k-Met is a phonetic clustering algorithm for grouping words by their approximate pronunciation. It uses fuzzy matching techniques and the double metaphone indexing algorithm.

Random pieces of C++ code

Data Clustering and Data Analysis Framework in Java

Visualization of k-Means and Fuzzy c-Means clustering algorithms

Scala implementation of clustering algorithms using Spark framework

An algorithm for clustering social network data.

Implementation of the K-Means++ Algorithm for better centroid initializations than the standard version of K-Means Algorithm

A tool to make dendograms from gene expressions.

SemesterProject repository

Data clustering algorithm based on agglomerative hierarchical clustering (AHC) which uses minimum volume increase (MVI) and minimum direction change (MDC) clustering criteria.

Agglomerative hierarchical clustering for sparse similarity matrices.

A fun review of spectral clustering with MATLAB demos I made for the NU machine learning meetiup in 2014

A D-Stream clustering algorithm implementation in Python

Predictive Analysis using Big Data platforms and Machine Learning Libraries

Clustering for modelling OECD Pisa scores (MSc Modelling for Science and Engineering, Modelling Workshop)

Square Packing As Algorithmic Art

Python implementation of the Nearest Subclass Classifier (NSC), based on Maximum Variance Clusters (MVC).

A clustering tutorial with scikit-learn for beginners.

Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree