Data Analysis in the AI Era: Models, Methods and Techniques

Data Analysis in the AI Era covers the process of exploring and analyzing data from various sources for the purpose of extracting information, building models, and making decisions and inferences.

The AI and data analysis field is a scientific area that has grown enormously in recent decades, following a rapidly growing computer industry and the wide applicability of computational techniques in conjunction with new advances in analytic tools. Modeling enables data analysts to apply various statistical methods to the data they are investigating, identify relationships between variables, make predictions about future sets of data, and understand, interpret and visualize the extracted information more strategically. New research results have been developed and published, with many more in progress at the present time.

This book includes applications to health, demography, markets and climate, along with new mathematical and statistical techniques.

James R. Bozeman is a professor of Mathematics at the American University of Malta. He is also a Global Roster of Experts member at the International Science Council (ISC).

Christos H. Skiadas is the founder and former director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete, Greece. He is a prominent researcher in demography and was awarded Honorary Doctor of Accounting and Finance at the Hellenic Mediterranean University, Greece.