ISBN13: | 9781032255682 |
ISBN10: | 1032255684 |
Binding: | Paperback |
No. of pages: | 529 pages |
Size: | 234x156 mm |
Language: | English |
Illustrations: | 146 Illustrations, black & white; 64 Halftones, black & white; 82 Line drawings, black & white; 21 Tables, black & white |
700 |
Analysis
Combinatorics and graph theory
Probability and mathematical statistics
Applied mathematics
Engineering in general
Electrical engineering and telecommunications, precision engineering
Civil and construction engineering
Database management softwares
Artificial Intelligence
Product design
Analysis (charity campaign)
Combinatorics and graph theory (charity campaign)
Probability and mathematical statistics (charity campaign)
Applied mathematics (charity campaign)
Engineering in general (charity campaign)
Electrical engineering and telecommunications, precision engineering (charity campaign)
Civil and construction engineering (charity campaign)
Database management softwares (charity campaign)
Artificial Intelligence (charity campaign)
Product design (charity campaign)
Engineering Mathematics and Artificial Intelligence
GBP 61.99
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The fields of Artificial Intelligence and Machine Learning have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between Mathematics and AI/ML and provides an overview of the current research streams.
The fields of Artificial Intelligence (AI) and Machine Learning (ML) have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between mathematics and AI/ML and provides an overview of the current research streams.
Engineering Mathematics and Artificial Intelligence: Foundations, Methods, and Applications discusses the theory behind ML and shows how mathematics can be used in AI. The book illustrates how to improve existing algorithms by using advanced mathematics and offers cutting-edge AI technologies. The book goes on to discuss how ML can support mathematical modeling and how to simulate data by using artificial neural networks. Future integration between ML and complex mathematical techniques is also highlighted within the book.
This book is written for researchers, practitioners, engineers, and AI consultants.