Data Science and Machine Learning Mathematical and Statistical Methods

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Synopsis

"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 can be found on the authors website: https://github.com/DSML-book/Lectures

Book details

Series:
Chapman And Hall/crc Machine Learning And Pattern Recognition Ser.
Author:
Dirk P. Kroese, Zdravko Botev, Thomas Taimre, Radislav Vaisman
ISBN:
9781000731071
Related ISBNs:
9781138492530, 9780367816971
Publisher:
CRC Press
Pages:
510
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2023-09-19
Usage restrictions:
Copyright
Copyright date:
2020
Copyright by:
Taylor & Francis Group, LLC 
Adult content:
No
Language:
English
Categories:
Business and Finance, Computers and Internet, Mathematics and Statistics, Nonfiction