Deep Learning Architectures: A Mathematical Approach - Ovidiu Calin
-30% with code BOOKS
Shipping in 12-18 days
30-day return policy
This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former ... Full description
You May Also Like
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-30% with code BOOKS
In stock at our supplier
TOP
How To Think About AI: A Guide For The Perplexed
-30% with code BOOKS
In stock at our supplier
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-30% with code BOOKS
In stock at our supplier
TOP
AI Engineering: Building Applications with Foundation Models
-30% with code BOOKS
In stock at our supplier
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-30% with code BOOKS
In stock at our supplier
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-30% with code BOOKS
In stock at our supplier
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-30% with code BOOKS
In stock at our supplier
TOP
How to Talk to AI: (And How Not To)
-30% with code BOOKS
In stock at our supplier
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-30% with code BOOKS
In stock at our supplier
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-30% with code BOOKS
In stock at our supplier
TOP
The Art of Game Design: A Book of Lenses
-30% with code BOOKS
In stock at our supplier
TOP
How Linux Works: What Every Superuser Should Know
-30% with code BOOKS
In stock at our supplier
TOP
Hands-On Large Language Models: Language Understanding and Generation
Maarten Grootendorst, Jay Alammar
-30% with code BOOKS
In stock at our supplier
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-30% with code BOOKS
In stock at our supplier
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-30% with code BOOKS
In stock at our supplier
TOP
Clean Architecture: A Craftsman's Guide to Software Structure and Design
-30% with code BOOKS
In stock at our supplier
TOP
World of Warcraft Chronicle, Volume 2
-30% with code BOOKS
In stock at our supplier
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-30% with code BOOKS
In stock at our supplier
TOP
Deep Learning: Foundations and Concepts
Christopher M. Bishop, Hugh Bishop
-30% with code BOOKS
In stock at our supplier
Description
This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter. This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.
More Information
| Author | Ovidiu Calin |
|---|---|
| Publisher | Springer Nature Switzerland |
| Series | Springer Series in the Data Sciences |
| Release year | 2021 |
| Cover type | Softcover |
| EAN | 9783030367237 |