A Face Detection and Recognition system based on Eigenface method

Supervised Machin Learning Analysis using scikit-learn and imbalanced-learn libraries.

Using and comparing Support Vector machine, Random Branch Forest and Easy Ensemble algorithms to predict if a stock will have a positive or negative annual return.

Project on course "Data Mining 2"

Face Recognition by Eigenface method with the trained Feed Forward Neural Network and other classifiers applied to biometric attendance system functional on static-images.

Given the details of cell nuclei taken from breast mass, objective is to predict whether or not a patient has breast cancer using the Ensembling Techniques. This is a classification problem. The dataset consists of several predictor variables and one target variable, Diagnosis. The target variable has values 'Benign' and 'Malignant', where 'Beni…

Dynamic Ensemble Diversification

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

Analyze, visualize and predict customer churn using Machine Learning

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.

This project aims to build a strong sentiment analysis model for Amazon product reviews. It tackles class imbalance, uses diverse machine learning and deep learning approaches, and uncovers hidden customer sentiments, providing valuable insights.

Machine learning diabetes prediction mini project

Kernels for machine learning problems

Since 1946, all member states of the United Nations have come together at the United Nations General Assembly to discuss and vote on resolutions, among other things. Currently 193 states belong to the United Nations. Each of these member states has exactly one vote in the General Assembly’s resolution votes on issues such as disarmament, interna…

Machine learning project to classification of stars, quasars and galaxies

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

Ensemble of Narrow DNN Chains.

Predicted credit risk using resampling models, SMOTEENN algorithm and Ensemble classifiers.

The project entails building a model that predicts if someone who seeks a loan might be a defaulter or a non-defaulter. We have several independent variables like, checking account balance, credit history, purpose, loan amount etc. Ensemble Models such as Bagging, AdaBoosting, GradientBoost, XGBoost, Random Forest etc will be used for the modelling

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.