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Working IoT, AI/ML and embedded builds with abstracts, component lists, documentation, and developer support — ready for your final-year submission.
Social Media Ad Click Prediction using ML
This project builds a data-driven pipeline for social media ad click prediction using Gradient Boosting (LightGBM/XGBoost) trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Water Quality Classification System using ML
This project builds a data-driven pipeline for water quality classification system using ensemble stacking of multiple classifiers trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Credit Score Classification using ML
This project builds a data-driven pipeline for credit score classification using regression models (Linear, Ridge, Lasso) trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Predictive Maintenance for Industrial Machines using ML
This project builds a data-driven pipeline for predictive maintenance for industrial machines using Gradient Boosting (LightGBM/XGBoost) trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Disaster Survival Risk Prediction using ML
This project builds a data-driven pipeline for disaster survival risk prediction using K-Means and hierarchical clustering trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Hospital Readmission Prediction using ML
This project builds a data-driven pipeline for hospital readmission prediction using K-Means and hierarchical clustering trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Insurance Premium Prediction System using ML
This project builds a data-driven pipeline for insurance premium prediction system using Gradient Boosting (LightGBM/XGBoost) trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Product Recommendation Engine for E-Commerce using ML
This project builds a data-driven pipeline for product recommendation engine for e-commerce using regression models (Linear, Ridge, Lasso) trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
House Rent Prediction System using ML
This project builds a data-driven pipeline for house rent prediction system using Decision Trees and Random Forest trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Retail Demand Forecasting using ML Models
This project builds a data-driven pipeline for retail demand forecasting models using ensemble stacking of multiple classifiers trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Student Performance Prediction using ML Algorithms
This project builds a data-driven pipeline for student performance prediction algorithms using K-Means and hierarchical clustering trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Bank Marketing Campaign Success Prediction
This project builds a data-driven pipeline for bank marketing campaign success prediction using regression models (Linear, Ridge, Lasso) trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.