What are Hidden Markov Models in machine learning
Hidden Markov Models in machine learning are statistical models used to describe sequences of observable events governed by underlying hidden states. They assume that the observed data are generated by an unobservable Markov process with hidden states that evolve over time. HMMs find applications in speech recognition, natural language processing, bioinformatics, and more, where understanding … Read more