| 书目名称 | Probability for Information Technology | | 编辑 | Changho Suh | | 视频video | | | 概述 | Illustrates how probability principles drive modern IT applications.Incorporates programming implementations of various algorithms.Nearly self-contained and supplemented with a plethora of exercise pr | | 图书封面 |  | | 描述 | .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 an | | 出版日期 | Textbook 2025 | | 关键词 | Random Processes; Digital Communication; Data Science; Machine Learning; Community Detection; Speech Reco | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-97-4032-1 | | isbn_softcover | 978-981-97-4034-5 | | isbn_ebook | 978-981-97-4032-1 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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发表于 2025-3-21 18:12:10
