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 id
Data Analysis and Applications 3: Computational, Classification, Financial, Statistical and Stochastic Methods
โ Scribed by Andreas Makrides (editor), Alex Karagrigoriou (editor), Christos H. Skiadas (editor)
- Publisher
- ISTE Ltd
- Year
- 2020
- Tongue
- English
- Leaves
- 252
- Edition
- 3
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Data analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and statistics packages. This book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis. The chapters included in this volume represent a cross-section of current concerns and research interests in these scientific areas. The material is divided into two parts: Computational Data Analysis, and Classification Data Analysis, with methods for both - providing the reader with both theoretical and applied information on data analysis methods, models and techniques and appropriate applications.
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