Mercywafula196/AI-for-SDG13-Climate-Action

A simple machine learning model that predicts Kenya’s CO₂ emissions to support SDG 13: Climate Action. # 🌍 AI for Sustainable Development ### Machine Learning Meets SDG 13: Climate Action **Project Title:** Forecasting Kenya’s CO₂ Emissions Using Machine Learning --- ## 📘 Project Overview This project demonstrates how **Artificial Intelligence** can support the **United Nations Sustainable Development Goal 13 (Climate Action)**. By using a simple **Machine Learning model**, we analyze Kenya’s historical carbon dioxide (CO₂) emissions and predict future emission levels to aid environmental planning and policy-making. --- ## 🎯 Objective - Apply **supervised learning** (Linear Regression) to predict CO₂ emissions per capita in Kenya. - Show how **AI can help monitor and reduce climate risks**. - Build a transparent and ethical model for sustainability insights. --- ## 🧠 Methodology 1. **Dataset:** CO₂ emissions data from the *Our World in Data* (OWID) repository. 2. **Preprocessing:** - Filtered data for Kenya. - Handled missing values. - Created lag features (previous 3 years). 3. **Model:** Linear Regression trained on historical emissions. 4. **Evaluation Metrics:** - Mean Absolute Error (MAE) - Root Mean Square Error (RMSE) - R² Score 5. **Visualization:** Compared actual vs predicted values and forecasted future emissions. --- ## 📊 Results - The model accurately captured historical emission patterns. - Kenya’s CO₂ emissions show a **steady upward trend** over recent years. - Forecast predicts a **slight increase** in CO₂ per capita for the coming year. Visualization example: