--- product_id: 592937482 title: "Springer Deep Learning: Foundations and Concepts" price: "€ 209.34" currency: EUR in_stock: true reviews_count: 5 url: https://www.desertcart.at/products/592937482-springer-deep-learning-foundations-and-concepts store_origin: AT region: Austria --- # Springer Deep Learning: Foundations and Concepts **Price:** € 209.34 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Springer Deep Learning: Foundations and Concepts - **How much does it cost?** € 209.34 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.at](https://www.desertcart.at/products/592937482-springer-deep-learning-foundations-and-concepts) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description Buy Springer Deep Learning: Foundations and Concepts by Bishop, Christopher M., Bishop, Hugh online on desertcart.ae at best prices. ✓ Fast and free shipping ✓ free returns ✓ cash on delivery available on eligible purchase. Review: 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: Great book! Book is available online to read, but it makes it difficult to study and learn from. Arrived on time in pristine condition. ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | #41,615 in Books ( See Top 100 in Books ) #14 in Programming Algorithms #56 in Databases & Big Data #87 in Applied Mathematics | | Customer reviews | 4.4 4.4 out of 5 stars (228) | | Dimensions | 19.69 x 3.81 x 26.67 cm | | Edition | 2024th | | ISBN-10 | 3031454677 | | ISBN-13 | 978-3031454677 | | Item weight | 1.41 Kilograms | | Language | English | | Print length | 669 pages | | Publication date | 2 November 2023 | | Publisher | Springer | ## Images ![Springer Deep Learning: Foundations and Concepts - Image 1](https://m.media-amazon.com/images/I/61ex1w3dnCL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ Review *by S***. on 25 November 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. ### ⭐⭐⭐⭐⭐ Review *by A***N on 20 February 2026* Great book! Book is available online to read, but it makes it difficult to study and learn from. Arrived on time in pristine condition. ### ⭐⭐⭐⭐⭐ Review *by I***N on 9 November 2024* 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). ## Frequently Bought Together - Deep Learning: Foundations and Concepts - Understanding Deep Learning - Build a Large Language Model (From Scratch) --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.at/products/592937482-springer-deep-learning-foundations-and-concepts](https://www.desertcart.at/products/592937482-springer-deep-learning-foundations-and-concepts) --- *Product available on Desertcart Austria* *Store origin: AT* *Last updated: 2026-04-30*