Can I read Applied Modeling Techniques and Data Analysis 2 : Financial, Demographic, Stochastic and Statistical Models and Methods on EtoBox?

Applied Modeling Techniques and Data Analysis 2 : Financial, Demographic, Stochastic and Statistical Models and Methods by Yiannis Dimotikalis; Alex Karagrigoriou; Christina Parpoula; Christos H. Skiadas is a nonfiction available to read on EtoBox.

What is Applied Modeling Techniques and Data Analysis 2 : Financial, Demographic, Stochastic and Statistical Models and Methods about?

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 2 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.

Who reads Applied Modeling Techniques and Data Analysis 2 : Financial, Demographic, Stochastic and Statistical Models and Methods?

Author

Yiannis Dimotikalis; Alex Karagrigoriou; Christina Parpoula; Christos H. Skiadas

Publisher

Wiley-ISTE

Published

2022

Language

EN

ISBN

9781119821632

Category

nonfiction

Subjects

Management, Business, Computer Science