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The Probability Companion for Engineering and Computer Science (Paperback)
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The Probability Companion for Engineering and Computer Science (Paperback)
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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.
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