A general-purpose algorithm for finding astrophysically-relevant clusters from point-cloud data.

density-based clustering for exploratory data analysis based on multi-parameter persistence

A generalised soft-clustering algorithm for propagating difficult-to-quantify effects into fuzzy clusters.

A simple python implementation of Fuzzy C-means algorithm.

Codes for Practical experiments of Data Warehousing and Mining (Semester V - Computer Engineering - Mumbai University)

K-Means Image Compression is a Python-based project that compresses an image by reducing the number of colors used. This technique is implemented using the K-Means clustering algorithm, making it ideal for those looking to understand and apply machine learning concepts in image processing.

Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.

Repository to store studies of machine learning algorithms implemented in artificial intelligence.

Predict the type of flower based on standard Iris dataset and deal with Image data (pixels) to predict hand-written digits (0-9) using K-Means Clustering Algorithm.

A general purpose Snakemake workflow to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data.

Repository containing code and databases for experimental analysis of the ranged k-median algorithm presented in the master thesis "Range-Centric Coresets in Dynamic Geometric Streams"

Python package for clustering categorical data

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

This project focuses on implementing face recognition for biometric validation. The scope includes understanding computational challenges in face recognition, conducting a literature review, and constructing a solution using existing methods.

Automated discovery and classification of websites content through unsupervised learning approach

Implementing LEACH protocol in a WSN using Python, aiming to increase energy efficiency, reduce system delay, energy consumption, packet loss.

Our Topological Hyperparameter Evaluation Mapping Algorithm.

Clustering with Agglomerative and DBSCAN algorithm Machine Learning

Developed and deployed a scalable machine learning model for real-time customer segmentation using FastAPI, Docker, Kubernetes, and GitHub Actions, with an end-to-end CI/CD pipeline on Azure Kubernetes Service, enhancing targeted marketing strategies through robust and seamless integration and deployment

Efficient implementation of object condensation losses for use in various projects