Probability in Electrical Engineering and Computer Science: An Application-Driven Course (1st ed. 2021)

By: Jean Walrand

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Synopsis: This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at mary.james@springer.com. This is an open access book.

Book Quality:: Publisher Quality
ISBN-13:: 9783030499952
Related ISBNs:: 9783030499945
Publisher:: Springer International Publishing
Date of Addition:: 08/31/22
Copyrighted By:: The Editor
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Computers and Internet, Technology, Mathematics and Statistics, Communication
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.