TY  - GEN
AU  - Walrand, Jean
TI  - Probability in electrical engineering and computer science: an application-driven course
SN  - 9783030499945
U1  - 519.2 
PY  - 2021///
CY  - Cham
PB  - Springer
KW  - Probabilities
KW  - Electrical engineering--Mathematics
KW  - Computer science--Mathematics
KW  - Mathematical statistics
KW  - Statistics
N1  - Includes index and references
N2  - 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. The companion website now has many examples of Python demos and also Python labs used in Berkeley.f
ER  -