Pusion (Python Universal Fusion) is a generic and flexible framework written in Python for combining multiple classifier’s decision outcomes.

Final Project on how to detect domains that were generated using "Domain Generation Algorithm" (DGA). The idea is to tell DGA-generated and non-DGA-generated domains apart using a combination of linguistic features by transforming raw domain strings to ML features.

Analyze, visualize and predict customer churn using Machine Learning

Developed and evaluated machine learning and deep learning models for detecting financial fraud.

Predictive Modeling for Cardiovascular Disease Prevention

A multiNER websevice based on the KB's multiNER

RED CoMETS: an ensemble classifier for symbolically represented multivariate time series

A summary of my approaches for the Diabetic Retinopathy Image Classification Dataset

Dynamic Ensemble Diversification

An ensemble model created to classify images of currencies of 211-different classes. Winning entry for the https://www.kaggle.com/competitions/currency-prediction-challenge with around 88% accuracy.

Two ensemble models made from ensembles of LightGBM and CNN for a multiclass classification problem.

Machine learning diabetes prediction mini project

This repository contains the code for a web-based diabetes prediction application using a machine learning model. The application is built using Flask and allows users to input various health parameters to predict the likelihood of diabetes using ensemble voting classifier.

This project focuses on predicting the likelihood of a person having diabetes based on various health-related attributes using Random Forest Algorithm

This project focuses on predicting the likelihood of diabetes in individuals using ensemble machine learning models. It combines various ensemble techniques, including Random Forest, AdaBoost, Gradient Boosting, Bagging, Extra Trees, XGBoost, Voting Classifier and some others to get predictions.

머신러닝1 팀프로젝트 '위험/위급 상황 음향 분류 AI 모델 제작' 결과물 입니다.

Supervised machine learning models to monitor the condition of installed water pumps across Tanzania

Project on course "Data Mining 2"

This repository contains a machine-learning project that focuses on classifying different types of glass based on their chemical properties. The dataset comprises various features, including refractive index, percentage of elements like sodium, magnesium, aluminium, silicon, potassium, calcium, barium, and iron, as well as the type of glass.