Hidden Markov models with Baum-Welch algorithm using python I'm looking for some python implementation (in pure python or wrapping existing stuffs) of HMM and Baum-Welch.
Some ideas?
I've just searched in google and I've found really poor material with respect to other machine learning techniques. Why?
 A: Have you seen NLTK?
http://www.nltk.org/
It has some classes that are suitable for this sort of thing, but somewhat application dependent.
http://www.nltk.org/api/nltk.tag.html#nltk.tag.hmm.HiddenMarkovModelTrainer
If you are looking for something more 'education oriented', I wrote toy trainer a while ago:
http://pastebin.com/aJG3Ukmn
A: You can find Python implementations on:


*

*Hidden Markov Models in Python - CS440: Introduction to Artifical Intelligence - CSU

*Baum-Welch algorithm: Finding parameters for our HMM | Does this make sense?
BTW: See Example of implementation of Baum-Welch on Stack Overflow - the answer turns out to be in Python.
A: The scikit-learn has an HMM implementation. It was until recently considered as unmaintained and its usage was discouraged. However it has improved in the development version. I cannot vouch for its quality, though, as I know nothing of HMMs.
Disclaimer: I am a scikit-learn developer.
Edit: we have moved the HMMs outside of scikit-learn, to https://github.com/hmmlearn/hmmlearn
A: Some implementation of basic algorithms (including Baum-welch in python) are available here: http://ai.cs.umbc.edu/icgi2012/challenge/Pautomac/baseline.php
A: The General Hidden Markov Model library has python bindings and uses the Baum-Welch algorithm.
A: Following is a Pyhton implementation of Baum-Welch Algorithm:
https://github.com/hamzarawal/HMM-Baum-Welch-Algorithm
