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Markov chains, named after Andrey Markov, are mathematical systems that hop from one "state" (a situation or set of values) to another. For example, if you made a Markov chain model of a baby's behavior, you might include "playing," "eating", "sleeping," and "crying" as states, which together with other behaviors could form a 'state space': a list of all possible states. In addition, on top of the
Edit A previous version of this blogpost had the worst typo ever. I simulated everything using np.random.randint(1,6) which only samples between 1-5. This led to a lot more jail time because it was much more likely to get there. I've been trending on hackernews, I've been linked to in boing-boing; 14000 views later and nobody mentioned the error. Thankfully, I have a collegue who doesn't mind poin
Markov chains, named after Andrey Markov, are mathematical systems that hop from one "state" (a situation or set of values) to another. For example, if you made a Markov chain model of a baby's behavior, you might include "playing," "eating", "sleeping," and "crying" as states, which together with other behaviors could form a 'state space': a list of all possible states. In addition, on top of the
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