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A comprehensive R-based data analysis project that examines housing rental patterns across multiple cities, utilizing statistical methods and visualization techniques to analyze 4,746 properties' data points including rent prices, locations, and amenities. The project employs various R libraries to clean, process, and visualize rental market trends
Segment Sphere is a customer segmentation tool using RFM analysis to group customers based on recency, frequency, and monetary value. It processes e-commerce data, provides actionable insights, and visualizes results with interactive charts. Ideal for understanding customer behaviour and supporting data-driven decisions.
This project focuses on predicting employee attrition using machine learning techniques. It analyzes factors influencing employee turnover, such as job satisfaction, work environment, and compensation. By leveraging data preprocessing, feature selection, and classification models, the project provides insights for retaining valuable talents.