kartikkaul/ML-Based-Financial-Inclusion-In-East-Africa

Machine learning based Project to predict factors affecting financial inclusion of people living in East Africa # Financial-Inclusion-In-East-Africa This project aims to build machine learning models to predict individuals with a higher likelihood of owning/using a bank account. By doing so in Kenya, Rwanda, Tanzania, and Uganda, it provides insights into factors affecting financial security and measures financial inclusion across these regions. Key Highlights: 1. Utilized machine learning techniques to identify the most influential features for predicting poverty levels, highlighting the significance of cellphone access and job type. 2. Conducted comparative analysis of model performance, showcasing significant accuracy improvements in Random Forest and kNN models when utilizing the top 15 features. 3. Implemented different feature selection techniques like PCA, advocating for the strategic selection of methods to optimize model performance based on dataset and model characteristics.