The book "Information Theory and Network Coding" by Raymond W. Yeung is an advanced text that builds upon the author's previous work, "A First Course in Information Theory." It covers the rapid development of network coding, which has become a significant research field in information science, influencing areas such as coding theory, networking, wireless communications, and optimization theory. The book is divided into two parts: Part I, "Components of Information Theory," and Part II, "Fundamentals of Network Coding." Part I provides a comprehensive introduction to information theory, covering topics such as Shannon's information measures, the I-Measure, zero-error data compression, weak and strong typicality, discrete memoryless channels, rate-distortion theory, and differential entropy. It also includes discussions on Markov structures and information inequalities, which are crucial for understanding the limitations and capabilities of information theory. Part II focuses on network coding, starting with an introduction to the butterfly network and its applications in wireless and satellite communications. It then delves into the max-flow bound, linear network coding on acyclic and cyclic networks, and multi-source network coding. The book includes detailed proofs, examples, and discussions on the practical aspects of network coding, making it suitable for both educational and reference purposes. The author emphasizes the importance of Part I as a foundation for understanding the more complex concepts in Part II, and the book is recommended for use in a two-semester course in electrical engineering. The book also includes a comprehensive instructor's manual and an errata page to help readers and instructors navigate any errors or omissions.The book "Information Theory and Network Coding" by Raymond W. Yeung is an advanced text that builds upon the author's previous work, "A First Course in Information Theory." It covers the rapid development of network coding, which has become a significant research field in information science, influencing areas such as coding theory, networking, wireless communications, and optimization theory. The book is divided into two parts: Part I, "Components of Information Theory," and Part II, "Fundamentals of Network Coding." Part I provides a comprehensive introduction to information theory, covering topics such as Shannon's information measures, the I-Measure, zero-error data compression, weak and strong typicality, discrete memoryless channels, rate-distortion theory, and differential entropy. It also includes discussions on Markov structures and information inequalities, which are crucial for understanding the limitations and capabilities of information theory. Part II focuses on network coding, starting with an introduction to the butterfly network and its applications in wireless and satellite communications. It then delves into the max-flow bound, linear network coding on acyclic and cyclic networks, and multi-source network coding. The book includes detailed proofs, examples, and discussions on the practical aspects of network coding, making it suitable for both educational and reference purposes. The author emphasizes the importance of Part I as a foundation for understanding the more complex concepts in Part II, and the book is recommended for use in a two-semester course in electrical engineering. The book also includes a comprehensive instructor's manual and an errata page to help readers and instructors navigate any errors or omissions.