Hierarchical divisive clustering algorithm execution, visualization and Interactive visualization.

Python Program for Text Clustering using Bisecting k-means

Naive Implementation of Machine Learning Algorithms in distributed frameworks MapReduce and Spark

K-Means and Bisecting K-Means clustering algorithms implemented in Python 3.

Build and evaluate clustering models using PySpark 3.0.1 library.

SDLDpred - Symptom-based Drugs of Lifestyle-related Diseases prediction

My master thesis – It is about clustering of product data as provided by typical product information management systems.

PySpark - Clustering with Kmeans++ and Bisecting K-means

CS F320: Foundations of Data Science Assignment

Implemented an auto-clustering tool with seed and number of clusters finder. Optimizing algorithms: Silhouette, Elbow. Clustering algorithms: k-Means, Bisecting k-Means, Gaussian Mixture. Module includes micro-macro pivoting, and dashboards displaying radius, centroids, and inertia of clusters. Used: Python, Pyspark, Matplotlib, Spark MLlib.

Clustering the given text data using a variation of DBSCAN

Successfully performed unsupervised clustering on student social network profiles to identify behavior patterns and group similarities, aiding in personalized engagement and targeted academic interventions.

Scalable PySpark implementation of clustering and classification on the Iris dataset, employing K-means, bisecting K-means, and decision-tree algorithms for high-performance botanical data analytics.