Bonaparte003/linear_regression_model

This is a project for linear regression evaluation for Machine Learning at African Leadership University - year 2 - Trimester 3 # African SME Job Creation Predictor ## Eradicating Youth Unemployment Through Digital Transformation --- ## Live Deployment **API Endpoint**: `linear-regression-model-sef…` **Swagger Documentation**: `linear-regression-model-sef…` **Video Demo**: youtube.com](youtube.com **Mobile App Apk**: Click Me **N.B**: As the api endpoint is hosted onrender on a free tier - it's advisable to first make sure that the server is on by visiting this link --- ## Mission Statement **The Challenge**: Youth unemployment in Africa exceeds 20%, yet SMEs create 80% of all jobs. **My Solution**: Predict how many jobs an African SME will create based on their digital transformation strategies, revenue, and business characteristics. **The Impact**: Enable entrepreneurs, investors, and policymakers to identify high-potential SMEs for job creation, make data-driven funding decisions, and design effective digital transformation programs that maximize youth employment. --- ## Why This Matters - **Problem**: 60% of Africa's unemployed are youth (ages 15-24) - **Opportunity**: African SMEs employ 80% of the workforce - **Solution**: Machine learning predicts job creation potential with **97.9% accuracy** - **Action**: Target resources to SMEs that will create the most jobs This project directly addresses **UN SDG 8: Decent Work and Economic Growth** by providing actionable insights into which digital strategies help African businesses hire more young people. --- ## Dataset **Source**: African SME Digital Transformation Survey **Geographic Coverage**: 5 countries (Ghana, Kenya, Nigeria, Rwanda, South Africa) **Industry Coverage**: 6 sectors (Education, Farming, Finance, Logistics, Manufacturing, Retail) **Sample Size**: 1,000 real African SMEs **Target Variable**: Number of employees (direct job creation metric) **Features**: 30 comprehensive busines …