Mathematical Modeling for Big Data Analytics

Mathematical Modeling for Big Data Analytics, 1st Edition, examines mathematical models and algorithms designed for analyzing large and complex datasets. The book outlines analytical frameworks to support structured data processing across modern computing environments.

The theoretical foundations address qualitative and quantitative analytics techniques alongside statistical modeling concepts. Theoretical coverage extends to digital twins and their application in analytical systems. Additional topics include machine learning methods, deep learning architectures, optimization techniques, and data visualization procedures.

The text incorporates ethical considerations and data privacy guidelines into the discussion of analytical workflows. These topics assist smart system developers, data engineers, and statisticians who build and evaluate complex data solutions.