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Hidden Markov Model (HMM)

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Hidden Markov Model (HMM)  VIDEO LINK:  https://youtu.be/YIGCWNG8BIA A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. Video Chapters: HMM in Artificial Intelligence 00:00 Introduction 00:31 Statistical Model 00:54 HMM Examples 02:30 HMM 03:10 HMM Components 05:23 Viterbi Algorithm 06:23 HMM Applications 06:38 HMM Problems 07:28 HMM in Handwriting Recognition 11:20 Conclusion  HMM COMPONENTS A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. An HMM consists of states, observations, transition probabilities, emission probabilities, and initial probabilities. It is commonly used in a...
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What is a meta heuristic algorithm for?

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  Metaheuristic  means a High-level problem-independent algorithmic framework that is developed for the optimization algorithm. Metaheuristic algorithms  find the best solution out of all possible solutions of an optimization. I discussed some Meta-heuristic algorithm like: Grey Wolf Optimization (GWO) Algorithm:  GWO is a metaheuristic proposed by Mirjaliali Mohammad and Lewis, 2014. GWO is inspired by the social hierarchy and the hunting technique of Grey Wolves Bat Algorithm:  The  Bat algorithm  is a metaheuristic algorithm for global optimization. It was inspired by the echolocation behavior of microbats. Cuckoo Search Algorithm: Cuckoo Search is a n ature-inspired  algorithm , based on the brood reproductive strategy of cuckoo birds to increase their population. Meta-heuristic Algorithms
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