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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...

METAHEURISTIC OPTIMIZATION

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 Introduction to Metaheuristic Optimization Metaheuristic represents the family of approximate Optimization Techniques / Algorithms. Using Metaheuristic Techniques we can solve complex real world problems, Engineering design problems, Scientific Problems, Industrial Problems and obtain acceptable solution within time [ especially used to solve Science and Engineering Problem s]. In Metaheuristic , META means Upper Level Methodology / High Level Procedure and HEURISTIC means Art of discovering new strategies or rules to solve problems / discover or learn something for themselves.  Metaheuristic is an advanced technique used to locate, create, or select a heuristic that may provide correct and acceptable results to Optimization Problems. Optimization is finding better solutions among different possible solutions within acceptable amounts of time. Metaheuristic algorithms are best to solve complex engineering design problems. Popular Metaheuristic Algorithms are:  Geneti...
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