Talent Path
Global Mart Data Transformation
See post
here.
Team project designed to understand fundamentals of Azure. Case scenario to migrate on-premise datasets to the cloud while providing efficient storage, analytics services for transformation, and data warehouse for business analytics.
Modern Olympic Games Dashboard
View the dashboard
here.
This project was focused on learning how to build an interactive R Shiny dashboard.
Springboard
Recruit Restaurant Visitor Forecasting
See post
here.
A machine learning project that focused on predicting the number of visitors per day to over 700 restaurants. The model was created using historical data and additional features created using time-series functions.
Food Access Prediction
See post
here.
A machine learning project that aimed to predict the ratio of convenience stores to grocery stores in US counties. The model used datasets from the USDA, the Census Bureau, and the IRS to add multiple socioeconomic features to the store counts. Performance of different models: linear regression, random forest, and gradient boosting, was evaluated using a hold-out set and calculating an RMSE.