*Edited by Marco Antonio Aceves-Fernández*

The interest within the academic community regarding AI has experienced exponential growth in recent years. Several key factors have contributed to this surge in interest. Firstly, the rapid advancements in AI technologies have showcased their potential to revolutionize various fields, such as healthcare, finance, and transportation, sparking curiosity and enthusiasm among researchers and scholars. Secondly, the availability of vast amounts of data and computing power has enabled academics to delve deeper into AI research, exploring complex algorithms and models to tackle real-world problems. Additionally, the interdisciplinary nature of AI has encouraged collaboration among experts from diverse fields like computer science, neuroscience, psychology, and ethics, fostering a rich exchange of ideas and approaches. With contributions from a diverse group of authors, this book offers a multifaceted perspective on machine learning and data mining. Whether you're an experienced researcher or a newcomer, this collection is an essential resource for staying at the forefront of these dynamic and influential disciplines.

*Andries Engelbrecht, Artificial Intelligence Series Editor*

ISBN 978-0-85014-513-7

Machine Learning and Data Mining Annual Volume 2023

ISSN 2633-1403

Published in London, UK © 2023 IntechOpen © your\_photo / iStock

## IntechOpen Series Artificial Intelligence, Volume 21
