Skip to main content Accessibility help
Internet Explorer 11 is being discontinued by Microsoft in August 2021. If you have difficulties viewing the site on Internet Explorer 11 we recommend using a different browser such as Microsoft Edge, Google Chrome, Apple Safari or Mozilla Firefox.
Home
> Subjects
> Introduction to Machine Learning

Introduction to Machine Learning Illustrated Principles

eTextbook coming soon in November 2026

Authors

Christian R. Shelton
, University of California, Riverside
Published 2026

Description

Aimed at undergraduate students, this text guides readers through the methods and principles of machine learning in an approachable manner without sacrificing mathematical precision or notation. Step-by-step explanations allow students to grasp complicated mathematical calculations and translate the theory and mathematics into programming and applications. The text presents machine learning concepts visually, and uses example datasets from fictional hippopotamuses and illustrations to explain the material in a unique, but easily understood and engaging way. Worked examples connect the mathematics and…

  • Add bookmark
  • Export citation
  • Share
Resources available Unlock the full potential of this textbook with additional resources. There are free resources and Instructor restricted resources available for this textbook. Explore resources

Key features

  • Provides straightforward explanations of key methods and principles without sacrificing mathematical precision or notation
  • Includes a chapter on Data Representations that introduces common data encoding methods, particularly for text and images
  • End-of-chapter mathematical exercises and additional coding projects reinforce the focus on concept mastery and real-world application, while extensive illustrations demonstrate concepts and practical aspects of machine learning
  • Step-by-step explanations allow students to grasp complicated mathematical calculations and translate theory to coding

About the book

Curated content