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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...

LOOPING STRUCTURE - WHILE LOOP, DO-WHILE LOOP

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Code Generator

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Discrete Event Simulation (DES)

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Discrete event simulation  ( DES ) is the process of codifying the behavior of a complex system as an ordered sequence of well-defined  events . In this context, an  event  comprises a specific change in the system's state at a specific point in time.
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