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I read quite a bit of hidden markov models and was able to code a pretty basic version of it myself.

But there are two main ways I seem to learn. One is to read and implement it into code(which is done) and the second is to understand how it applies under different situations(so I can better understand how it relates to problems I might be working on). All the examples I have done so far have involved either some kind of dna prediction or coin tossing.

I'm wondering if there are any resources to get other markov problems(language doesn't matter but hopefully with the answers as well so I can know if I'm right or wrong)?

Lostsoul
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  • Did you take the Stanford AI class? There are some basic problems in there ;) – SuperTron Dec 28 '11 at 22:27
  • Its funny you mentioned that, I am going through it right now. Haven't seen everything but they seem a bit similar to the unfair dice examples(I got to run but I will finish the markov section tonight). Thanks SuperTron! – Lostsoul Dec 28 '11 at 22:42
  • Haha, I guessed as much. I think you may find some better information on [stats.stackexchange](http://stats.stackexchange.com/) (since HMM is a statistical model). Stack overflow is more for programming specific questions. Best of luck! – SuperTron Dec 28 '11 at 22:47

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There are a couple good examples in the stanford ai class, otherwise, do some googling for intro's to HMM's. This PDF has a decently good example on the topic, and there are a ton of other resources available online. As I mentioned in my comment, stats.stackexchange may be a better place for a question like this because HMM's are a type of statistical model, so you may get a more detailed answer there. Hope this helps!

Community
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SuperTron
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I would recommend the book Markov Chains by Pierre Bremaud for conceptual and theoretical background. For practical examples in the context of data analysis, I would recommend the book Inference in Hidden Markov Models.

EWA
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