Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning

This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to follow.

Many excellent books in this field have been published in the past. However, these books are not necessarily intended for self-study by beginners.

This book limits the topics to the minimum essential t...