Nature Inspired Computing for Data Science (Paperback, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 871
Release date:	2021
First published:	2020
Editors:	Minakhi Rout • Jitendra Kumar Rout • Himansu Das
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	295
Edition:	1st ed. 2020
ISBN-13:	978-3-03-033822-0
Categories:	Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-033822-3
Barcode:	9783030338220

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