Sequential and Parallel(using Open MP and Pthreads) Implementations(c++) of the K Means Clustering Algorithm and visualizing the results for a comparative study of the Speedup and Efficiency achieved in 3 different implementations

Parallel implementation of K-means Clustering algorithm using OpenMp in C

Implemented the parallelized version of k-means clustering algorithm in Spark and assess its efficiency using a real-world dataset.

Parallel Kmeans project developed using Pyspark and CloudVeneto resources from the University of Padova

K-Means, Hierarchical Agglomerative, Density based and Map Reduce K-Means Clustering implemented on 2 Gene Datasets in Python