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.

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

Unofficial pytorch implementation on DAR-BN

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

WeLT TablERT-CNN Trainer

WeLT-SpERT Model

WeLT-ASpERT Trainer

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

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

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