Markov Chain Concepts with Applications
Автор: Elucidation and Interpretation
Загружено: 2025-12-09
Просмотров: 67
In this video, we explore the fundamental concepts of Markov Chains, one of the most important tools in stochastic processes and probability theory. Markov Chains help us model systems that move from one state to another, where the future depends only on the present — not on the past.
You’ll learn:
🔹 What a Markov Chain is and how it works
🔹 Transition probabilities and transition probability matrices
🔹 Types of states: recurrent, transient, absorbing
🔹 Key ideas: stationary distribution, limiting distribution, and long-run behavior
🔹 Real-world applications in weather prediction, finance, reliability, biology, and machine learning
This video from “Elucidation and Interpretation” breaks down the theory into simple, intuitive explanations and connects each concept to practical examples.
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