eltonmwema/Tanzania-Water-Wells-Classification

# TANZANIA-WATER-WELLS-PREDICTION-PROJECT # Business Understanding ## 1.1 Overview Tanzania is a developing country that struggles to get clean water to its population of 59 million people. According to WHO, 1 in 6 people in Tanzania lack access to safe drinking water and 29 million don’t have access to improved sanitation. The focus of this project is to build a classification model to predict the functionality of waterpoints in Tanzania given data provided by Taarifa and the Tanzanian Ministry of Water. The model was built from a dataset containing information about the source of water and status of the waterpoint (functional, functional but needs repairs, and non functional) using an iterative approach and can be found here. The dataset contains 60,000 waterpoints in Tanzania and the following features will be used in our final model: amount_tsh — Total static head (amount water available to waterpoint) gps_height — Altitude of the well installer — Organization that installed the well longitude — GPS coordinate latitude — GPS coordinate basin — Geographic water basin region — Geographic location population — Population around the well recorded_by — Group entering this row of data construction_year — Year the waterpoint was constructed extraction_type_class — The kind of extraction the waterpoint uses management — How the waterpoint is managed payment_type — What the water costs water_quality — The quality of the water quantity — The quantity of water source_type — The source of the water waterpoint_type — The kind of waterpoint The first sections focus on investigating, cleaning, wrangling, and reducing dimensionality for modeling. The next section contains 4 different classification models and evaluation of each, ultimately leading to us to select our best model for predicting waterpoint status based on the precision of the functional wells in the model. Finally, I will make recommendations to the Tanzanian Government and provide insight on p …