Grocery Sales Forecasting System

Designed a predictive analytics solution to forecast grocery sales and uncover demand trends within a retail environment. The project involved data cleaning, aggregation of transactional records, exploratory analysis, and time-based sales modeling. Predictive insights generated from the model support inventory planning, operational efficiency, and strategic retail decision-making. This project highlights the value of machine learning in optimizing sales performance and reducing uncertainty in competitive retail markets.