- Analyzed extensive sales data from 2013, comprising 1559 products across 10 stores in diverse cities, with the objective of constructing a predictive model for sales estimation.
- Utilized Python libraries like pandas, matplotlib, seaborn, and scikit-learn to preprocess, visualize, and analyze the dataset, employing regression algorithms including Linear Regression, Ridge, Lasso, Decision Tree, Random Forest, and Extra Trees to develop robust predictive models.