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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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Objective Function Evaluation | Greedy Method | Knapsack Problem Example...

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Knapsack Problem using Greedy Method Algorithm Design Techniques Divide and Conquer Greedy Method Dynamic Programming Back Tracing Branch and Bound Divide and Conquer:  Many algorithms are recursive in structure. To solve any problem, they call themselves recursively again and again [one or more times]. Three steps are followed by divide and conquer algorithms. 1.) Divide the problem into the number of sub-problems. 2.) Conquer the sub-problems by solving them recursively. 3.) Combine the solution to the sub-problems into the solution for the original problem. The greedy method  is the Straight design technique. It can be applied to a wide variety of problems. Obtain a subset that satisfies the same constraints.  Feasible Solution: If any subset satisfies these constraints.  Our GOAL: Find a feasible solution that either Maximize or Minimize the given Objective Function. A feasible solution that does this is known as OPTIMAL SOLUTION.   A feasible Solution...
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