classimbalance

mlim: single and multiple imputation with automated machine learning for R and Stata

End-to-end ML pipeline for stroke risk prediction with XGBoost, FastAPI API, and Streamlit dashboard — designed to handle severe class imbalance and maximize recall.

WeLT-ASpERT Trainer

Knee osteoarthritis grading on the Kellgren–Lawrence (KL) scale from X-rays, with custom CNNs trained from scratch, Grad-CAM, and an in-browser app.

Classification model was created to conduct an analysis that can detect the Non- Human Traffic presence on website using, Gradient Boosting Classifier & RF.

The aim of this project is to predict fraudulent credit card transactions using machine learning models.

Unofficial pytorch implementation on DAR-BN

Using deep learning models from hungingface ,fine tune them and creating streamlit app for sentiment analysis

A experimental project that delves in dealing with CI dataset using SMOTENN+GAN with dvc experimentation.

WeLT TablERT-CNN Trainer

A Comparative Analysis of Machine Learning Models for Credit Card Transactions with an Emphasis on Maximizing Recall.

ML pipeline predicting loan default risk — imbalance-aware training, cost-based thresholding, and SHAP explainability on 32K+ records.

Machine learning model for Credit Card fraud detection

WeLT-SpERT Model

Snakemake pipeline to reproduce the results in the forthcoming paper "One week ahead prediction of harmful algal blooms in Iowa lakes"

Class Imbalance

A deep learning project focused on musical instrument classification using Convolutional Neural Networks (CNNs). This project explores the use of different CNN architectures to classify musical instruments from images data.

Build a custom convolutional neural network neural network from scratch in Tensorflow to identify the type of skin cancer from image.