EmmanuelOchieng01/kenya-agro-weather-predictor

AI-powered crop yield prediction for Kenyan farmers using ML # Kenya Agro-Weather Yield Predictor Developed an AI-powered crop yield prediction system for Kenyan farmers using Python, Scikit-learn, and Flask. Collected 10,000+ weather records, trained ML models achieving 80% accuracy, and deployed an interactive web application. # Overview This project uses Machine Learning to predict crop yields for **Maize, Beans, and Groundnuts** across Kenyan counties based on: - Historical weather patterns (2015-2024) - Soil properties - Growing seasons - Climate conditions # Live Demo Web application with interactive predictions # Key Features Real Weather Data- 10,000+ records from Open-Meteo API - ML Model - Random Forest with 80% accuracy (R² = 0.80) - 3 Counties - Nairobi, Mombasa, Nakuru - 3 Crops- Maize, Beans, Groundnuts - Web Interface - User-friendly prediction dashboard - 180+ Training Samples- Robust model training # Quick Start ```bash pip install pandas numpy scikit-learn flask requests ``` Run: PROJECT1.ipynb Access: localhost Tech Stack Python | Pandas | Scikit-learn | Flask | NumPy License MIT License