Predictive Analytics for Jewelry Sales Using Time Series and Machine Learning

The project focuses on developing advanced predictive models to forecast sales for a jewelry company. By integrating statistical methods and machine learning algorithms, the research aims to improve the accuracy of sales predictions and provide actionable insights for inventory management and strategic planning. The project utilizes historical sales data, seasonal trends, and economic indicators to build robust predictive models. Key applications include demand forecasting, revenue management, and promotional planning. The outcomes are expected to aid the company in optimizing operations and enhancing customer satisfaction.