A KMeans implemented in C++ with Python bindings and GPU acceleration

Every year, students in the 5th semester get to enroll in a open course subject of their choice out of 12 electives. This data analysis project is a study on the trends and behavior's of student choices.

This repository contains the code and analysis for a research project aimed at enhancing social media impact for food safety security organizations. The project focuses on understanding text tone preferences based on user demographics using machine learning techniques.

R Markdown script to perform bioinformatic analysis of RNA-seq raw count matrices, including DE-testing via DESeq2 and gene set enrichment analysis (GSEA).

BPNN, K-means, K-medoids

Data Collection,Processing,EDA,visualization,application of machine learning to drive insights for given use case

An overview of all clustering techniques with examples of data.

This project analyzes a Portuguese bank's term deposit marketing campaigns, uncovering key factors and client profiles to optimize marketing strategies and enhance the bank's lending pool and revenues.

Machine learning models for enhanced fraud detection in e-commerce transactions, exploring feature engineering, distance prediction, and clustering analysis.

ML projects using a variety of different methods for solving classification problems

Implementations in Python for COMP425: Computer Vision. This repository covers edge and corner detection, image segmentation and clustering, ...

UAV Power Consumtion for Survivability in WPT WSN application

This team project is consists recommendation deck and monitoring dashboard for an Eco-Friendly Online Taxi Company by using K-Means and Hierarchical Clustering of CO2 emissions levels from various car brands.

The project aims at clustering of wholesale customers based on annual spending on different types of products by the clients of a wholesale distributor. K means clustering is adopted to identify similar clusters among the customer data. This is useful in various marketing techniques

Flora Genie is a personalized plant recommendation system designed to help amateur gardeners select the most suitable plants for their homes or gardens.

Creating a Website that has Machine Learning feature to predict Students Performance segmentation (using Clustering Model)

Este proyecto consiste en la construcción de un sistema de recuperación de información que puede manipular documentos de diferentes formatos provenientes de un repositorio de información. La aplicación utiliza herramientas como Lucene y Tika para indexar y extraer información de los documentos.

This repository contains a collection of labs that explore various machine learning algorithms and techniques. Each lab focuses on a specific topic and provides detailed explanations, code examples, and analysis. The labs cover clustering, classification and regression algos, hyperparameter tuning, data-preprocessing and various evaluation metrics.

Customer segmentation is essential for enhancing marketing efficiency and satisfaction. By categorizing customers based on demographics, interests, and purchasing behavior, companies tailor messages to engage each segment effectively. Our app utilizes advanced clustering algos like KMeans, DBSCAN, and AGNES to extract insights from data

Smartphone Dataset Analysis (Undergraduate)