lukmani666/nigeria-food-market-price-tracker

# 🛒 Smart Price Tracker for Food Markets (Nigeria) A production-ready machine learning application for predicting food prices in Nigerian markets using XGBoost and LSTM models. ## 🌟 Features - **🎯 Price Prediction**: Accurate food price predictions using state-of-the-art ML models - **🗺️ Market Finder**: Discover markets with the lowest prices for specific commodities - **📊 Data Explorer**: Interactive visualization and analysis of market trends - **🔄 Model Comparison**: Compare XGBoost and LSTM performance metrics - **📍 Geographic Visualization**: Interactive maps showing market locations - **📈 Historical Analysis**: View price trends and patterns over time ## 🚀 Quick Start ### 1. Install Dependencies ```bash pip install -r requirements.txt ``` ### 2. Train Models **Option A: Using Python Script (Recommended for production)** ```bash python run_training.py ``` **Option B: Using Jupyter Notebook (Recommended for exploration)** ```bash jupyter notebook model_training.ipynb ``` ### 3. Test Models (Optional) ```bash python test_prediction.py ``` ### 4. Run Application ```bash streamlit run app.py ``` The app will open at `localhost` ## 📊 Models ### XGBoost Pipeline - Gradient Boosting with StandardScaler - LabelEncoder for categorical features - Optimized hyperparameters - Fast inference time ### LSTM Neural Network - 2-layer LSTM architecture - Dropout regularization - Early stopping - Captures temporal patterns ## 📁 Project Structure ``` ├── data/ │ └── nigeria_food_dataset.parquet # Dataset (54,883 records) ├── models/ # Trained models (created after training) ├── model_training.ipynb # Interactive training notebook ├── run_training.py # Automated training script ├── test_prediction.py # Model testing script ├── app.py # Streamlit web application ├── requirements.txt # Python dependencies ├── P …