Mathematical Basics Underlying Big Data Analytics
El-Amin, Mohamed F.
El-Amin, Mohamed F.
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Supervisor
Date
2024-06-30
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Abstract
This chapter provides an introduction to the fundamental mathematical and statistical concepts essential for big data analytics and digital abstraction. Key topics include probability theory, statistical inference, linear algebra, and optimization techniques. Additionally, it explores the foundational elements of data mining and data preprocessing, equipping readers with the tools needed to handle and analyze large datasets effectively. The chapter aims to bridge the gap between theoretical concepts and practical applications, enabling a deeper understanding of how these principles underpin advanced data analytics.
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Book title
Mathematical Modelling for Big Data Analytics