Deep Learning: Foundations and Concepts
Product ID: 598276005
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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 Review: The best book to learn modern deep learning! (INDIAN CUSTOMERS BEWARE of pirated copies) - Deep Learning: Foundations and Concepts is the best book to learn fundamentals of Neural Networks and Deep Learning. I have tried reading several other new books, but this is the best of them all, especially if you want to learn about Transformers. The Transformers chapter in this books goes step by step, builds concepts one by one, and completely demystifies how the Large Language Model technology works. If you want to really learn how LLMs work, and understand each important bit of the entire structure well, go for Christopher Bishop's book. The math of the Transformers chapter is not heavy, which makes the introduction easier to understand for many. One of the biggest advantages of this book is that the author tries to build an intuition for the reader, which is very helpful if you want to be a researcher and go deep into the subject and explore new areas on your own. Highly recommended book. INDIAN CUSTOMERS BEWARE of pirated copies: desertcart India sellers are selling pirated copies of this book. Do not buy pirated copies from desertcart India sellers. Buy directly from Springer Online store. Pirated copies have low quality binding, and it will come out very soon. Very disappointed to find that desertcart India seller ("shree Sai Fashion") sold me a pirated copy of the book. Review: Better then prml - Whhoowww hooo!! I was eagerly waiting to read this book. Thank you desertcart.
| Best Sellers Rank | #31,316 in Books ( See Top 100 in Books ) #89 in Artificial Intelligence |
| Customer Reviews | 4.3 out of 5 stars 240 Reviews |
N**L
The best book to learn modern deep learning! (INDIAN CUSTOMERS BEWARE of pirated copies)
Deep Learning: Foundations and Concepts is the best book to learn fundamentals of Neural Networks and Deep Learning. I have tried reading several other new books, but this is the best of them all, especially if you want to learn about Transformers. The Transformers chapter in this books goes step by step, builds concepts one by one, and completely demystifies how the Large Language Model technology works. If you want to really learn how LLMs work, and understand each important bit of the entire structure well, go for Christopher Bishop's book. The math of the Transformers chapter is not heavy, which makes the introduction easier to understand for many. One of the biggest advantages of this book is that the author tries to build an intuition for the reader, which is very helpful if you want to be a researcher and go deep into the subject and explore new areas on your own. Highly recommended book. INDIAN CUSTOMERS BEWARE of pirated copies: Amazon India sellers are selling pirated copies of this book. Do not buy pirated copies from Amazon India sellers. Buy directly from Springer Online store. Pirated copies have low quality binding, and it will come out very soon. Very disappointed to find that Amazon India seller ("shree Sai Fashion") sold me a pirated copy of the book.
R**A
Better then prml
Whhoowww hooo!! I was eagerly waiting to read this book. Thank you amazon.
S**H
Very Good Content
It covers required mathematical details for deep learning.
A**E
Great book for advancing in this field of generative AI and deep learning.
This is one of the top 5 books for students to have. For me, this a direct continuation to the legendary goodfellow's 2016 book and a proper introduction for beginners as well (before chapter 10). The approach to explaining generative models that this book has taken is quite intuitive and has made learning quite easy.
P**H
Horrible binding
The binding of this book is absolutely terrible. I strongly advise against purchasing it from this seller. My first copy fell apart within weeks, and after requesting a replacement, I received another copy with the same issue - pages separating like a deck of flashcards. This is clearly a recurring problem. If you’re considering buying this book, check it in person at a store to ensure the quality. Save yourself the frustration - don’t buy from here! (Attached photos for reference.)
A**K
Deep learning
The book met the expectation and contained all the topics I was looking for. The binding of the book is really good and is better than the product available on Flipkart
M**T
As usual again a great book by Bishop !
Great book if you have the patience to read each page by page. Readers should not even skip a single paragraph. Once that is followed, the result would be mind-blowing. You will end up having meaty concepts in Applied ML & Stats. And this book is not at all for casual reading. A serious approach with a pen & notebook will help, otherwise the content will appear very dull.
Q**Y
Pages are coming out of the binding
Though I loved the content of this book, it has a very poor binding. I am looking for some book binders in my locality to get all the pages fixed. Page quality is good and as expected though.
S**.
Lots of topics, not very hands-on
Deep Learning: Foundations and Concepts by Christopher M. Bishop and Hugh Bishop is a comprehensive and accessible introduction to the world of deep learning. The book effectively balances theoretical depth with practical insights, making it suitable for both beginners and experienced practitioners. Key strengths of the book include: Clear and concise explanations: The authors do an excellent job of breaking down complex concepts into easily understandable terms, making the material accessible to a wide range of readers. Strong mathematical foundation: The book provides a solid mathematical foundation for understanding deep learning algorithms, but it avoids excessive mathematical formalism, making it engaging for readers with varying levels of mathematical background. Practical applications: The book covers a wide range of real-world applications, such as computer vision, natural language processing, and speech recognition, providing practical examples to illustrate the concepts. Up-to-date coverage: The book covers the latest advancements in deep learning, including attention mechanisms, transformer models, and generative adversarial networks. Potential areas for improvement: More hands-on exercises: While the book provides theoretical explanations, it could benefit from more practical exercises and coding examples to reinforce learning. Deeper dives into specific topics: For readers who want to delve deeper into specific topics, such as reinforcement learning or unsupervised learning, additional resources or references could be helpful. Overall, Deep Learning: Foundations and Concepts is an excellent resource for anyone interested in learning about deep learning. It provides a clear and comprehensive introduction to the field, making it a valuable addition to any machine learning enthusiast's library.
A**N
Great book!
Great book! Book is available online to read, but it makes it difficult to study and learn from. Arrived on time in pristine condition.
I**N
If you only choose one deep learning book, this is it.
This book continues the Bishops' tradition of writing accessible and clear yet rigorous treatment of machine learning/deep learning content. The transformers and diffusion chapters fantastic, and exactly what I was looking for. The authors share solutions to end of chapter questions which is perfect for students and self- learners alike. You can scan the book on their site, but this one is a *must have* for your bookshelf. If you need any more reason to purchase this book immediately, LeCun, Bengio and Hinton all wrote highly supportive reviews (see site).
H**N
iyi bir textbook
Goodfellow'un 2016 basimli DL kitabi uzerine alanda cok fazla gelisme oldu. DL alaninda teori-matematik bilgileri tazelemek-guncellemek icin iyi bir textbook.
C**2
Erfüllt meine Erwartungen bis auf die Verpackung.
Sehr schönes Buch. Klar und übersichtlich, guter Druck auf gutem Papier. Guter Aufbau des Stoffes. Da ich erst begonnen habe, das Buch durchzuarbeiten, kann ich zu den Details noch nicht all zu viel sagen. Das Schmökern lässt jedoch vermuten, dass dieses Buch die wesentlichen Aspekte des 'Deep Learning' sehr gut zu vermitteln weiss. Das Buch kam aus Indien, Verpackung ungenügend wie immer bei Amazon in der letzten Zeit, daher beschädigte Ecken. Sehr schade! Amazon sollte hinsichtlich Verpackung wirklich eine Anstrengung unternehmen, auch wenn das geringfügig mehr für den Kunden kostet.
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