Probability for Information Technology 2024th Edition

Probability for Information Technology 2024th Edition book cover

Probability for Information Technology 2024th Edition

Author(s): Changho Suh (Author)

  • Publisher: Springer
  • Publication Date: 18 Nov. 2024
  • Edition: 2024th
  • Language: English
  • Print length: 365 pages
  • ISBN-10: 9819740312
  • ISBN-13: 9789819740314

Book Description

This book introduces probabilistic modelling and explores its role in solving a broad spectrum of engineering problems that arise in Information Technology (IT). Divided into three parts, it begins by laying the foundation of basic probability concepts such as sample space, events, conditional probability, independence, total probability law and random variables. The second part delves into more advanced topics including random processes and key principles like Maximum A Posteriori (MAP) estimation, the law of large numbers and the central limit theorem. The last part applies these principles to various IT domains like communication, social networks, speech recognition, and machine learning, emphasizing the practical aspect of probability through real-world examples, case studies, and Python coding exercises.

A notable feature of this book is its narrative style, seamlessly weaving together probability theories with both classical and contemporary IT applications. Each concept is reinforced with tightly-coupled exercise sets, and the associated fundamentals are explored mostly from first principles. Furthermore, it includes programming implementations of illustrative examples and algorithms, complemented by a brief Python tutorial.

Departing from traditional organization, the book adopts a lecture-notes format, presenting interconnected themes and storylines. Primarily tailored for sophomore-level undergraduates, it also suits junior and senior-level courses. While readers benefit from mathematical maturity and programming exposure, supplementary materials and exercise problems aid understanding. Part III serves to inspire and provide insights for students and professionals alike, underscoring the pragmatic relevance of probabilistic concepts in IT.

Editorial Reviews

Review

Select Guide Rating

From the Back Cover

This book introduces probabilistic modelling and to study its role in solving a wide variety of engineering problems that arise in Information Technology (IT). The book consists of three parts. The first introduces the basic concepts of probability: sample space, events, conditional probability, independence, total probability law, random variables, probability mass functions, density functions and expectation. In the second part, we study the concept of random processes, as well as key principles such as Maximum A Posteriori (MAP) estimation, Maximum Likelihood (ML) estimation, law of large numbers and central limit theorem. Using the language and principles acquired in the prior parts, the last discusses IT applications chosen from communication, social networks and speech recognition. The book puts a special emphasis on “probability in action”: probabilistic concepts are taught through many running examples, killer applications and Python coding exercises.

One defining feature of this book is that it succinctly relates the “story” of how the key principles of probability play a role, via classical and trending IT applications. All the key “plots” involved in the story are coherently developed with the help of tightly-coupled exercise problem sets, and the associated fundamentals are explored mostly from first principles. Another key feature is that it includes programming implementation of toy examples and various algorithms inspired by fundamentals. It also provides a brief tutorial of the used programming tool: Python.

This book does not follow a traditional book-style organization, but is streamlined via a series of lecture notes that are intimately related, centered around coherent storylines and themes. It serves as a textbook mainly for a sophomore-level undergraduate course, yet is also suitable for a junior or senior-level undergraduate course. Readers benefit from having some mathematical maturity and exposure to programming. But the background can be supplemented by almost self-contained materials, as well as by numerous exercise problems intended for elaborating on non-trivial concepts. In addition, Part III for IT applications should provide motivation and insights to students and even professional engineers who are interested in the field.

View on Amazon

电子书代发PDF格式价格30我要求助
未经允许不得转载:Wow! eBook » Probability for Information Technology 2024th Edition