Modeling Manufacturing Data Using Markov Chains

Author(s): Ning Jia

Originally published on Towards AI.

Markov process, despite its simplicity, continues to find practical uses with real-world manufacturing datasets.

Markov chain is a simple mathematical model with wide machine-learning applications. It tries to model a system that transitions from one state to another, where the probability of transitioning to a given state depends only on the system's current state. The critical element of a Markov chain is the transition matrix, which is a square matrix that describes the probabilities of transitioning from one state to another.

There are tons of articles on Markov chains. I'm not writing another introductory essay on the Markov chain with artificial examples like weather modeling. Instead, I want to share my experience applying the Markov… Read the full blog for free on Medium.

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Published via Towards AI