Study Week: Selected textbooks only 14.99 each—eBooks & softcovers on sale! Shop now >>

cover

Statistical Learning with Math and Python

100 Exercises for Building Logic

Authors: Suzuki, Joe

  • Equips readers with the logic required for machine learning and data science via math and programming 
  • Provides in-depth understanding of Python source programs rather than how to use ready-made Python packages
  • Written in an easy-to-follow and self-contained style
see more benefits

Buy this book

eBook $34.99
price for USA in USD
  • The eBook version of this title will be available soon
  • Due: November 20, 2021
  • ISBN 978-981-15-7877-9
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover $44.99
price for USA in USD
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: October 23, 2021
  • ISBN 978-981-15-7876-2
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
About this Textbook

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building Python programs.

As the preliminary part, Chapter 1 provides a concise introduction to linear algebra, which will help novices read further to the following main chapters. Those succeeding chapters present essential topics in statistical learning: linear regression, classification, resampling, information criteria, regularization, nonlinear regression, decision trees, support vector machines, and unsupervised learning. 

Each chapter mathematically formulates and solves machine learning problems and builds the programs. The body of a chapter is accompanied by proofs and programs in an appendix, with exercises at the end of the chapter. Because the book is carefully organized to provide the solutions to the exercises in each chapter, readers can solve the total of 100 exercises by simply following the contents of each chapter.

This textbook is suitable for an undergraduate or graduate course consisting of about 12 lectures. Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning.

About the authors

Joe Suzuki is a professor of statistics at Osaka University, Japan. He has published more than 100 papers on graphical models and information theory.

Buy this book

eBook $34.99
price for USA in USD
  • The eBook version of this title will be available soon
  • Due: November 20, 2021
  • ISBN 978-981-15-7877-9
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover $44.99
price for USA in USD
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: October 23, 2021
  • ISBN 978-981-15-7876-2
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
Loading...

Services for this Book

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Statistical Learning with Math and Python
Book Subtitle
100 Exercises for Building Logic
Authors
Copyright
2021
Publisher
Springer Singapore
Copyright Holder
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-15-7877-9
DOI
10.1007/978-981-15-7877-9
Softcover ISBN
978-981-15-7876-2
Edition Number
1
Number of Pages
X, 230
Number of Illustrations
2 b/w illustrations, 65 illustrations in colour
Topics