onyangoju/1-Financial-Inclusion-in-Africa

Challenging Financially Inclusive Africa # Financial Inclusion in Africa – Zindi Challenge **Due:** 8 Feb by 0:59 **Points:** 100 **Submission:** File upload **Availability:** 2 Feb at 1:00 – 9 Feb at 0:30 --- ## 📘 Overview Zindi is a platform that hosts data science competitions aimed at solving real-world challenges in Africa. This repository documents my participation in the **Financial Inclusion in Africa Challenge**, where the goal was to use data to predict which individuals are most likely to have or use a bank account. Financial inclusion is a key step toward economic development, and this challenge provided an opportunity to apply machine learning to a real-world socioeconomic issue. --- ## 🎯 Learning Objectives - Gain practical experience using supervised machine learning on real data. - Analyze, prepare, and model data individually. - Practice using metrics such as accuracy, precision, and recall to evaluate models. - Engage with the wider data science community through the Zindi platform. --- ## 🛠️ Process - Explored the dataset to identify the target variable (`bank_account`). - Examined important features such as age, gender, education, and location. - Cleaned and preprocessed the data (handled missing values, encoded categorical variables, ensured dataset alignment). - Built supervised learning models (e.g., logistic regression, decision tree, random forest). - Evaluated models using accuracy, precision, and recall. - Generated predictions and submitted them to Zindi for leaderboard scoring. --- ## 📂 Deliverables - **Reflection Note (PDF/Word)** - Methods tried - Challenges faced - Key insights about financial inclusion - Lessons learned from the competition - **Leaderboard Screenshot** - Captured score on the Zindi leaderboard --- ## 👩‍💻 Author This work was completed individually by **Pauline Onyango** as part of the Zindi *Financial Inclusion in Africa Challenge*.