Data Science and Machine Learning : Mathematical and Statistical Methods PDF
by Alice Y.C. (University of Wales Trinity Saint David, Hong Kong) Te
Part of the Chapman & Hall/CRC Machine Learning & Pattern Recognition series
Description
"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 CollegeThe 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
Information
-
Download - Immediately Available
- Format:PDF
- Pages:532 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:20/11/2019
- Category:
- ISBN:9781000730777
Information
-
Download - Immediately Available
- Format:PDF
- Pages:532 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:20/11/2019
- Category:
- ISBN:9781000730777