This repository demonstrates unsupervised learning using K-Means and Hierarchical Clustering algorithms. It covers data preparation, clustering logic, and evaluation to identify patterns and group similar data points. Designed for beginners learning clustering and exploratory data analysis concepts.

Quantize/compress image colors using K-Means algorithm, with configurable number of colors K.

Let's get those centroids!

It is a ml implementation of K means on mall customer dataset

A C implementation of K-Means clustering algorithm with Python bindings

A computer vision application that retrieves the most similar video frames to selected image/object/character

👩🏻‍🚀 12- Data Mining Hands-on project exploring clustering techniques (K-Means, Mean-Shift, Affinity Propagation) with data cleaning, visualization, and method comparison

A c++ implementation of kmeans and kmeans++ algorithms for machine learning

This repository contains multiple projects demonstrating the application of KMeans clustering, an unsupervised machine learning algorithm. Each project explores clustering on different datasets, combined with techniques such as data preprocessing, dimensionality reduction (PCA), and visualization.

👩🏻‍🚀 9- Data Mining Hands-on project exploring use of the KMeans Algorithm Presentation

👩🏻‍🚀 8-Data Mining Prediction - Comprehensive K-Means clustering tutorial with step-by-step Python implementation, including normalization, elbow and silhouette methods, cluster visualizations and applications in image segmentation, Monkey analysis, and other clustering tasks.

High-performance .NET library for optimal 1D K-means clustering. Guarantees globally optimal solutions in O(k·n) time.

App that utilizes Kmeans clustering algorithems to compress given images

FLARE is a novel approach to redefine the design of firewalls. Traditional firewalls generally rely on static rule sets, which can be exploited by advanced algorithms. FLARE provides a novel approac by designing Machine Learning based firewalls integrated with fedreated learning.

MATLAB implementation of the Constrained K-Means algorithm for Data Mining, clustering and classification tasks. Tested on Iris, Wine, and Breast Cancer Wisconsin datasets.

clustering of night time satellite images and depicting them by use of different colors

Uses K-Means clustering to uncover, group, and analyze top-streamed female artists (e.g., Taylor Swift, Beyoncé) based on popularity, followers, and genres.

A Python tool for extracting hidden numbers from Ishihara color blindness test images using a custom K-means clustering algorithm. Supports multiple color spaces (RGB, HSV, Lab, YCrCb) and includes visualization, CLI tools, and parameter optimization for enhanced accuracy.

This project systematically processes images through feature extraction, dimensionality reduction, clustering, and evaluation to enable intelligent image categorization

AI Machine learning Deep learning Projects with code