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Christopher M. Bishop
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Deep Learning: Foundations and Concepts Hardcover – Nov. 2 2023

by Christopher M. Bishop (Author), Hugh Bishop (Author)
4.3 4.3 out of 5 stars 32 ratings
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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 Hinton " With 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
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  1. ISBN-10
    3031454677
  2. ISBN-13
    978-3031454677
  3. Edition
    2024th
  4. Publisher
    Springer Nature
  5. Publication date
    Nov. 2 2023
  6. Language
    English
  7. Dimensions
    19.69 x 3.81 x 26.67 cm
  8. Print length
    649 pages
  9. See all details
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Product description

From the Back Cover

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 Hinton " With 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 inprobability. These concepts are powering current industrial AI systems and are likely to form the basis of further advances towards artificial general intelligence." --  Yoshua Bengio


About the Author

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, a Fellow of the Royal Society of Edinburgh, and a Fellow of the Royal Society of London. He is a keen advocate of public engagement in science, and in 2008 he delivered the prestigious Royal Institution Christmas Lectures, established in 1825 by Michael Faraday, and broadcast on prime-time national television. Chris was a founding member of the UK AI Council and was also appointed to the Prime Minister's Council for Science and Technology.Hugh Bishop  is an Applied Scientist at Wayve, an end-to-end deep learning based autonomous driving company in London, where he designs and trains deep neural networks. Before working at Wayve, he completed his MPhil in Machine Learning and Machine Intelligence in the engineering department at Cambridge University. Hugh also holds an MEng in Computer Science from the University of Durham, where he focused his projects on deep learning. During his studies, he also worked as an intern at FiveAI, another autonomous driving company in the UK, and as a Research Assistant, producing educational interactive iPython notebooks for machine learning courses at Cambridge University.

Product details

  • Publisher ‏ : ‎ Springer Nature; 2024th edition (Nov. 2 2023)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 649 pages
  • ISBN-10 ‏ : ‎ 3031454677
  • ISBN-13 ‏ : ‎ 978-3031454677
  • Item weight ‏ : ‎ 1.44 kg
  • Dimensions ‏ : ‎ 19.69 x 3.81 x 26.67 cm
  • Customer Reviews:
    4.3 4.3 out of 5 stars 32 ratings

About the author

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Christopher M. Bishop

Christopher M. Bishop

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Christopher Michael Bishop (born 7 April 1959) FREng, FRSE, is the Laboratory Director at Microsoft Research Cambridge and professor of Computer Science at the University of Edinburgh and a Fellow of Darwin College, Cambridge. Chris obtained a Bachelor of Arts degree in Physics from St Catherine's College, Oxford, and a PhD in Theoretical Physics from the University of Edinburgh, with a thesis on quantum field theory.

Bio from Wikipedia, the free encyclopedia. Photo by MSRCambridge (Own work) [CC BY-SA 4.0 (http://creativecommons.org/licenses/by-sa/4.0)], via Wikimedia Commons.

Customer reviews

4.3 out of 5 stars
4.3 out of 5
32 global ratings

Top reviews from Canada

Amazon Customer
5.0 out of 5 stars Book quality is improved
Reviewed in Canada on February 23, 2024
Verified Purchase
Received a new copy on Feb 18. Book quality looks fine to me. Loved the content.
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Amazon Customer
4.0 out of 5 stars Quality is meh.
Reviewed in Canada on April 9, 2024
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Hard cover but I expected the paper quality to be smooth like Elements of Statistical Learning...
One person found this helpful
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Top reviews from other countries

Amazon Customer
5.0 out of 5 stars Excellent AI Book
Reviewed in the United States on March 20, 2024
Verified Purchase
An excellent book on neural networks, deep learning and their applications to AI and computer vision. Extremely well organized with well-connected chapters which makes it easy to follow and get the BIG picture, while diving deep into the specifics using elaborate math language and yet not lacking the intuitive approach. The book can be used either as a one stop-reference for subject matter experts, or simply turned into a self-learning or university level textbook. This book also enjoyed the exceptional and unique style of Prof. Christopher M Bishop , who has been a researcher, a public speaker, and a distinguished leader in the field of NN, DL, ML and AI for decades.

Dr. Cazhaow Qazaz
VP of Advanced Analytics and AI
Knowledge Square LLC
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Longo Giuseppe
5.0 out of 5 stars a must
Reviewed in Italy on April 26, 2024
Verified Purchase
I am a professor of Machine learning. My interest in the field arose from reading the first book by Bishop which, in my opinion, was the best book ever written on the topic: clear, exhaustive and inspirational. Unfortunately over the years it became outdated. I was therefore thrilled when I saw this new book and I bought it immediately and read eagerly. It is a masterpiece, even better and more seminal than the previous one. I adopted it for my course on Machine learning. In my opinion it is a must have in the library of every person working in the field: theoretician or practitioner. Thanks Prof. Bishop.
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C. Jaensch
5.0 out of 5 stars Excellent textbook on DL foundations & recent developments
Reviewed in Germany on April 20, 2024
Verified Purchase
A high-quality textbook on deep learning that covers both the fundamentals - including an introduction to probability theory - as well as recent developments, such as Transformer models, autoencoders, or diffusion models. I especially love the targeted use of color to accentuate important points or elements in diagrams.
One can tell that the main author has decades of experience in the field and spent years compiling and writing this book.
Readers should be aware that this is a university-level book that requires at least a calculus and linear algebra background to be able to follow the explanations.
One person found this helpful
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mkj
5.0 out of 5 stars The best Deep Learning book
Reviewed in the United Kingdom on April 15, 2024
Verified Purchase
I have many books on Deep Learning and this is the first that presents the subject in a coherent, well thought out manner.

Each topic is introduced carefully, explained well with relevant pointers to other fields/work. The underlying statistics are clearly presented in a logical manner. The connections between many of the techniques used are clearly exposed.

It's a delight to read and I would recommend it wholeheartedly.
One person found this helpful
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Anier Velasco Sotomayor
5.0 out of 5 stars In my list of top ML books
Reviewed in Spain on March 8, 2024
Verified Purchase
About the shipping and manufacturing: it arrived in perfect conditions, great printing quality.
About the book itself: it's just amazing. I had already read some parts of it in the free online version. Great to finally have the hardcover version.
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Anier Velasco Sotomayor
5.0 out of 5 stars In my list of top ML books
Reviewed in Spain on March 8, 2024
About the shipping and manufacturing: it arrived in perfect conditions, great printing quality.
About the book itself: it's just amazing. I had already read some parts of it in the free online version. Great to finally have the hardcover version.
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One person found this helpful
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