Soft Methods for Data Science

This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Ferraro, Maria Brigida (Editor), Giordani, Paolo (Editor), Vantaggi, Barbara (Editor), Gagolewski, Marek (Editor), Ángeles Gil, María (Editor), Grzegorzewski, Przemysław (Editor), Hryniewicz, Olgierd (Editor)
Format: e-Book
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
Edition:1st ed. 2017.
Series:Advances in Intelligent Systems and Computing, 456
Subjects:
Computational intelligence.
Artificial intelligence.
Probabilities.
Computer science > Mathematics.
Mathematical statistics.
Computational Intelligence.
Artificial Intelligence.
Probability Theory.
Probability and Statistics in Computer Science.
Online Access:Full-text access
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Description
Summary:This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.
Physical Description:XVI, 535 p. 70 illus., 30 illus. in color. online resource.
ISBN:9783319429724
ISSN:2194-5365 ;
DOI:10.1007/978-3-319-42972-4

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