Cement Demand Dashboard & Forecasting
"A sophisticated tool that uses ML to forecast cement demand trends and improve production scheduling."
Country Clustering Using K-Means and PCA
Applied k-means clustering and PCA analysis to to group countries based on socio-economic and demographic indicators for insightful global comparisons.
S&P 500 Stock Prediction
Developed and deployed machine learning models using Random Forest and XGBoost to identify at-risk customers, enabling proactive retention strategies that reduced churn by 18%.
Healthcare Insights Dashboard
Interactive analytics platform that transforms healthcare data into actionable insights, featuring patient demographics, billing analysis, and ML-powered predictions.
E-Commerce Dashboard With Prediction
This interactive e-commerce analytics dashboard provides comprehensive business intelligence and predictive analytics for online retail operations. Built with Python and Streamlit, it transforms raw sales data into actionable insights through data visualization, statistical analysis, and machine learning.
Retail Product Association Analysis
Performed market basket analysis on transaction data to discover product associations and develop targeted cross-selling strategies that increased average order value by 12%.
Employee Performance & Engagement Dashboard
Designed a comprehensive HR analytics dashboard to track employee performance metrics, engagement scores, and attrition risks, enabling proactive talent management.
RFM Customer Segmentation Analysis
Used RFM (Recency, Frequency, Monetary) analysis and K-means clustering to segment customers and develop targeted marketing strategies for each segment.
Financial Time Series Forecasting
Implemented ARIMA, SARIMA, and Prophet models to forecast financial KPIs, providing reliable predictions for budgeting and business planning processes.