SuprajaPayyavula721/Pump-it-Up-Data-Mining-the-Water-Table

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 # Pump it Up: Data Mining the Water Table 💧🌍 ## 📌 Overview Access to clean drinking water is a critical public health issue. This research project employs machine learning techniques to predict the operational state of Tanzanian water pumps, utilizing the famous "Pump It Up" dataset from the Taarifa waterpoint mapping platform. ## 🚀 Key Features - **High-Impact Goal:** By predicting which pumps are functional, non-functional, or in need of repair, this model helps NGOs and local authorities prioritize maintenance and ensure clean water access for communities. - **Comprehensive Dataset:** Analyzed over **59,000** distinct water points. - **Complex Feature Engineering:** Evaluated numerous variables including geographical location, installation specifics, water point type, and management structure to build highly accurate predictive models. ## 🛠️ Tech Stack - **Environment:** Jupyter Notebook - **Techniques:** Data Cleaning, Feature Engineering, Classification Algorithms