TejasM76/Tanzania-Water-Pump-Predictive-Maintenance

This project utilizes machine learning to predict the functionality of water wells in Tanzania. By analyzing data on existing wells, the model aims to identify wells that are functional, non-functional, or in need of repair. This information can be crucial for NGOs and local authorities to prioritize maintenance efforts and ensure clean water acess # 💧 Tanzania Water Pump Predictive Maintenance A humanitarian Machine Learning project aimed at predicting the functional status of water wells across Tanzania. By analyzing historical maintenance records and geographical data, this model accurately classifies pumps as "functional", "non-functional", or "needs repair", allowing NGOs and local governments to optimize their logistical repair routes and ensure consistent clean water access. ## 🚀 Key Features - **Predictive Maintenance Multi-Class Classification:** Forecasts equipment failure before it happens. - **Geospatial Data Analytics:** Processes complex GPS and regional metadata to identify high-risk geographic clusters. - **High-Impact Application:** Directly optimizes real-world logistics for humanitarian organizations. ## 🛠️ Tech Stack - Python (Jupyter Notebooks) - Scikit-Learn - Pandas / Matplotlib - XGBoost / Random Forest Classifiers