The book "Uniform Markov Chains", written by Zhong Kai-lai and supplemented by the works of B. F. Colchin and C. X. Sirazhdinova is a fascinating and deep dive into the world of probability theory and statistics. This work not only illuminates the basic concepts of homogeneous Markov chains, but also offers readers a unique perspective on their application in various fields of science and technology. If you have ever thought about how random processes affect the real world, this book will be a real discovery for you. Markov’s homogeneous circuits are an important tool in probability theory that finds application in a wide variety of fields, from economics and sociology to biology and computer science. The authors explain in detail how these chains work, what properties they have, and how they can be used to model real-world processes. The book begins with the basics, gradually deepening into more complex topics, making it accessible to both students and professionals seeking to expand their knowledge in this area. This work will be of particular interest to undergraduate and graduate students studying mathematics, statistics, and related disciplines. But not only them: researchers working in the field of machine learning, game theory and even in the social sciences will find in it many useful ideas and concepts. The book can be an excellent addition to training courses in probability theory and statistics, as well as a useful resource for practitioners. One of the key topics raised in the book is the connection between theory and practice. The authors not only present theoretical aspects, but also give examples of real applications of homogeneous Markov chains. This allows the reader to see how abstract mathematical concepts can be used to solve specific problems, such as predicting user behavior on the Internet or analyzing biological processes. This approach makes the material more lively and interesting, and also helps to better assimilate complex ideas. The style of the authors is clear and accessible, which makes reading a book not only useful, but also fascinating. Zhong Kai-lai, known for his work in probability theory, masterfully explains complex concepts using simple and understandable examples. In. F. Colchin and C. X. Sirazhdinov add their comments and explanations, which makes the text even more saturated and informative . If you are looking for books that are similar in genre, pay attention to "Probability Theory and Mathematical Statistics" A. N. Shiryaev or "