Ogutu01/Tanzania-Water-Infrastructure

# PREDICTIVE MAINTENANCE FOR TANZANIA’S WATER INFRASTRUCTURE: A MACHINE LEARNING APPROACH. ### Author: Joy Achieng Ogutu ## INTRODUCTION Welcome to our presentation on Predicting Water Well Conditions in Tanzania. In this project, we deploy advanced machine learning techniques, specifically a well-tailored classifier, to gain insights into the state of water wells across the country. Our analysis is driven by a comprehensive dataset, encompassing various factors that influence the conditions of water wells. The primary objective of our project is to develop a predictive model that accurately estimates the conditions of water wells in Tanzania. This model aims to provide invaluable insights to different stakeholders, including NGOs focused on well rehabilitation, the Tanzanian government, and organisations dedicated to improving water infrastructure. Throughout the presentation, we will walk you through our project's methodology, key findings, and the model's performance in predicting water well conditions. Thank you for joining us on this journey to enhance water infrastructure management in Tanzania. ## PROJECT OVERVIEW ### Tanzania's Water Infrastructure Background. Tanzania, an East African nation with a population exceeding 57 million, faces significant obstacles in ensuring consistent access to clean water. The country's diverse geography, ranging from coastal plains to mountainous regions, significantly influences the distribution and availability of water resources. In many Tanzanian communities, wells serve as essential water sources, addressing the daily needs of both urban and rural populations. However, this reliance on wells introduces a set of challenges. To comprehend this intricate challenges, stakeholders must understand the factors influencing well functionality, most of which align with the columns provided in our dataset: - Population Pressure: With a population of over 57 million, Tanzania is a developing nation where providing access t …