Mini toolsDefinition
Mathematical systems that transition between states according to probabilistic rules where future states depend only on the current state.
Detailed Explanation
Markov Chain Models are stochastic processes that satisfy the Markov property meaning the future state depends only on the present state and not on the sequence of events that preceded it. They use transition probability matrices to describe the likelihood of moving from one state to another making them powerful tools for modeling sequential data and processes with memory-less properties.
Use Cases
Natural language processing for text generation weather pattern prediction financial market modeling web page ranking algorithms and gene sequence analysis.
