Markov Chain Analysis: The Backbone of Data Science

Markov Chain Analysis is a powerful mathematical framework used in data science to model probabilistic processes where future states depend only on the present state. This technique is widely applied in machine learning, finance, NLP, and predictive analytics to analyze sequential data and forecast outcomes. By leveraging transition probabilities and state-dependent dynamics, Markov Chains help businesses and researchers make data-driven decisions, optimize processes, and enhance predictive modeling accuracy.