What Is Markov Chain?
Markov chain it's an algorithm that considers past events and predicts future outcomes. The algorithm is used in many computer sciences and mathematics, including artificial intelligence and probability theory. It's like that game where you're on a train, and you have to get from point A to point B, but there are no rails, so you have to jump from one train to the next to make it across town. Instead of trains, we're talking about states and variables, and instead of jumping, we call it "transitioning. "The cool thing about Markov chains is that they don't necessarily have an end-point; they keep transitioning until they reach equilibrium. Markov chain can model the likelihood of rain throughout the day. The chain updates its shape every hour based on the weather at the start of that hour. If you see rainy weather at the start of the hour, there is a 90% chance that the chain will stay in the same state. If the temperature at the beginning of the hour is partly cloudy, there is a 60% chance that the chain will remain in the same condition and a 40% chance that the chain will transition to a rainy state. It is Wednesday, and you know what that means: it's time to talk about Markov chains. Markov chains have several implementations in computing and Internet technologies. For example, the PageRank(r) formula employed by Google Search uses a Markov chain to calculate the PageRank of a particular Web page. It is also used to predict user behavior on a website based on users' previous preferences or interactions with it. Markov chains are named after their creator, Andrey Markov, who used them as mathematical models for statistical analysis. The idea is simple: each state (or "node") of the network can only be reached from its previous state (or "parent node"), but not vice versa. It means that state changes are independent of each other, don't depend on outside factors, and only depend on the current state and its parent node. In other words? They make life easier for people who want to predict how things will go online!
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