Nature Inspired Computing for Data Science
Synopsis
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.
Publisher information
- Publisher: Springer International Publishing
- ISBN: 9783030338190
- Number of pages: 295
- Dimensions: 235 x 155 x 19 mm
- Weight: 635g
- Languages: English
