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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...

Flower Pollination Algorithm (FPA) Step-by-Step Learning

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 Flower Pollination Algorithm (FPA) Flower Pollination Algorithm (FPA)  is a Nature Inspired Metaheuristic Optimization Algorithm. It is introduced by Xin She Yang in 2012. Flower Pollination Algorithm is a population based metaheuristic algorithm that is basically inspired by the plants  flowering  behavior in nature. Flower Pollination Algorithm outperform different Metaheuristics and provide better results in different fields such as: For Feature Selection. For Image Processing. For Signal Processing. In Computer Gaming. For Wireless Sensor Network Problems. For Structural Design Problems. For Clustering Problems. For Global Optimization Problems. There are more than 250000 species of flowering plants around the world and 200000 species of pollinators. Pollinators play major role in the pollination process. 35% of our food pants are animal pollinated.  Pollen: Pollen are the grains / Yellow Dust like particles.  Pollinators: Pollinators play major r...
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