Shiny mobile app that has users select whether headlines are real or fake (from Buzzfeed survey); connects to mysql DB on EC2

Final project using a survey commissioned by Buzzfeed to identify the factors that best predict whether someone can correctly distinguish between accurate and inaccurate news headlines

Classification using logistic regression and model selection criteria

Regularization using LASSO and ridge regression; cross-validation for parameter selection

Linear regression using different variable selection techniques

A lecture on the basics of exploratory data analysis using tidyverse as a TA for Wharton's Statistics Department's STAT701 - Modern Data Mining.

Building a model to predict whether or not a patient would be readmitted within 30 days after diabetic hospitalization

Text classification using logistic regression, SVM, and random forest; PCA

🔍 Streamline background checks with our platform, integrating natural language queries and real-time analytics for enhanced decision-making.