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
منتج #: 81984630

Deep Learning: Foundations and Concepts

منتج #: 81984630

USD 66

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This essential book equips readers with a robust foundation for potential future specialization in deep learning.
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Comprehensive Content
Covers comprehensive foundations and advanced concepts in deep learning, making it suitable for both beginners and experts in the field, ensuring a thorough understanding of this rapidly evolving technology.
Up-to-date Edition
The 2024 edition incorporates the latest research and trends in deep learning, providing readers with current information that reflects the state-of-the-art techniques and methodologies in artificial intelligence.
Practical Applications
Focuses on real-world applications and problem-solving strategies, empowering readers to apply deep learning concepts to diverse fields, enhancing their capabilities in both academic and industry settings.

تفاصيل المنتج

Shop Deep Learning: Foundations and Concepts online at a best price in لبنان. 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 3.1 pounds (1.41 kg)
Dimensions 7.75 x 1.5 x 10.5 inches (19.7 x 3.8 x 26.7 cm)

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Suitable For
  • Students in AI

    Ideal for university students who are studying artificial intelligence and want a solid foundation in deep learning techniques.

  • Industry Professionals

    Great for professionals seeking to enhance their skills in deep learning applications for real-world business problems.

  • Researchers

    Suitable for academic researchers looking for comprehensive theoretical and practical insights into deep learning methodologies.

Not Suitable For
  • Casual Learners

    Not ideal for those looking for a light introductory resource without a rigorous approach to deep learning.

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أسئلة العملاء & الإجابات

  • سؤال: كيف تتسوق Deep Learning: Foundations and Concepts عبر الانترنت من يوباى?

    إجابه: من السهل التسوق في Deep Learning: Foundations and Concepts عبر الإنترنت من يوباي. كل ما عليك فعله هو البحث عن المنتج واختيار طريقة الشحن الخاصة بك أثناء الدفع وسيتم توصيله الى عنوانك
  • سؤال: هل Deep Learning: Foundations and Concepts متوفر للتسوق عبر الإنترنت في Lebanon؟

    إجابه: نعم ، في يوباي Lebanon هذا المنتج متاح لك للتسوق بسعر مناسب. Deep Learning: Foundations and Concepts غير متوفر محليًا ولكن يمكنك الوثوق بنا بخدماتنا للشحن السريع.
  • سؤال: كم من الوقت يستغرق الحصول على المنتج بعد تقديم الطلب؟

    إجابه: يختلف وقت تسليم المنتج الذي طلبته حسب ما طلبته وطريقة الشحن التي اخترتها. يتم ذكر وقت التسليم المقدر أثناء عملية الدفع ، لذا كن مرتاحًا أثناء التسوق.

Intelligence & Semantics Editorial Review

Deep Learning: Foundations and Concepts is a comprehensive resource authored by Christopher M. Bishop and Hugh Bishop, providing an engaging introduction to deep learning that appeals to both beginners and experts. The book stands out with its clear and concise explanations that break down complex concepts, coupled with a strong mathematical foundation. Readers appreciate its up-to-date coverage on advancements, including large transformers and attention mechanisms. While it succeeds in theory, some readers suggest that more hands-on exercises or coding examples could enhance the learning experience. This balance of rigor and clarity makes it a must-have for anyone serious about diving into machine learning.

مراجعات العملاء وتقييماتهم

4.7
267 تقييمات العملاء
  • 5 نجمة
    84%
  • 4 نجمة
    9%
  • 3 نجمة
    5%
  • 2 نجمة
    1%
  • 1 نجمة
    1%

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إيجابيات

  • Clear and concise explanations enhance understanding
  • Strong mathematical foundation for deep learning concepts
  • Covers real-world applications like computer vision
  • Up-to-date on latest advancements in AI
  • Well-organized chapters for easy navigation

سلبيات

  • Could benefit from more practical exercises and coding examples

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