Mathematics of Data Science: A Computational Approach to Clustering and Classification

Mathematics of Data Science: A Computational Approach to Clustering and Classification
ISBN-10
1611976375
ISBN-13
9781611976373
Category
Mathematics
Pages
199
Language
English
Published
2020-11-20
Publisher
SIAM
Authors
Erkki Somersalo, Daniela Calvetti

Description

This textbook provides a solid mathematical basis for understanding popular data science algorithms for clustering and classification and shows that an in-depth understanding of the mathematics powering these algorithms gives insight into the underlying data. It presents a step-by-step derivation of these algorithms, outlining their implementation from scratch in a computationally sound way. Mathematics of Data Science: A Computational Approach to Clustering and Classification proposes different ways of visualizing high-dimensional data to unveil hidden internal structures, and nearly every chapter includes graphical explanations and computed examples using publicly available data sets to highlight similarities and differences among the algorithms. This self-contained book is geared toward advanced undergraduate and beginning graduate students in the mathematical sciences, engineering, and computer science and can be used as the main text in a semester course. Researchers in any application area where data science methods are used will also find the book of interest. No advanced mathematical or statistical background is assumed.

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