Math and Architectures of Deep Learning (Paperback)
Language: English
Published by Manning Publications, New York, 2024
- Softcover
- New
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
AbeBooks seller since June 22, 2007
Condition: New
£ 116.65
Quantity: 1 available
Add to basketItem description from seller
Paperback. The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually function. Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. Written by deep learning expert Krishnendu Chaudhury, you'll peer inside the black box to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications. about the technology It's important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You'll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you'll be glad you can quickly identify and fix problems. about the book Math and Architectures of Deep Learning sets out the foundations of DL in a way that's both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You'll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. By the time you're done, you'll have a combined theoretical insight and practical skills to identify and implement DL architecture for almost any real-world challenge. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
Seller Inventory # 9781617296482
- Title
- Math and Architectures of Deep Learning (Paperback)
- Author
- Krishnendu Chaudhury
- Publisher
- Manning Publications, New York
- Publication year
- 2024
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1617296481
- ISBN 13
- 9781617296482
about the technology
It's important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You'll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you'll be glad you can quickly identify and fix problems.about the book
Math and Architectures of Deep Learning sets out the foundations of DL in a way that's both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You'll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. By the time you're done, you'll have a combined theoretical insight and practical skills to identify and implement DL architecture for almost any real-world challenge."Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
AussieBookSeller
Truganina, VIC, Australia
AbeBooks seller since June 22, 2007
Shipping rates from Australia to U.S.A.
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