Monitor industrial machines in real time using sensors to track temperature, vibration, and sound, preventing failures through timely alerts.

A machine learning project to forecast agricultural crop yields using environmental and chemical factors. Developed by Team, The Outliers.

AI-powered smart healthcare monitoring system using ESP32, LoRa, and machine learning to enable real-time heart rate tracking, long-range data transmission, early risk prediction, and offline/local health dashboards for proactive healthcare monitoring.

A clean and modern machine learning project that predicts diabetes using the dataset, showcasing smart data preprocessing, insightful visualizations, and accurate prediction models all built to demonstrate the power of data science in early health risk detection.

Predictive modeling and RFM customer segmentation with Tableau and Python.

🔴 Planned

Customer churn prediction with Logistic Regression, Random Forest, Gradient Boosting, and SVM — includes threshold tuning and an interactive Streamlit dashboard