Machine Learning Powered Sales Analytics

Making use of publicly available datasets, this project conducted an in-depth Sales analysis across three diverse domains: Lifestyle, Merchandise, and Electronics. To uncover valuable insights, a variety of Machine Learning and Data Science techniques were applied. Clustering algorithms helped segment the data and identify patterns among different product categories. Advanced visualization tools were employed to create intuitive and informative graphical representations of the sales data, making it easier to understand trends and anomalies. Statistical modeling was utilized to analyze relationships within the data and to make informed predictions about future sales performance.