Springer, 2023. - 371 p. - ISBN: 3662678810.
This textbook provides an easy-to-understand introduction to the
mathematical concepts and algorithms at the foundation of
data science. It covers essential parts of
data organization, descriptive and inferential statistics, probability theory, and machine learning. These topics are presented in a
clear and mathematical sound way to help readers gain a
deep and fundamental understanding. Numerous application examples based on real data are included. The book is well-suited for
lecturers and students at technical universities, and offers a good introduction and overview for people who are
new to the subject. Basic mathematical knowledge of calculus and linear algebra
is required.
True PDF