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Hardcover - 9783030499945
53,49 €
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Beschreibung
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.
An Application-Driven Course
An Application-Driven Course
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 24. Juni 2022 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 616 Gramm |
| Format | Softcover |
| ISBN-13 | 9783030499976 |
| Auflage | 1st edition 2021 |
| Seiten | 380 |
Schlagwörter
Communications Engineering - Networks, Mathematical and Computational Engineering Applications, Mathematik für Informatiker, Mathematik für Ingenieure, Nachrichtententechnik - Telekommunikation, Probability and Statistics in Computer Science, Probability Theory, Statistics in Engineering - Physics - Computer Science - Chemistry and Earth Sciences, Stochastik, Wahrscheinlichkeitsrechnung und Statistik
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