iamchiboy/Ghana-Rain-Forecast

# Ghana Rain Nowcasting (30-Minute Prediction) **An AI-powered machine learning system for real-time rainfall forecasting in Accra, Ghana** This project collects real-time weather data, engineers predictive features, trains a machine learning model, and provides 30-minute rain forecasts through an interactive web dashboard. ## 🌟 Features - ✅ **Real-time Data Collection** - Automatic weather data fetching every 10 minutes - ✅ **Advanced Feature Engineering** - Rolling windows, lag features, derived meteorological indicators - ✅ **Robust ML Model** - Random Forest with cross-validation and performance metrics - ✅ **Prediction Confidence** - Probability scores and confidence levels for each forecast - ✅ **Interactive Dashboard** - Beautiful Streamlit interface with charts and metrics - ✅ **Production-Ready** - Error handling, logging, validation, and monitoring - ✅ **Secure** - Environment variable management for API keys ## 🏗️ System Architecture ``` OpenWeather API (10-min interval) ↓ Data Collection & Validation ↓ Feature Engineering (rolling, lag, derived features) ↓ Data Cleaning & Preprocessing ↓ Train/Test Split with Stratification ↓ Random Forest Classifier (300 trees) ↓ Cross-Validation & Metrics ↓ Live Prediction Module ↓ Streamlit Dashboard (Real-time visualization) ``` ## 📁 Project Structure ``` Ghana Rain Forecast/ ├── app/ │ └── dashboard.py # Streamlit web dashboard ├── src/ │ ├── __init__.py │ ├── config.py # Centralized configuration │ ├── logger.py # Logging setup │ ├── collect_data.py # API data collection with validation │ ├── preprocess.py # Feature engineering & preprocessing │ ├── train_model.py # Model training with validation │ ├── predict.py # Prediction module with confidence scores │ ├── rain_model.pkl # Trained model (generated) │ ├── model_metrics.json # Model evaluation metrics (generated) │ └── feat …