This portfolio demonstrates end-to-end predictive analytics capabilities across three business forecasting challenges. Part A implements ATM cash withdrawal forecasting for financial services, processing 1,500+ transactions across 4 machines to generate month-ahead predictions using ensemble methods (Prophet, SARIMA, ETS), achieving 7.2% MAPE through sophisticated feature engineering including payday effects, day-of-week patterns, and rolling statistics—delivering $70K annual savings per ATM through optimized cash management. Part B [provide your Part B description if applicable]. Part C tackles infrastructure monitoring by processing irregularly-sampled water flow sensor data from two pipes with misaligned timestamps, performing time-base sequencing to hourly intervals, conducting rigorous stationarity testing (ADF, KPSS, Phillips-Perron), and generating 7-day forecasts using Prophet with transparent uncertainty quantification. The complete portfolio showcases production-ready modeling, systematic data quality assessment, business-focused feature engineering, and professional communication of technical results to non-technical stakeholders, with all deliverables published via RPubs and provided in Excel format for operational deployment.

Research Funding Rates

A short vignette demonstrating a simple dplyr workflow on the built-in mpg dataset, including data exploration, a mutate transformation, grouping, summarizing, and identifying the top 5 manufacturers by efficiency.

In this project, we analyze the dataset containing sales and rating information of programming books being sold by the company. We are given the task to find the most profitable book title.

Exploring how algorithm speed changes as input grows.