The project revolves around analyzing a comprehensive Black Friday sales dataset, encompassing diverse demographic and purchasing information. The dataset includes details such as user demographics, product categories, and purchase amounts.
The primary objectives involve exploring the relationships between various attributes, predicting purchase amounts using machine learning models, and understanding the impact of different factors on Black Friday sales.
The analysis encompasses data cleaning, visualization, and statistical approaches to derive insights into customer behavior and preferences during this prominent shopping event. Through the utilization of data science techniques, the project aims to contribute valuable information for retailers, enabling them to tailor marketing strategies, optimize product offerings, and enhance the overall Black Friday shopping experience.