Unlock the full machine learning workflow behind the paper “Strategic Customer Lifetime Value Prediction: Leveraging Machine Learning to Maximize Profitability in Retail.” This premium Jupyter Notebook package includes all Python code used for data cleaning, feature engineering, model training (Linear Regression & XGBoost), and RFM + K-Means customer segmentation.

Purchase Content

A complete business intelligence and analytics toolkit built from real 2023–2024 retail operations data. It visualizes sales trends, customer behavior, and discount performance, offering an end-to-end look at how analytics can drive data-informed retail decisions. Includes reproducible Jupyter Notebook code, a Streamlit-powered dashboard, setup documentation, and Kaggle dataset link.

Purchase Content

A fully annotated Stata script for preparing NHANES 2011–2018 data. This syntax merges socio demographic and BMI data(BMI, waist circumference), harmonizes education and marital status variables, restricts to adults (≥18 years), applies complete-case analysis, and sets NHANES survey weights. Ready for publication-quality analysis and fully adaptable for any NHANES dataset (1999–present).

Purchase Content