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Hands-On Markov Models with Python

You're reading from   Hands-On Markov Models with Python Implement probabilistic models for learning complex data sequences using the Python ecosystem

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781788625449
Length 178 pages
Edition 1st Edition
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Authors (2):
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Ankur Ankan Ankur Ankan
Author Profile Icon Ankur Ankan
Ankur Ankan
Abinash Panda Abinash Panda
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Abinash Panda
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Summary

In this chapter, we gave a detailed introduction to Markov chains. We talked about different types of Markov chains, mainly chains with a discrete state space, with either discrete time or continuous time. We also introduced the concepts of time-homogeneous and non-time-homogeneous Markov chains. We discussed the different properties of Markov chains in detail, and provided relevant examples and code.

Markov chains and their properties are the basic concepts on which HMMs are built. In the next chapter, we will discuss HMMs in much more detail.

You have been reading a chapter from
Hands-On Markov Models with Python
Published in: Sep 2018
Publisher: Packt
ISBN-13: 9781788625449
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