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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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Soft Computing - Neural Networks || Module 2 || ~xRay Pixy

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Video Chapters: Soft Computing Module 2 - Neural Networks 00:00 Introduction 00:39 Topics Covered in Video 01:19 Neural Network Basics 05:12 Problem 01 - Calculate Net Input to Output Neuron 06:33 Artificial Neural Network Terminologies 06:54 Weights 07:59 Bias 08:13 Threshold 08:33 Learning Rate 08:49 Momemtum Factor 09:03 Problem 02 - Calculate Output of Neuron (Y) using Activation Function 09:30 Activation Function 12:42 Problem 02 - Solution 15:25 Neural Network Types 15:38 Simple Neural Network 16:08 Single Feedforward Neural Network 16:41 Multilayer Feedforward Neural Network 17:21 Single Layer Recurrent Network 17:50 Multilayer Recurrent Network 17:52 Perceptron 21:57 Multilayer Perceptron 22:15 Adaline -Its Training and Capabilities 22:59 Conclusion
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