---
product_id: 599525501
title: "Deep Learning: Foundations and Concepts"
price: "$184"
currency: NZD
in_stock: true
reviews_count: 12
url: https://www.desertcart.nz/products/599525501-deep-learning-foundations-and-concepts
store_origin: NZ
region: New Zealand
---

# Deep Learning: Foundations and Concepts

**Price:** $184
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- **What is this?** Deep Learning: Foundations and Concepts
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## Description

desertcart.com: Deep Learning: Foundations and Concepts: 9783031454677: Bishop, Christopher M., Bishop, Hugh: Books

Review: 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.
Review: The best book on Deep Learning out there - I'm feeling lucky. This is incredibly, unspeakably, impossibly good book. I've seen the book at the CVPR conference, and hesitated a bit before buying it. $90 after all. But I can't be happier with my purchase. It's simply the best book on Deep Learning - and on Machine Learning - I've seen in 20 years. It gives a very accessible and intuitive introduction in many topics - and, at the same time, preserves the mathematical rigor. For example, the chapter on transformers is the very, very best description of a topic I've seen so far. The book also contains all the info on the ML basics - from multivariate distributions to EM algorithm. Again, it is written very candidly - and, at the same time, preserves theoretical foundations. It is probably slightly less "mathy" than the "Pattern Recognition and Machine Learning" book by Bishop - which is a previous iteration of this text. But much, much more accessible as well. It explains "narrow" topics in plain English. You may read it in this textbook, and then go back to "Pattern Recognition" if you want to get a slightly deeper math for the same topic. Also the book is very recent and covers the hottest and most recent topics, like Diffusion Models. Saved me lots, lots of time and effort - instead of digging through a heap of research papers I can nos just read a chapter from this book. Many thanks to Chris Bishop for writing it!

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #21,655 in Books ( See Top 100 in Books ) #2 in Information Theory #15 in Probability & Statistics (Books) #55 in Artificial Intelligence & Semantics |
| Customer Reviews | 4.5 4.5 out of 5 stars (218) |
| Dimensions  | 7.75 x 1.5 x 10.5 inches |
| Edition  | 2024th |
| ISBN-10  | 3031454677 |
| ISBN-13  | 978-3031454677 |
| Item Weight  | 3.1 pounds |
| Language  | English |
| Print length  | 669 pages |
| Publication date  | November 2, 2023 |
| Publisher  | Springer |

## Images

![Deep Learning: Foundations and Concepts - Image 1](https://m.media-amazon.com/images/I/61ex1w3dnCL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Lots of topics, not very hands-on
*by S***. on November 25, 2024*

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.

### ⭐⭐⭐⭐⭐ The best book on Deep Learning out there
*by R***R on July 11, 2024*

I'm feeling lucky. This is incredibly, unspeakably, impossibly good book. I've seen the book at the CVPR conference, and hesitated a bit before buying it. $90 after all. But I can't be happier with my purchase. It's simply the best book on Deep Learning - and on Machine Learning - I've seen in 20 years. It gives a very accessible and intuitive introduction in many topics - and, at the same time, preserves the mathematical rigor. For example, the chapter on transformers is the very, very best description of a topic I've seen so far. The book also contains all the info on the ML basics - from multivariate distributions to EM algorithm. Again, it is written very candidly - and, at the same time, preserves theoretical foundations. It is probably slightly less "mathy" than the "Pattern Recognition and Machine Learning" book by Bishop - which is a previous iteration of this text. But much, much more accessible as well. It explains "narrow" topics in plain English. You may read it in this textbook, and then go back to "Pattern Recognition" if you want to get a slightly deeper math for the same topic. Also the book is very recent and covers the hottest and most recent topics, like Diffusion Models. Saved me lots, lots of time and effort - instead of digging through a heap of research papers I can nos just read a chapter from this book. Many thanks to Chris Bishop for writing it!

### ⭐⭐⭐⭐⭐ Good for all levels.
*by H***P on October 28, 2025*

Good for beginners and pros. Well written and explained. Up-to-date, but that changes daily, eh? Perfect Gift.

## Frequently Bought Together

- Deep Learning: Foundations and Concepts
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*Store origin: NZ*
*Last updated: 2026-02-23*