Soft Methods for Data Science

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Ferraro, Maria Brigida (Επιμελητής έκδοσης), Giordani, Paolo (Επιμελητής έκδοσης), Vantaggi, Barbara (Επιμελητής έκδοσης), Gagolewski, Marek (Επιμελητής έκδοσης), Ángeles Gil, María (Επιμελητής έκδοσης), Grzegorzewski, Przemysław (Επιμελητής έκδοσης), Hryniewicz, Olgierd (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: Advances in Intelligent Systems and Computing, 456
• Θέματα: Engineering.; Mathematical statistics.; Artificial intelligence.; Probabilities.; Computational intelligence.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).; Probability Theory and Stochastic Processes.; Probability and Statistics in Computer Science.
• Φυσική περιγραφή: XVI, 535 p. 70 illus., 30 illus. in color. online resource.
• ISBN: 9783319429724
• ISSN: 2194-5357 ;

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.