Shravan Kanamadi
Computer Science at University of Hertfordshire
Data analyst with a focus on predictive modeling, Computer Science at University of Hertfordshire. Developed a machine learning model to predict CLV using RFM analysis and K-Means clustering. Collaborated on processing multilingual retail datasets, ensuring data quality and compliance.
Work by Shravan Kanamadi
- Predicting Customer Lifetime Value (CLV) Using Machine Learning: A Comparative Study of Random Forest and XGBoost with Behavioural Clustering
This project investigates the effectiveness of machine learning models in predicting Customer Lifetime Value (CLV) using the Online Retail II dataset. RFM (Recency, Frequency, Monetary) features were engineered and enhanced through K-Means behavioural clustering to segment customers. The study…