{"id":26025328,"url":"https://github.com/preethi2805/gaussian_mixture_models","last_synced_at":"2026-06-05T19:31:20.095Z","repository":{"id":278496269,"uuid":"935812193","full_name":"Preethi2805/Gaussian_Mixture_Models","owner":"Preethi2805","description":"This repository contains the implementation of a 3-component, 2D Gaussian Mixture Model (GMM) using Python. 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The goal of the exercise is to visualize the behaviour of a **3-component, 2D Gaussian Mixture Model (GMM)** using the specified parameters for each Gaussian component.\n\nThe exercise includes generating samples from the GMM, and visualizing them in a 3-panel plot that shows:\n1. **Joint Distribution** of the GMM samples.\n2. **Marginal Distribution** of the samples.\n3. **Responsibilities** of each Gaussian component in explaining each sample.\n\n## Files in this Repository\n\n- **gmm_visualization.py**: Contains the implementation of the Gaussian Mixture Model sampling, visualization, and plotting.\n- **README.md**: This file provides an overview of the exercise and repository.\n\n![Gaussian Mixture Model](GMM.png)\n\n## Conclusion\nThe code successfully implements the task to visualize a 3-component 2D Gaussian Mixture Model, with appropriate visualization techniques to display how each component contributes to the overall mixture. The plot allows for a qualitative analysis of the GMM's behavior and the responsibilities of each component in explaining the data.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpreethi2805%2Fgaussian_mixture_models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpreethi2805%2Fgaussian_mixture_models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpreethi2805%2Fgaussian_mixture_models/lists"}