Soft Methods for Data Science. [electronic resource]
Další autoři: |
Ferraro, Maria Brigida, editor
Giordani, Paolo, editor
Vantaggi, Barbara, editor
Gagolewski, Marek, editor
Ángeles Gil, María, editor
Grzegorzewski, Przemysław, editor
Hryniewicz, Olgierd, editor
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Jazyk: | angličtina |
Informace o vydání: | Cham : Springer International Publishing : Imprint: Springer, 2017. |
Předmět: | |
Druh dokumentu: | Electronic; Non-fiction |
ISSN: | 2194-5357 ; 2194-5357 ; |
Abstrakt: | 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. |
Databáze: | Vybrané kolekce e-knih |
Externí odkaz: |