mlim: single and multiple imputation with automated machine learning

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.

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.

Unofficial pytorch implementation on DAR-BN

Class Imbalance

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

WeLT-ASpERT Trainer

Machine learning model for Credit Card fraud detection

WeLT TablERT-CNN Trainer

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.

WeLT-SpERT Model

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