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The Probability Companion for Engineering and Computer Science (Paperback) Loot Price: R1,415
Discovery Miles 14 150
The Probability Companion for Engineering and Computer Science (Paperback): Adam Prugel-Bennett

The Probability Companion for Engineering and Computer Science (Paperback)

Adam Prugel-Bennett

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Loot Price R1,415 Discovery Miles 14 150 | Repayment Terms: R133 pm x 12*

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This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overview for students.

General

Imprint: Cambridge UniversityPress
Country of origin: United Kingdom
Release date: 2020
Authors: Adam Prugel-Bennett
Dimensions: 253 x 178 x 23mm (L x W x T)
Format: Paperback - Trade
Pages: 470
ISBN-13: 978-1-108-72770-9
Categories: Books > Computing & IT > General theory of computing > General
Books > Computing & IT > Applications of computing > General
Books > Business & Economics > Economics > Econometrics > General
Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics
Books > Business & Economics > Finance & accounting > Finance > Insurance > General
Books > Money & Finance > Insurance > General
LSN: 1-108-72770-0
Barcode: 9781108727709

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