application areas. – Yann LeCun“This excellent and very educational book will bring the reader up to date with the main concepts and advances in deep learning with a solid anchoring in probability. Theseconcepts are powering current industrial AI systems and are likely to form the basis of further advances towards artificial general intelligence.” -- Yoshua Bengio
Publisher Springer
Publication date November 2, 2023
Edition 2024th
Language English
Print length 669 pages
ISBN-10 3031454677
ISBN-13 978-3031454677
Item Weight 1.41 Kilograms
Dimensions 7.75 x 1.5 x 10.5 inches (19.7 x 3.8 x 26.7 cm)

A chi è consigliato?

Suitable For
  • Aspiring Data Scientists

    Ideal for individuals pursuing a career in data science, focusing on developing advanced deep learning skills.

  • Academics and Researchers

    Perfect for educators and researchers looking to deepen their understanding of foundational concepts in deep learning.

  • Tech Industry Professionals

    Great for software engineers and AI practitioners seeking to enhance their knowledge of deep learning applications.

Not Suitable For
  • Casual Readers

    Not suitable for those looking for a light read, as it covers complex technical subjects in depth.

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English Edition Christopher M. Bishop Applied Editorial Review

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Deep Learning: Foundations and Concepts is a comprehensive resource for those looking to understand the fundamental principles and applications of deep learning. Weighing 8 pounds, this book packs an abundance of information, making it an essential reference for students and professionals alike. It thoroughly covers various topics, ensuring readers grasp complex concepts and the foundations necessary for advanced study or practical application in the field. This educational resource has received positive accolades for its clarity and depth, helping to demystify the intricate landscape of deep learning, making it accessible for all levels of learners.

Recensioni e valutazioni dei clienti

4.5
263 valutazioni dei clienti
  • 5 stella
    79%
  • 4 stella
    8%
  • 3 stella
    4%
  • 2 stella
    2%
  • 1 stella
    7%

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Vantaggi

  • In-depth coverage of deep learning principles
  • Suitable for both students and professionals
  • Clarifies complex deep learning concepts
  • Comprehensive reference for practical applications
  • Well-structured for easy understanding

Contro

  • Weight may deter portability for some readers

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€ 95

Ordina subito e ricevilo entro Mercoledì, Ottobre 14

Qtà:

Solo 1 articolo rimasto in magazzino.
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  • Over 300,000 available academic books from a leading publisher.
  • Comprehensive introduction to deep learning for both newcomers and experienced individuals.
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  • Well-organized bite-sized chapters for easy understanding and teaching.
  • Includes crucial mathematical foundations and practical techniques.
  • Written by experts in the field for clear and effective learning.

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