Emmamems18/Emmanuel-Moemeke-Deliverable-Week-8---Capstone-Project---AnalystLab-Africa

Demonstration of practical skills acquired during internship exercise by completing an end to end data science project using real world data(The World Bank Dataset for predicting GDP Growth in African countries) # 🌍 African Economic GDP Predictor **"Africa's Numbers Don't Lie. But They Don't Tell the Whole Story Either."** An end-to-end Machine Learning pipeline predicting African GDP growth trends using World Bank macroeconomic data. Built as a Capstone Project for the AnalystLab Africa Data Science Internship. ## 📊 Project Overview This project investigates whether traditional macroeconomic indicators (like inflation, debt, and agricultural GDP) can accurately forecast economic trajectories across 54 African nations. The final output is a deployed web application that allows users to input economic metrics and receive an instant GDP growth estimation. ## 🗂️ Repository Structure * `african_countries_GDP_predictor.py`: The Streamlit web application code (Front-end). * `gdp_model_pipeline.pkl`: The serialized scikit-learn machine learning pipeline (Data Preprocessor + Gradient Boosting Model). * `requirements.txt`: The list of Python dependencies required to run the environment. * `African Economic GDP Predictor (Capstone Project).ipynb`: The Jupyter Notebook containing the full EDA, data cleaning, and model training processes. ## 🚀 How to Run Locally 1. Clone this repository to your local machine. 2. Open your terminal or command prompt in the project folder. 3. Install the required dependencies: ```bash pip install -r requirements.txt