Discrete Stochastic Processes

Tools for Machine Learning and Data Science

Nicolas Privault author

Format:Paperback

Publisher:Springer International Publishing AG

Published:8th Oct '24

Should be back in stock very soon

Discrete Stochastic Processes cover

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.

ISBN: 9783031658198

Dimensions: unknown

Weight: unknown

288 pages

2024 ed.