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Can I read Data Science, Learning by Latent Structures, and Knowledge Discovery (Studies in Classification, Data Analysis, and Knowledge Organization) on EtoBox?

Data Science, Learning by Latent Structures, and Knowledge Discovery (Studies in Classification, Data Analysis, and Knowledge Organization) by Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Böhmer (eds.) is a nonfiction available to read on EtoBox.

What is Data Science, Learning by Latent Structures, and Knowledge Discovery (Studies in Classification, Data Analysis, and Knowledge Organization) about?

This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking, and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics, and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg

Who reads Data Science, Learning by Latent Structures, and Knowledge Discovery (Studies in Classification, Data Analysis, and Knowledge Organization)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Böhmer (eds.)
Publisher
Springer-Verlag Berlin Heidelberg
Published
2015
Language
EN
ISBN
9783662449820
Category
nonfiction
Subjects
Science, Mathematics, Business

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