Elements of Data Science, Machine Learning, and Artificial Intelligence Using R

Emmert-Streib, Frank; Moutari, Salissou; Dehmer, Matthias

ISBN 10: 3031133382 / ISBN 13: 9783031133381

Verlag: Springer, 2023

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Inhaltsangabe:

The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data.

Über die Autorin bzw. den Autor:

Frank Emmert-Streib is Professor of Data Science at Tampere University (Finland). He leads the Predictive Society and Data Analytics Lab, which pursues innovative research in deep learning and natural language processing. The Lab develops and applies high-dimensional methods in machine learning, statistics, and artificial intelligence that can be used to extract knowledge from data in the fields of biology, medicine, social media, social sciences, marketing, or business.

Salissou Moutari is Senior Lecturer at Queen’s University Belfast (UK) and Interim Director of Research of the Mathematical Science Research Centre (MSRC). His research interests include mathematical modelling, optimization, machine learning and data science, and the applications of these methods to problems from traffic, transportation and distribution systems, production planning and industrial processes.

Matthias Dehmer is Professor at UMIT (Austria) and also has a position at Swiss Distance University of Applied Sciences, Brig, Switzerland. His research interests are in complex networks, complexity, data science, machine learning, big data analytics, and information theory. In particular, he is working on machine learning based methods to analyse high-dimensional data.

Bibliografische Details

Titel: Elements of Data Science, Machine Learning, ...
Verlag: Springer
Erscheinungsdatum: 2023
Einband: Hardcover
Zustand: Neu