Data Science and Machine Learning: Mathematical and Statistical Methods

by Dirk P. Kroese, Zdravko Botev, Thomas Taimre, and Radislav Vaisman

0 ratings • 0 reviews • 0 shelved
Book cover for Data Science and Machine Learning

Bookhype may earn a small commission from qualifying purchases. Full disclosure.

"This textbook is a well-rounded, rigorous, and informative work presenting the mathematics behind modern machine learning techniques. It hits all the right notes: the choice of topics is up-to-date and perfect for a course on data science for mathematics students at the advanced undergraduate or early graduate level. This book fills a sorely-needed gap in the existing literature by not sacrificing depth for breadth, presenting proofs of major theorems and subsequent derivations, as well as providing a copious amount of Python code. I only wish a book like this had been around when I first began my journey!" -Nicholas Hoell, University of Toronto

"This is a well-written book that provides a deeper dive into data-scientific methods than many introductory texts. The writing is clear, and the text logically builds up regularization, classification, and decision trees. Compared to its probable competitors, it carves out a unique niche.
-Adam Loy, Carleton College

The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science.



Key Features:
  • Focuses on mathematical understanding.
  • Presentation is self-contained, accessible, and comprehensive.
  • Extensive list of exercises and worked-out examples.
  • Many concrete algorithms with Python code.
  • Full color throughout.




Further Resources
  • ISBN13 9781000731071
  • Publish Date 20 November 2019 (first published 14 November 2019)
  • Publish Status Active
  • Publish Country GB
  • Publisher Taylor & Francis Ltd
  • Imprint Chapman & Hall/CRC
  • Format eBook
  • Pages 510
  • Language English