Mathematics of Data Science

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
includes graphical explanations and computed examples using publicly available data sets in nearly every chapter to highlight similarities and differences among the algorithms.

Mathematics of Data Science features in the following genres: Applied mathematics, Maths for computer scientists, Maths for scientists, Maths for engineers

Mathematics of Data Science is available in Paperback

Mathematics of Data Science was written by Daniela Calvetti, Erkki Somersalo and published by Society for Industrial and Applied Mathematics an imprint of SIAM - Society for Industrial and Applied Mathematics

Mathematics of Data Science has 189 pages

Yes it is part of Data Science series