FayselN/financial-inclusion-africa-ml

# 🌍 Financial Inclusion in Africa ## 📌 Project Overview The goal of this project is to build a machine learning model to predict which individuals are most likely to have or use a bank account. Understanding these patterns helps assess the state of financial inclusion in Kenya, Rwanda, Tanzania, and Uganda, and provides insights into the factors driving financial security across the population. ## 🎯 Problem Definition Financial inclusion is critical for economic development and poverty reduction. Many individuals in Africa lack access to banking services, which limits their ability to save, borrow, or invest. This project aims to: * Identify individuals likely to have a bank account * Understand the key features that drive financial inclusion * Provide a predictive model that can assist financial institutions and policymakers ## 📊 Dataset Description The dataset is provided by Zindi Africa for the competition Financial Inclusion in Africa. Files Included | File | Description | | ------------------------ | --------------------------------------------------------------------------------------------- | | `Train.csv` | Dataset including the target variable (bank account ownership). Use this to train your model. | | `Test.csv` | Dataset without the target column. Apply your model here to generate predictions. | | `variableDefinition.csv` | Full list of features and explanations. | | `samplesubmission.csv` | Example submission file in the correct format. | | `startupnotebook.ipynb` | Starter notebook to help create your first submission. | ## 🧪 Features The dataset contains demographic, socio-economic, and behavioral features. For detailed feature descriptions, refer to variableDe …