Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques. This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.
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Will deliver when available. Publication date 01 Jan 2025
Product Details
Dimensions: 191 x 235mm
Publication Date: 01 Jan 2025
Publisher: Elsevier Science & Technology
Publication City/Country: United States
Language: English
ISBN13: 9780443267352
About
Dr. Passent M El-Kafrawy is a Full Professor in the Department of Math and Computer Science at Effat University Saudi Arabia and a Full Professor of Artificial Intelligence in the Math and Computer Science Department Faculty of Science at Menoufia University Egypt. Dr. El-Kafrawy received her Ph.D. from the University of Connecticut USA in Computer Science and Engineering in the field of Computational Geometry as a branch of Artificial Intelligence. She has taught at Eastern State University Connecticut USA and at Nile University Egypt. She has been an organizing member of conferences including Signal Processing and Information Technology the International Conference of Language Engineering and the International Learning and Technology conference and was co-Editor of the Signal Processing and Information Technology conference proceedings published by Springer. Dr. Mohamed F. El-Amin is a Full Professor of Applied Mathematics and Computational Sciences at Effat University Saudi Arabia. He is also a Visiting Professor at King Abdullah University of Science and Technology Saudi Arabia and is a Full Professor at Aswan University Egypt. As a mathematician he has over 25 years of research experience in the field of computational sciences applied mathematics transport in porous media heat/mass transfer fluid dynamics turbulence reservoir simulation and other aspects of complex systems. After obtaining his PhD in 2001 he held research positions in several universities including South Valley University (Egypt) Stuttgart University (Germany) Kyushu University (Japan) and KAUST. Dr. El-Amin is the editor of several journal special issues and the editor of books including Numerical Modeling of Nanoparticle Transport in Porous Media: MATLAB/Python Approach Elsevier. Dr. El-Amin's key areas of research are computational mathematics and fluid flow modeling with applications in several areas - including but not limited to reservoir simulation transport phenomena nanofluids flow multiphase flow transport in porous media heat and mass transfer hydrogen energy boundary layer flow magnetohydrodynamics and non-Newtonian fluids.