nguro23/Project-Tanzania-Water-Wells

# Phase III Project: Using classification model to predict the functionality of Tanzania water wells. ## Overview Tanzania is a developing country that struggles to get clean water to its population of 63.59 million people as of 2021. The goal of this project is to construct a classification model that can be used to predict the condition of water wells in Tanzania. This model will classify the condition of water wells into 3 categories namely:- - functional - the waterpoint is operational and there are no repairs needed - functional needs repair - the waterpoint is operational but needs repairs - non-functional - the waterpoint is not operational To construct this model, we used the data from Taarifa and the Tanzanian Ministry of Water. The approach for this project is to follow the OSEMN framework. The steps of this framework are as follows:- - Obtain the data - Scrub the data - Explore the data - Model the data - Interpret the data ### Obtaining the Data The data from Taarifa and the Tanzanian Ministry of Water is originally divided into 3 CSV files - - Test set values: The independent variables that need predictions - Training set labels: The dependent variable (status_group) for each of the rows in Training set values - Training set values: The independent variables for the training set Since there are no labels for the test dataset, we primarily use the training dataset to construct the model as well as test the various scores of the model. Then use the values of test data to generate predictions. ## Business and Data Understanding ### Stakeholder - Our project is focused on addressing a critical issue in Tanzania, a developing country where access to clean water is a major challenge for its population of over 63 million. - The primary goal is to develop a classification model capable of predicting the condition of water wells across the country. This model is not only for government bodies and NGOs working in Tanzania but also for local communiti …