Information Theory for Data Science - by Changho Suh (Hardcover)

About the Book

This book aims at demonstrating modern roles of information theory in a widening array of data science applications, and it is written as a text for senior undergraduate students in Information Theory

Book Synopsis

Information theory deals with mathematical laws that govern the flow, representation and transmission of information, just as the field of physics concerns laws that govern the behavior of the physical universe. The foundation was made in the context of communication while characterizing the fundamental limits of communication and offering codes (sometimes called algorithms) to achieve them.

The most significant achievement of the field is the invention of digital communication which forms the basis of our daily-life digital products such as smart phones, laptops and any IoT devices. Recently it has also found important roles in a spotlight field that has been revolutionized during the past decades: data science.

This book aims at demonstrating modern roles of information theory in a widening array of data science applications. The first and second parts of the book covers the core concepts of information theory: basic concepts on several key notions; and celebrated source and channel coding theorems which concern the fundamental limits of communication. The last part focuses on applications that arise in data science, including social networks, ranking, and machine learning.

The book is written as a text for senior undergraduate and graduate students working on Information Theory and Communications, and it should also prove to be a valuable reference for professionals and engineers from these fields.

Review Quotes

"By going through the proposal and the credentials of the author, I can instantly tell that the proposed book will be looked forward to by the community. The book is going to build a bridge between information theory and data science (also involving some AI). It will be a very useful tool not only for final-year undergraduate and graduate students, but also for researchers (for example myself) who want to understand the relation between the two subjects but do not want to invest too much time on it. The author has a stellar track record. He has worked with and learned from very top people in related fields, and he has received many awards for his research work. In summary, I am confident that this proposed title will be a highly valuable addition to the literature." - Raymond W Yeung, The Chinese University of Hong Kong--Raymond W Yeung (9/24/2022 12:00:00 AM)

About the Author

Dr. Changho Suh is an Associate Professor of Electrical Engineering at KAIST. He received the B.S. and M.S. degrees in Electrical Engineering from KAIST in 2000 and 2002 respectively, and the Ph.D. degree in Electrical Engineering and Computer Sciences from UC Berkeley in 2011.