This book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and inspiration for researchers to wanting to employ nature-inspired optimization techniques in their own endeavors.
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Focuses on the advances in nature-inspired computing and its value in data science Presents contributions from various fields of computational intelligence, machine learning, deep learning, and nature-inspired computing to build intelligent systems for real-time data analytics Includes fundamentals, applications, algorithms and case studies of the advances and research in the fields of nature-inspired computing, data science and engineering
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GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
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Product details

ISBN
9783030338220
Published
2021-01-24
Publisher
Springer Nature Switzerland AG
Height
235 mm
Width
155 mm
Age
Research, P, 06
Language
Product language
Engelsk
Format
Product format
Heftet
Number of pages
12