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🚀 Welcome to Tutorial 204 in our OpenCV & C++ Series! In this video, we explore Expectation Maximization (EM), a powerful unsupervised machine learning algorithm used for clustering and density estimation. 🔄✨ Learn how EM models data as a mixture of Gaussian distributions, estimates hidden variables, and iteratively improves cluster parameters. We’ll cover both the Expectation step (estimating probabilities) and the Maximization step (updating parameters), making complex data patterns easier to understand and model. You’ll also see practical coding examples using OpenCV’s cv::ml::EM, visualizing clustering on 2D datasets, and tips for choosing the number of clusters and covariance types. Whether you’re doing image segmentation, anomaly detection, or general ML tasks in computer vision, EM is an essential tool to master. 🔍📊 🎯 What you’ll learn: How Expectation Maximization works and why it’s useful for unsupervised learning Training & predicting with cv::ml::EM in OpenCV C++ Understanding Gaussian mixtures, cluster probabilities, and convergence Visualizing clustering results for different datasets Comparing EM with K-Means and other clustering algorithms Step-by-step code walkthrough with practical examples 📚 Perfect for: Developers learning OpenCV ML, C++ beginners exploring clustering techniques, and anyone working on unsupervised tasks in computer vision projects! 💻 Code + Theory + Demos = Complete Understanding 📌 Missed Tutorial 203? Check it out to learn Random Trees (RTrees) for classification and regression in OpenCV & C++! 🌠 EM class: https://docs.opencv.org/4.8.0/d1/dfb/... 🌠 Tutorial Series Plan: https://docs.opencv.org/4.8.0/modules... 🌠 Stackoverflow: https://stackoverflow.com/users/11048... 🌠 Github: https://github.com/yunus-temurlenk?ta... 🌠 Twitter: / code_enjoy 🌠 Hashnode: https://yunustemurlenk.hashnode.dev/ ▬ Contents of this video ▬▬▬▬▬▬▬▬▬▬ 0:00 - Introduction 4:06 - Coding If you see any mistake or have advice, please comment. Thanks for watching… #OpenCV #Cplusplus #MachineLearning #EM #ExpectationMaximization #ComputerVision