Intro to Markov Models with Swift

The article introduces Markov models and chains, which are used to model randomly changing systems where future states depend only on the current state. It explains how Markov models can be used in various fields such as genetics, finance, economics, game theory, and more. The article also discusses hidden Markov models, which are a type of Markov chain where some states are observable and some are hidden. A specific example is given using Twilio's sentence analysis to visualize weighted distributions and transitions between states. The article concludes by mentioning the use of Swift libraries such as MarkovModel to create visualizations of Markov models in code.