Hospital admission data was analyzed to accurately predict the patient’s Length of Stay at the time of admit so that the hospitals can optimize resources and function better.

Implement common statistical machine learning algorithms with raw Numpy.

Introduction to XGBoost with an Implementation in an iOS Application

Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing

This project is a part of research on Breast Cancer Diagnosis with Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.

Credit Card Fraud Detection using Machine Learning

Angular 8 application for course project using AWS AND ML features

XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!

This project is a part of research on Breast Cancer Diagnosis with a Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.

Southern Data Science Conference Attempt 2020

Self-taught applications of Machine Learning Model XGBoost for COMP4650

Kaggle Competition (Encoding categorical variables)

Jupyter-Lab based setup for data science (Conda, TF2, XGBoost GPU)

build a model that accurately detect the presence of Parkinson’s disease in an individual.

Walmart Sales Forecast Solution

Built Random Forest and GBDT using XGBOOST model on Amazon fine food review dataset

Predictions and Analysis of Customer Churn for Telecoms Company with Plotly Dash Application.

An XGBoost model in Python that classifies if a customer will cancel his/her hotel booking or not. I also use counterfactuals guided by prototypes from the Alibi package to explore the minimum changes needed to flip a prediction from canceled to not canceled and vice versa.

Exploratory Data Analysis and Prediction on Pima Indians Diabetes Dataset