Artificial Intelligence For Data Science

Alloghani, Mohamed

ISBN 10: 3030922472 / ISBN 13: 9783030922474

Edité par Springer, 2023

N° de réf. du vendeur V9783030922474

Synopsis :

This book provides valuable information on effective, state-of-the-art techniques and approaches for governments, students, researchers, practitioners, entrepreneurs and teachers in the field of artificial intelligence (AI). The book explains the data and AI, types and properties of data, the relation between AI algorithms and data, what makes data AI ready, steps of data pre-processing, data quality, data storage and data platforms. Therefore, this book will be interested by AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.

À propos de l?auteur:

Mohamed Alloghani is an advisor (Research and Capacity Building) for the UAE's Minister of State for Artificial Intelligence, Digital Economy and Remote Work Applications at UAE Prime Minister's Office. Dr. Alloghani is the first UAE national graduated with a Doctor of Philosophy - PhD focused on Artificial Intelligence from Liverpool John Moores University. Dr. Alloghani has 14 years of working experience in various public organizations such as oil and gas industry, judicial/ public prosecution, and healthcare sector. As part of his work experience and working on strategic national missions, Dr. Alloghani was delegated by Minister of State for Artificial Intelligence and appointed by the Director-General of UNESCO to represent UAE in the Ad Hoc Expert Group (AHEG), in March 2020. The group comprised of 24 renowned specialists selected from the world. He was the head of UAE delegation G20 Digital Economy Task Force (DETF) in Feb 2020. Dr. Alloghnai research interest's focuseson artificial intelligence, research and development, software engineering and project management. He authored and co-authored several scientific papers in regional and international in refereed high-impact journals and conferences. He published 51 peer-reviewed scientific papers.

Christopher P. Thron is associate professor of mathematics at Texas A&M University-Central Texas. Previously he was a communications systems engineer at NEC, Motorola, and Freescale Semiconductor. He has also held visiting positions at multiple universities in Cameroon, China, Nigeria, and Sudan. His teaching and research have been supported by grants from the U.S. Fulbright Program, the International Mathematicians Union, and the U.S. Air Force. His research focuses on the application of computational mathematics and statistics (including machine learning) to various fields such as algorithm design, wireless communications systems, epidemiology, social sciences, and operations research. He has nine patents granted and 40+ publications in refereed journals. He has also presented conference talks and workshops in computational mathematics across the African continent.

Saad Subair was born on the banks of the river Nile, a few kilometers away from the capital Khartoum He is a Professor of Bioinformatics and Computer Science at the College of Computer Studies, International University of Africa (IUA), Khartoum, Sudan. Prof. Subair obtained a BSc from the University of Khartoum, PGD, MSc (Computer Science) and PhD (Bioinformatics) from UTM, Malaysia, and an MSc in Genetics from UPM, Malaysia He is an author and/or contributing author to several books, articles, and scientific papers published in USA, Germany, Malaysia, India, and Arabia. He has been Keynote Speaker in numerous regional conferences. Prof. Subair is a member of scientific and academic committees in multiple universities in Sudan and Arabia Prof Subair is also member of high committees in the Ministry of Higher Education, Sudan. Prof Subair has trained hundreds of students in the fields of machine learning and bioinformatics, and has supervised and/or advised several research students who have achieved further successes in the UK and USA.

Détails bibliographiques

Titre : Artificial Intelligence For Data Science
Éditeur : Springer
Date d'édition : 2023
Reliure : Couverture souple
Etat : New