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Data Science in Applications: Studies in Computational Intelligence, cartea 1084

Editat de Gintautas Dzemyda, Jolita Bernatavičienė, Janusz Kacprzyk
en Limba Engleză Hardback – 10 mar 2023
This book provides an overview of a wide range of relevant applications and reveals how to solve them. Many of the latest applications in finance, technology, education, medicine and other important and relevant fields are data-driven. The volumes of data are enormous. Specific methods need to be developed or adapted to solve a particular problem. It illustrates data science in applications. These applications have in common the discovery of knowledge in data and the use of this knowledge to make real decisions. The set of examples presented serves as a recipe book for their direct application to similar problems or as a guide for the development of new, more sophisticated approaches. The intended readership is data scientists looking for appropriate solutions to their problems. In addition, the examples provided serves as material for lectures at universities.
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Specificații

ISBN-13: 9783031244520
ISBN-10: 3031244524
Ilustrații: XII, 252 p. 100 illus., 76 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.59 kg
Ediția:1st ed. 2023
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Computational Thinking Design Application for STEAM Education.- Education Data for Science: Case of Lithuania.- Imbalanced Data Classification Approach Based on Clustered Training Set.- Baltic States in Global Value Chains: Quantifying International Production Sharing at Bilateral and Sectoral Levels.- The Soft Power Of Understanding Social Media Dynamics: A Data-Driven Approach.- Bootstrapping  Network Autoregressive Models for Testing Linearity.- Novel data science methodologies for essential genes identification based on network analysis.- Acoustic Analysis for Vocal Fold Assessment - Challenges, Trends, and Opportunities.- The Paradigm of an Explainable Artificial Intelligence (XAI) and Data Science (DS) Based Decision Support System (DSS).- Stock Portfolio Risk-Return Ratio Optimisation using Grey Wolf Model.- Towards Seamless Execution of Deep Learning Application on Heterogeneous HPC Systems.


Textul de pe ultima copertă

This book provides an overview of a wide range of relevant applications and reveals how to solve them. Many of the latest applications in finance, technology, education, medicine and other important and relevant fields are data-driven. The volumes of data are enormous. Specific methods need to be developed or adapted to solve a particular problem. It illustrates data science in applications. These applications have in common the discovery of knowledge in data and the use of this knowledge to make real decisions. The set of examples presented serves as a recipe book for their direct application to similar problems or as a guide for the development of new, more sophisticated approaches. The intended readership is data scientists looking for appropriate solutions to their problems. In addition, the examples provided serves as material for lectures at universities.

Caracteristici

Presents recent research on Applied Data Science
Overviews recent developments in Data Science and Applications
Written by experts in the field