Kitty4567/Tanzania-Water-Crisis

# Tanzania-Water-Crisis: Addressed the water and sanitation crisis in Tanzania, affecting 59 million people, with a focus on improving access to clean drinking water. ▪ Utilized machine learning models to predict the functionality of groundwater pumps across the country, aiming to enhance the efficiency of maintenance and repair operations. ▪ Analyzed data on water pump functionality, incorporating variables such as location, usage, and maintenance history. ▪ Performed exploratory data analysis (EDA) to gain insights and understand underlying patterns and relationships between various variables. ▪ Implemented machine learning models including logistic regression, decision trees, and random forests to classify the operational status of water pumps. ▪ Conducted data preprocessing and feature engineering to optimize model accuracy and performance. ▪ Evaluated model performance using metrics like accuracy, precision, recall, ROC score, and F1 score, ensuring reliable predictions. ▪ Visualized data insights and model results using tools like Matplotlib and Seaborn to support decision-making processes.