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Find a path to becoming a Markov Model. Learn more at:
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Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Markov Model.
A classic work on Markov chain Monte Carlo (MCMC) methods. must-read for anyone interested in using MCMC methods for statistical inference.
A comprehensive introduction to Markov chains and stochastic processes. is suitable as a textbook or for self-study.
A comprehensive treatment of Markov processes and their applications. is suitable as a textbook or for self-study.
A comprehensive treatment of hidden Markov models (HMMs) and their applications. is suitable as a textbook or for self-study.
A comprehensive introduction to Markov decision processes (MDPs). is suitable as a textbook or for self-study.
A comprehensive introduction to Markov processes and their applications to stochastic modeling. is suitable as a textbook or for self-study.
A comprehensive introduction to Markov chains and their applications. is suitable as a textbook or for self-study.
An introduction to hidden Markov models (HMMs) and their applications. is suitable for a wide audience, from undergraduates to practitioners.
A mathematical treatment of Markov chains and their mixing times. is suitable for advanced readers with a strong background in mathematics.
A gentle introduction to Markov chains and their applications. is suitable for a wide audience, from undergraduates to practitioners.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/se3lf0/markov
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