Integrative Biomechanical and Clinical Features Predict In-Hospital Trauma Mortality

This repository is associated with interpretable/explainable ML model for liquefaction potential assessment of soils. This model is developed using XGBoost and SHAP.

Predicting true low-VAF SNVs in HPV using triplicate NGS samples and machine learning

Includes top ten must know machine learning methods with R.

In this work an application of the Triple-Barrier Method and Meta-Labeling techniques is explored with XGBoost for the creation of a sentiment-based trading signal on the S&P 500 stock market index. The results confirm that sentiment data have predictive power, but a lot of work is to be carried out prior to implementing a strategy.

mlim: single and multiple imputation with automated machine learning

Applies Machine Learning approach to predict spam.

Comparison of ensemble learning methods on diabetes disease classification with various datasets

Big Mart Sales Prediction is a data-driven project aiming to forecast product sales accurately across Big Mart outlets. Leveraging machine learning and comprehensive datasets, our project empowers retailers to optimize inventory, enhance profitability, and make informed decisions in the dynamic world of retail.

Sports Analytics in R (Gradient Boost approaches for Decision Tree in Regression problems)

Using data to help us choice high quality wine

Credit Card Fraud Detection using Extreme Gradient Boosting

Detecting Fraudulent Blockchain Accounts on Ethereum with Supervised Machine Learning

Solution for the Ultimate Student Hunt Challenge (1st place).

Code for the project "Predicting hospital readmission of diabetic patients using ensemble learning"

This repo contains the result of my computer science course: An automated tool to classify credit card transactions. Could be used with any dataset

Identifying the most influential food groups on COVID-19 recovery rate: exploratory data analysis and statistical modeling

This project compares the different machine learning models on Walmart Weekly Sales Data and predicts the weekly sales for the test data.

Algorithms used to confirm whether a celestial body is a planet or not.

This repository contains several machine learning projects done in Jupyter Notebooks