R codes for common Machine Learning Algorithms

Prediction of a readmission for a patient based on the Electronic Health Records (EHR) data. This project was done as part of a timed challenge with a time limit of 3 hours to work on this dataset. So, it is just a preliminary model using XGBoost algorithm with some basic data exploration for data processing.

Extreme Gradient Boosting (XGBoost) with R and H2o for Stroke Prediction

The main objective of this project is to build a model to identify whether the delivery of an order will be late or on time.

Machine Learning Project on Imbalanced Data in R

Ist Place Solution

Prediction of Order Returns of an Online Clothing Retailer (Real-World Data) With XGBoost and Random Forest

This code provides a glimpse on how to analyse Churn, Appetency and Upselling using R

Credit Card Fraud Detection

Practice project using Kaggle competition data on NYC Taxi Trips

Machine learning algorithms applied to the property value project.

Predicting Credibility using Gradient Boosting - Comparison Simple Tree, Random Forest and Boosted Trees (ML Course SS18)

Deep Learning & Parameter Tuning with MXnet, H2o Package in R

Hackathon by Analytics Vidhya - October 2016 - Rank Top 30 nationally

Machine learning models build on real time data

Perfect Rating Score Prediction (Binary YES/NO): This model predicts whether a listing will achieve a 100% perfect rating score, helping hosts understand the likelihood of achieving top-tier guest satisfaction. The models will utilize 56 features extracted from Airbnb's data, including amenities, location, price, and host response rates