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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
Author Profile Icon Abinash Panda
Abinash Panda
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Summary

In this chapter, we got a detailed introduction to Markov model and HMM. We talked about parameterizing an HMM, generating samples from it, and their code. We discussed estimating the probability of observation, which would form the basis of inference, which we'll cover in the next chapter. We also talked about various extensions of HMMs.

In the next chapter, we will take an in-depth look at inference in HMMs.

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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