Kmeans, Kmeans++, Gaussian Mixtures

In this project, I analyze a dataset containing annual spending spending data on diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with.

Machine Learning based Personal Voice Assisstant and text independent (Development phase)

A synchronous Kernels-only competition

Gaussian Mixture Error Estimation for Approximate Circuits

Gaussian Mixture Model implementation.

Python library to perform topic detection on textual data that are generated over time.

Implementation of the Automatic Recognition with VAS Index (pain index) with the aim of demonstrating the effectiveness of the Random Forest on the problem.

Building an anomaly detection model using Gaussian Mixture Model (GMM)

Use GMM to do color segmentation for images and detect if pixel is a playing field.

Cluster analysis of shape features in famous datasets

BUET Machine Learning Lab Course

Trained MATLAB models for 82% precision/80% recall, optimized with blob analysis for 25% performance boost. User-friendly alarm system with 500+ engaged users.

A from-scratch implementation of Gaussian Mixture Models

🎓 Advanced Multivariate Statistics in Python [UniMi • AY 2022/2023]

Clustering using Gaussian mixture modeling for species delimitation and classification

A comparative study between 5 different binary classification techniques.

CSE 601 Data mining and bioinformatics

This is Fortran-90 implementation of ECGMM algorithm

Python implementation of the Gaussian Mixture Probability Hypothesis Density Filter