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Discrete Stochastic Processes

Tools for Machine Learning and Data Science

Language EnglishEnglish
E-book Adobe ePub DRM
Publishers Springer, October 2024
This text presents selected applications of discrete-time stochastic processes that involve random i... Full description
? points 162 b
67.16
In stock Immediate digital delivery

This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (excited) random walks, convergence and mixing of Markov chains, distribution modeling using phase-type distributions, applications to search engines and probabilistic automata, and an introduction to the Ising model used in statistical physics. Applications to data science are also considered via hidden Markov models and Markov decision processes. A total of 32 exercises and 17 longer problems are provided with detailed solutions and cover various topics of interest, including statistical learning.

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About the book

Full name Discrete Stochastic Processes
Language English
Binding E-book - Adobe ePub DRM
Date of issue 2024
EAN 9783031658204
Libristo code 47698722
Publishers Springer
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