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Loan Default Prediction using ML Classification
This project builds a data-driven pipeline for loan default prediction classification 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.
Heart Disease Risk Prediction using ML
This project builds a data-driven pipeline for heart disease risk prediction 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.
Employee Performance Evaluation System using ML
This project builds a data-driven pipeline for employee performance evaluation 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.
Air Quality Index Prediction System using ML
This project builds a data-driven pipeline for air quality index prediction system 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.
Stock Price Trend Prediction using ML Regression
This project builds a data-driven pipeline for stock price trend prediction regression using Random Forest and 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.
Credit Card Fraud Detection using Anomaly Detection
This project builds a data-driven pipeline for credit card fraud detection 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.
Employee Salary Prediction using ML Regression
This project builds a data-driven pipeline for employee salary prediction regression 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.
Customer Lifetime Value Prediction using ML
This project builds a data-driven pipeline for customer lifetime value prediction 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.
Used Car Price Prediction System
This project builds a data-driven pipeline for used car price prediction 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.
Telecom Customer Churn Prediction System
This project builds a data-driven pipeline for telecom customer churn 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.
Crop Yield Prediction using ML Regression
This project builds a data-driven pipeline for crop yield prediction regression using Random Forest and 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.
Movie Recommendation System using Collaborative Filtering
This project builds a data-driven pipeline for movie recommendation 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.