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Applied Modeling Techniques and Data Analysis 1:...

Applied Modeling Techniques and Data Analysis 1: Computational Data Analysis Methods and Tools

Yiannis Dimotikalis, Alex Karagrigoriou, Christina Parpoula, Christos H. Skiadas (Editors)
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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 1 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.

卷:
7
年:
2021
出版:
1
出版社:
Wiley-ISTE
语言:
english
页:
283
ISBN 10:
1786306735
ISBN 13:
9781786306739
ISBN:
B091J352XD
系列:
Innovation, Enterpreneurship, Management Series: Big Data, Artificial Intelligence and Data Analysis Set
文件:
PDF, 11.15 MB
IPFS:
CID , CID Blake2b
english, 2021
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