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Theory of Information and its Value (Hardcover, 1st ed. 2020)
Loot Price: R3,486
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Theory of Information and its Value (Hardcover, 1st ed. 2020)
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This English version of Ruslan L. Stratonovich's Theory of
Information (1975) builds on theory and provides methods,
techniques, and concepts toward utilizing critical applications.
Unifying theories of information, optimization, and statistical
physics, the value of information theory has gained recognition in
data science, machine learning, and artificial intelligence. With
the emergence of a data-driven economy, progress in machine
learning, artificial intelligence algorithms, and increased
computational resources, the need for comprehending information is
essential. This book is even more relevant today than when it was
first published in 1975. It extends the classic work of R.L.
Stratonovich, one of the original developers of the symmetrized
version of stochastic calculus and filtering theory, to name just
two topics. Each chapter begins with basic, fundamental ideas,
supported by clear examples; the material then advances to great
detail and depth. The reader is not required to be familiar with
the more difficult and specific material. Rather, the treasure
trove of examples of stochastic processes and problems makes this
book accessible to a wide readership of researchers, postgraduates,
and undergraduate students in mathematics, engineering, physics and
computer science who are specializing in information theory, data
analysis, or machine learning.
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