The book "Computer Algebra - Symbolic and Algebraic Calculations" by Buchberger, Kalme et al is a fascinating and deep dive into the world of computational mathematics. which will be a desktop guide for both students, For professionals as well , Working in Mathematics , Physics and Engineering . This edition is not just a textbook, but a real encyclopedia that opens the door for readers to the world of symbolic calculations and algebraic manipulation. From the first pages of the book, the authors undertake the task not only to explain the basic concepts of computer algebra, but also to show how these concepts are applied in practice. The reader will learn about various methods of symbolic calculations, algorithms and software systems that allow solving complex mathematical problems. The book covers a wide range of topics, including polynomial equations, matrix operations, differential equations, and more. Each section is filled with examples and tasks that will help to consolidate the material and develop skills. This book will be of interest to senior students of mathematical and engineering specialties, graduate students and researchers, as well as anyone who wants to deepen their knowledge in the field of computer algebra. It will suit both those who are just beginning their journey in mathematics, and those who already have experience and want to expand their horizons. If you are interested in such topics as algorithms, programming, computational mathematics and even artificial intelligence, then this publication will be a real find for you. One of the key topics addressed in the book is the use of computer algebra to solve real-world problems. The authors emphasize the importance of symbolic computing in scientific research and engineering applications. They show how algorithms can not only find solutions to equations, but also analyze their properties, which opens up new horizons for scientific discoveries. The book also touches on computational optimization and algorithm efficiency, making it particularly relevant in light of current trends in big data and machine learning. The style of the authors is clear and accessible, which makes complex concepts understandable even for those who are not professional mathematicians. Buchberger and Kalme use a variety of illustrations and graphics that help visualize the material and make it more visual. Their approach to learning is based on the principle of “from simple to complex”, which allows the reader to gradually immerse himself in the topic and not lose interest. In addition, it is worth noting that this book is part of a wider line of publications devoted to computational mathematics. If you are interested in works such as "