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Table of Contents Book Description Instructor Resources

1st Edition


ENGINEERING MATHEMATICS AND ARTIFICIAL INTELLIGENCE FOUNDATIONS, METHODS, AND
APPLICATIONS

Edited By Herb Kunze, Davide La Torre, Adam Riccoboni, Manuel Ruiz Galán
Copyright 2024

   
 * Hardback
   £135.00
   
 * eBook
   £44.09
   
   
   
   
   
   

ISBN 9781032255675
529 Pages 146 B/W Illustrations
Published July 26, 2023 by CRC Press
Request Inspection Copy

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ISBN 9781003283980
529 Pages 146 B/W Illustrations
Published July 25, 2023 by CRC Press
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DESCRIPTION

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.




TABLE OF CONTENTS

Chapter 1 Multiobjective Optimization: An Overview

Matteo Rocca

Chapter 2 Inverse Problems

Didier Auroux

Chapter 3 Decision Tree for Classification and Forecasting

Mariangela Zenga and Cinzia Colapinto

Chapter 4 A Review of Choice Topics in Quantum Computing and Some Connections
with Machine Learning

Faisal Shah Khan

Chapter 5 Sparse Models for Machine Learning

Jianyi Lin

Chapter 6 Interpretability in Machine Learning

Marco Repetto

Chapter 7 Big Data: Concepts, Techniques, and Considerations

Kate Mobley, Namazbai Ishmakhametov, Jitendra Sai Kota,

and Sherrill Hayes

Chapter 8 A Machine of Many Faces: On the Issue of Interface in Artificial

Intelligence and Tools from User Experience

Stefano Triberti, Maurizio Mauri, and Andrea Gaggioli

Chapter 9 Artificial Intelligence Technologies and Platforms

Muhammad Usman, Abdullah Abonamah, and Marc Poulin

Chapter 10 Artificial Neural Networks

Bryson Boreland, Herb Kunze, and Kimberly M. Levere

Chapter 11 Multicriteria Optimization in Deep Learning

Marco Repetto and Davide La Torre

Chapter 12 Natural Language Processing:

Current Methods and Challenges

Ali Emami

Chapter 13 AI and Imaging in Remote Sensing

Nour Aburaed and Mina Al-Saad

Chapter 14 AI in Agriculture

Marie Kirpach and Adam Riccoboni

Chapter 15 AI and Cancer Imaging

Lars Johannes Isaksson, Stefania Volpe, and Barbara Alicja Jereczek-Fossa

Chapter 16 AI in Ecommerce: From Amazon and TikTok, GPT-3

and LaMDA, to the Metaverse and Beyond

Adam Riccoboni

Chapter 17 The Difficulties of Clinical NLP

Vanessa Klotzman

Chapter 18 Inclusive Green Growth in OECD Countries: Insight

from the Lasso Regularization and Inferential Techniques

Andrea Vezzulli, Isaac K. Ofori, Pamela E. Ofori,

and Emmanuel Y. Gbolonyo

Chapter 19 Quality Assessment of Medical Images

Ilona Anna Urbaniak and Ruben Nandan Pinto

Chapter 20 Securing Machine Learning Models: Notions and Open Issues

Lara Mauri and Ernesto Damiani


EDITOR(S)


BIOGRAPHY



Herb Kunze is a Professor of Mathematics at the University of Guelph, in Guelph,
Ontario, Canada. He received his Ph.D. in Applied Mathematics from the
University of Waterloo in 1997. He has held research funding from the Natural
Sciences and Engineering Research Council (NSERC) throughout his career. Among
his research interests are fractal-based methods in analysis, including a wide
array of both direct and inverse problems; neural networks and artificial
intelligence; mathematical imaging; and qualitative properties of differential
equations. His work combines rigorous theoretical elements with
application-driven considerations. He has over 100 research publications,
generally in high-impact, refereed journals.

Davide La Torre is an Applied Mathematician, Researcher, and University
Professor. Currently he holds the position of Full Professor and Director of the
SKEMA Institute for Artificial Intelligence. He is also the Head of the
(Programme Grande Ecole) Finance and Quants track. His research and teaching
interests include Artificial Intelligence and Machine Learning for Business,
Business and Industrial Analytics, Economic Dynamics, Mathematical and
Statistical Modeling, Operations Management, Operations Research, and Portfolio
Management. He holds a master’s in Applied and Industrial Mathematics (1997,
magna cum laude) and a Ph.D. in Computational Mathematics and Operations
Research (2002) both from the University of Milan, Milan, Italy, and an HDR in
Applied Mathematics from the Université Côte d'Azur (2021). He also holds
professional certificates in Big Data and Analytics (2017), Machine Learning,
and Quantum Computing (2021) from the Massachusetts Institute of Technology,
Cambridge, USA. In the past, he held permanent and visiting university professor
positions in Europe, Canada, the Middle East, Central Asia, and Australia. He
also served as Departmental Chair and Program Head at several universities. He
has more than 150 publications in Scopus, most of them published journals
ranging from Engineering to Business.

Adam Riccoboni is an AI entrepreneur, an author, and the CEO of Critical Future,
a technology and strategy consultancy, trusted by some of the world’s biggest
brands, with a strong record in pioneering AI development. He is an
Award-winning entrepreneur, the founder of high-growth businesses, as featured
in the Financial Times, ESPN, BBC, USA Today. He is also a Guest Lecturer on
Artificial Intelligence at ESCP, UK Business School.

Manuel Ruiz Galán received his Ph. D, from the University of Granada, Spain in
1999. He is a Full Professor in the Mathematics Department at the University of
Granada, Spain with more than 50 research papers and book chapters to his
credit. Dr. Galán has been a member and principal investigator in several
projects with national funds (Spanish Government), particularly on topics
focusing on convex and numerical analysis and their applications. He has acted
as a guest editor for some special issues of the journal Optimization and
Engineering, Mathematical Problems in Engineering, and the Journal of Function
Spaces and Applications. In addition, he is a member of the editorial board of
the publication Minimax Inequalities and its Applications.








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Book Series

This book is included in the following book series:

 * Mathematics and its Applications

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